Voice AI technology drives a $12 billion market projected to quadruple by 2029. Major companies such as Amazon, Apple, and Google have already demonstrated its potential. Today, voice AI is much more than simple command systems and preset responses — it handles complex conversations, grasps context, and provides human-like interactions at scale.

For business leaders and developers, this translates to automated customer support, multilingual communication, and accessible digital experiences. With 157 million users expected to rely on voice agents by 2026, companies need to integrate Voice AI to stay competitive.

Here's your guide to voice AI's components, applications, and business impact.

What is an AI voice?

AI voice is a technology that simulates human-like speech from text inputs or other sources using deep learning models trained on real voice data. It creates natural-sounding voices that can be customized based on gender, age, accent, and emotions.

Using AI voice agents in businesses means you slash support costs and offer 24/7 availability — like Bank of America's virtual assistant Erica, which handles over 2 billion customer interactions.

With AI voice, you can automate customer service, handle high call volumes, and provide consistent service quality across all customer interactions through voice bots and IVR systems. Modern AI voice tools analyze speech context, understand user intent, and generate appropriate responses without human intervention.

How do AI voices work: A detailed breakdown

AI voice systems convert human speech into actionable computer responses through five core components — each handles a specific task in the voice interaction chain. Here’s a walkthrough of these components.

Automatic speech recognition (ASR)

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ASR is the first step to speech-to-text conversion. When users speak to a voice assistant or call customer service, ASR converts their speech into text in a few steps:

• Audio capture: First, ASR captures audio through your microphone and splits it into tiny segments of 10-20 milliseconds. It then converts these segments into spectrograms — visual maps that show sound frequencies over time.
• Sound analysis: Deep learning models analyze these spectrograms and match them to phonemes (basic speech units). The system's neural networks break down the audio, compare it against existing speech patterns, and identify matching words from its data pool.
• Noise management: ASR filters out background noise and audio glitches that could affect accuracy before processing the text.
• Speech processing: Finally, a language model combines the identified phonemes into words and sentences. It checks the probability of word combinations to ensure that the transcription makes sense in the user's target language.

Modern ASR handles diverse accents, speaking speeds, and background conditions. The flexibility makes it effective for customer service, voice commands, and automatic transcription.

Natural language processing (NLP)

Next, NLP converts the text from ASR into meaningful actions. Here's how:

• Text breakdown: NLP splits user input into analyzable chunks and runs a syntactic analysis (checking word patterns and sentence structure). 
• Meaning extraction: The system collects the core meaning from text and analyzes it semantically (context and word relationships) to understand the user intent.
• Entity recognition: NLP spots and labels key information like customer names, account numbers, dates, and locations to process requests.
• Intent classification: The system identifies the specific action a user wants to take, whether it's checking a balance, scheduling an appointment, or filing a complaint.
• Sentiment analysis: NLP looks at word choice and phrasing to gauge user emotions and helps systems respond appropriately to satisfied or frustrated customers.

Dialog management

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Dialog management links the voice AI components together. It controls voice AI conversations through two core processes:

1. Dialog modeling

The system records essential information to maintain the conversation state. It tracks discussed topics, stores user-provided details and identifies missing information needed to complete requests. This data is often structured into slots in a form populated with values gathered during the interaction. 

For example, in a hotel booking conversation, it tracks check-in dates, room preferences, and guest information until all required fields are complete.

2. Dialog control

The system determines the next action based on the collected information. It decides when to request missing details, verify unclear inputs, or proceed with task completion. Confidence scores guide these decisions; high scores lead to task execution, while low scores trigger clarification requests.

For example, if the check-in date is unclear when booking that hotel room, the system will ask for confirmation before proceeding.

Natural Language Generation (NLG)

The process converts system decisions into human-friendly responses. It begins when NLG receives input from the dialog management system. This input contains the intent and relevant information needed for the response.

The system then structures this data into a logical sequence and applies grammar rules specific to each language.

For example, when recommending a product, the system converts structured data like: recommend(product="Premium Plan", features="24/7 support, unlimited calls") to natural responses: "Would you like to try our Premium Plan with 24/7 support and unlimited calls?"

Text-to-speech Synthesis (TTS)

Text-to-speech technology converts written text into spoken words. It follows these steps:

• The process starts with text analysis, where the system breaks text into processable units.

• Next, it converts these units into phonetic symbols that represent speech sounds.
• The system then adds prosody — the patterns of rhythm and sound in speech. This includes marking where to pause, which words need emphasis, and how to adjust tone.
• Finally, deep learning models generate audio waveforms that produce the actual speech output.

Modern TTS systems support different languages and voices and process thousands of requests simultaneously.Putting it all together: The voice AI workflowVoice AI creates a continuous cycle of speech processing and response generation. Here's how the components connect:

1. ASR captures user speech and converts it to text. When a customer asks, "What's my account balance?" ASR processes the audio and produces text output.
2. NLP analyzes this text to identify the user's intent — for example, checking account balance. It gathers key details like account references and command types.
3. The dialog manager takes this processed request and checks if it has all needed information, retrieves the account balance from the connected system, and decides how to present this information to the user.
4. NLG formats the response and turns raw data like "balance: $1,245.50" into a clear statement: "Your current balance is $1,245.50."
5. TTS converts this text response into spoken words delivered to the user through speakers or phone lines.

Plivo's Voice API lets you add call functionality across devices through server-side software development kits (SDKs) in multiple programming languages. You can create interactive voice response (IVR) menus with speech recognition, set up real-time coaching for agents, and detect answering machines for smart responses.The platform processes voice interactions in 28 accents across many languages and supports dual-channel call recording with encryption. Debug logs monitor performance, while webhooks keep you updated on on-call status.

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AI voice applications

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Voice AI is shifting business operations across industries with measurable impact. Let’s look at how these sectors leverage this technology.

Customer service

Voice AI balances automating interactions and conversation quality to deliver stellar customer services to businesses. The technology uses IVR systems to understand

natural language, route calls based on intent, and resolve common issues without human agents. These systems collect customer data, maintain conversation context, and transfer complex queries to live agents with relevant background information.

And the business impact — voice bots will reduce agent costs by $80 billion by 2026, with market growth projected at 23.3% through 2028.

Voice AI handles essential functions like intent detection, authentication, and technical troubleshooting. Companies see measurable results, too — 24/7 availability, simultaneous processing of thousands of conversations, and consistent response quality.

Plivo CX delivers these results with enterprise-grade IVR systems and voice bots that integrate with major platforms like Salesforce and Zendesk.  With this, you can:

• Integrate your voice AI with existing customer relationship management (CRM) systems.
• Monitor performance through real-time analytics, coach agents live, and optimize operations with 99.99% uptime.
• Deploy voice bots that process queries across 220+ countries and territories.

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Also read: How to Use AI to Analyze Phone Calls and Improve Customer Experience

Content creation

AI voice technology improves content production across multiple channels. For example:

• Podcasting creators use AI generated voices to convert written scripts to audio episodes without studio equipment.
• Marketing teams use AI voice generators for consistent brand messaging through video voiceovers, multilingual ads, and customer service greetings.
• Companies clone brand ambassador voices (with consent) for message consistency at scale.
• Publishers and authors turn books into audiobooks in days rather than weeks.

Accessibility

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Users with disabilities need more inclusive digital experiences. Yet, 98% of websites fail basic accessibility standards, which limits access to millions of potential users.

Businesses can fix this through AI voice to help users with visual impairments access digital content through advanced screen readers. Unlike traditional robotic voices, AI voice creates natural-sounding speech that improves comprehension and engagement. This matters for businesses because:

• Users spend more time with accessible content.
• Companies meet Web Content Accessibility Guidelines (WCAG) compliance requirements.
• More customers can access digital services independently.

AI voice converts written materials into audio formats for education and training to support employees with dyslexia or reading challenges.

Online retailers use AI voices to read product descriptions and reviews to make shopping accessible to visually impaired customers. The result? Increased sales plus brand loyalty among previously underserved groups.

Entertainment

AI voice helps reduce costs and speed up content delivery across multiple formats. The key applications are:

• Gaming: Create character voices and test dialog variations during development.
• Film and TV: Dub content in multiple languages and maintain continuity when human voice actors aren’t available.
• Advertising: Produce regional ad variations with a consistent brand voice.
• Animation: Generate character voices without multiple studio sessions.

Benefits of AI voice for businesses

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Here’s what AI voice means for your business:

• Streamlined customer support: Customer support teams handle cases faster through smart voice routing. The system qualifies leads, sorts urgent cases, and directs conversations to specialized agents based on intent recognition.
• Refined customer experience: Support teams receive prioritized call queues based on real-time voice sentiment analysis. The NLP engine learns from each interaction to refine responses, boosting customer satisfaction (CSAT) scores.
• Personalized and automated customer interactions: The platform learns to build customer profiles from each interaction. Voice patterns and conversation history shape responses so each conversation feels natural and informed.
• Reduced customer support costs: Voice automation cuts training costs and agent onboarding time. As the system manages routine conversations through NLP engines, new team members handle complex queries sooner.
• Used by differently-abled customers: Screen reader integration and voice commands make your services work for everyone. Customers with different abilities complete transactions independently using ASR technology.

Also, with Plivo-powered context-aware AI Voice Agents trained on knowledge base of choice, businesses can effortlessly manage everything from scheduling appointments and sending reminders to offering tailored financial advice. Boost your sales with AI-driven shopping assistance, break down language barriers in education through real-time translations, and provide outstanding customer support without a hitch. The possibilities are endless!

For your customers, this means:

• Self-serve: Customers get things done through simple voice commands. They check order status, update accounts, and solve issues without ever touching a keypad or screen.
• One-time data collection: Customers share information once, and you use it everywhere. The voice system securely stores customer data and shares it across your support channels so no one repeats their story.
• Less friction in communication: Voice AI removes communication barriers by letting customers speak in their language. They get instant answers 24/7 without navigating complex phone menus or facing language problems.

The future of AI voice technology and ethical considerations

Voice AI now combines multiple technologies to solve real business challenges. Some emerging voice AI trends include:

• Advancements in NLP create systems that learn your preferences and work habits, making every interaction count. Support teams can now communicate globally as these systems handle multiple languages, accents, and dialects.
• Voice systems work with cameras and motion sensors to understand what you see and do. Visual AI and gesture recognition let you control devices naturally in smart environments.
• The technology reads vocal patterns to detect your mood through tone analysis and deliver empathetic responses.
• The system learns your work patterns and routines through user profiling to respond based on contextual awareness (user location, schedule, and recent activities).
• Voice cloning lets you customize how the system speaks — use your own voice or choose from a library of options. The voice adapts to match different situations and conversations.
• Edge computing processes voice commands directly on your device, giving you instant responses and offline functionalities. Your data stays local instead of going to cloud servers, protecting privacy.
• Internet of Things (IoT) integration predicts what you need based on your habits and responds without you having to activate it first. One voice interface controls all your smart devices.

For those building and deploying these systems, privacy is crucial. Voice data needs data security protocols and consent policies. Voice cloning and sentiment analysis need guidelines to protect users and their data.

Your success with voice technology depends on getting this balance right. Build in privacy and security from the start, set clear guidelines, and you'll create systems your users trust and value.

Transform your communication strategy with Plivo Voice AI

With Plivo, there’s no room for privacy and security concerns. The enterprise-grade Voice AI platform provides the security protocols and infrastructure to launch context-aware voice bots while protecting customer data. You get immediate access to:

• AI integration: Connect with any STT, TTS, or LLM provider through simple APIs for maximum flexibility.
• Rapid recovery: Switch to backup networks in less than two seconds during outages to maintain operations.
• Dialog management: Maintain conversation context and natural flow across all interactions.
• Performance analytics: Track and optimize voice bot performance through detailed metrics and insights.
• Crystal-clear audio: 16kHz high-quality audio for smooth interactions.
• Unmatched reliability: 99.99% platform uptime for uninterrupted service.

Automate your support operations with Voice AI. Contact us to build your voice AI strategy.

Businesses have plenty of options when choosing CPaaS (Communications Platform as a Service) platforms, but two top contenders often stand out: Telnyx and Twilio. Both are feature-rich and reliable but excel in different areas.

For instance, Telnyx boasts a 91% customer satisfaction score, significantly outperforming Twilio in the category. Meanwhile, Twilio offers tiered support plans with varying response times and costs to accommodate diverse business needs.

The best communication platform for businesses rounds out the existing gaps of your CPaaS platform. Plivo is one such provider (we’ll explore it later in the article).

So, how do Telnyx and Twilio stack up? Let’s dive into a Telnyx vs. Twilio comparison to help you decide which fits your needs the best.

Telnyx vs. Twilio: A quick comparison

Before we dive into a detailed comparison, here’s a brief overview of both CPaaS platforms. Read on for an in-depth analysis of Twilio features, Telnyx capabilities, Telnyx API features, and their pricing structures.

Note: As per G2’s comparison report, Telnyx is rated an impressive 8.9 out of 10 as a CPaaS, edging out Twilio, which holds a solid score of 8.0.

Telnyx vs. Twilio: Detailed feature comparison

When it comes to SMS API comparison, both platforms offer solid solutions. They excel in programmable voice and messaging but differ in key areas such as pricing, customer support, and overall customer satisfaction.

Let’s take a closer look at these.

Telnyx SMS API features and use cases

Features

• Intelligent message encoding: Automatically get the most compact encoding possible, minimizing cost per send.
• MMS support: Drive two-way engagement with cross-channel messaging for MMS and more using a single API.
• Automatic opt-outs: Let your customers unsubscribe from future sends with a simple “stop word” message. (e.g. STOP)
• Message concatenation: Split and send a lengthy message into two messages without failures.

Use cases

• Account notifications
• SMS customer service
• SMS marketing
• Two-factor authentication (2FA)

Twilio SMS API features and use cases

Features 

• Screen-sharing and live chat: Add live chat, share screens, and create custom video players.

• Real-time route optimization: Automatically reroute global traffic every 75 seconds to avoid outages and latency.
• Messaging insights: Access real-time analytics for monitoring and troubleshooting message delivery and engagement.
• Message fallback: Benefit from automatic fallback to SMS when a message is not deliverable via WhatsApp or shortcode.
• MMS support: Drive two-way engagement with cross-channel messaging for MMS and more using a single API.
• ‍ Personalized messages: Customize messages for reminder notifications, delivery updates, and more.

Use cases

• Appointment reminders
• Delivery notifications
• Emergency alerts
• Send marketing messages (two-way communication)
• Account notifications
• Verifications and OTPs

Telnyx Voice API features and use cases

Features

• Media streaming: Access raw audio stream of calls in real time to integrate advanced artificial intelligence (AI) or machine learning (ML) capabilities.
• Text-to-speech and speech-to-text: Speak dynamic text in 29 languages and accents, powered by Amazon Polly, and get real-time transcription on a live call.
• Answering machine detection: Detect voicemail systems with exceptional accuracy using advanced AI techniques.
• Smart IVR: Build a multi-level IVR phone tree to intelligently route your call flows via voice commands.

Use cases

• Build a scalable IVR for a better customer experience
• Omnichannel marketing
• AI-powered conversations and voice analytics
• Manage a contact center
• Voice-based 2FA
• Customer survey and feedback collection

Twilio Voice API features and use cases

Features

• Actionable insights: Get actionable insights from your conversations with voice intelligence for a deeper understanding of every customer.
• Global conferencing: Add multi-party calling experiences, global dial-in support, and support for up to 250 participants with Payment Card Industry (PCI) and Health Insurance Portability and Accountability Act (HIPAA) compliance.
• IVR creation: Build a self-service auto attendant menu that customers can navigate in 100+ languages.
• Data security and compliance: Ensures all the messages and calls comply with HIPAA, General Data Protection Regulation (EU) (GDPR), American Institute of Certified Public Accountants (AICPA) Service Organization Control (SOC) 2, and Coalfire ISO certification.

Use cases

• Self-service customer support
• Voice-based lead qualification
• Real-time call transcriptions for compliance
• Voice-based lead qualification
• Automated call tracking in customer relationship management (CRM) systems

Telnyx Verify API features and use cases

Features

• Real-time reporting and insights: Get real-time analytics on verification success rates, delivery statuses, and user behavior to optimize verification workflows.

• Phone number validation: Identify and validate phone numbers in real-time, including carrier type, to prevent fraud and optimize delivery strategies.
• Multi-factor authentication (MFA) support: Integrate MFA with existing workflows to provide an additional layer of security for user logins and transactions.

Use cases

• Verify user identities during payment transfers, account changes, and other high-risk actions
• Safeguard sensitive patient data and meet HIPAA compliance
• Validate buyers and sellers before money transfers

Twilio Verify API features and use cases

Features

• Silent network authentication: Authenticate securely without user interaction, protecting accounts and transactions seamlessly within your app.
• Improved compliance: Build compliant healthcare and financial applications without requiring personally identifiable information (PII).
• Actionable insights: Access dashboards showing conversion and success rates by region and channel, along with SMS fraud trends to optimize fraud prevention.
• Multiple delivery channels: Deliver OTPs through SMS, WhatsApp, voice, and email, all via a single API.

Use cases

• Login protection
• Signup verification
• Personalize messaging and voice calls
• Improve message deliverability
• Enrich data and risk models

Twilio’s Flex and Engage

Twilio’s Flex and Engage are designed to help businesses deliver better customer experiences. Telnyx, on the other hand, doesn’t have a similar customer engagement tool suite offering real-time customer data analytics.

Let’s explore how Twilio’s tools support seamless communication and engagement.

Twilio Flex

Twilio Flex is a digital engagement center that lets you add a real-time data layer and AI capabilities to customize every sales and service interaction. With this solution, your customer service team can easily centralize support across chat, phone, and WhatsApp, customizing the interface to match their existing tools and processes.

Twilio Engage

Twilio Engage is a platform for personalized, data-driven marketing and customer engagement. It helps orchestrate real-time customer experiences from one central platform based on customer data across any communications channel.

Telnyx pricing vs. Twilio pricing

Let’s compare Telnyx pricing vs. Twilio pricing to get a clear view of how their cost structures compare.

Telnyx pricing

Note: Telnyx provides a lower-cost alternative for businesses needing cost-effective VoIP solutions.

Twilio pricing

Telnyx vs. Twilio customer support

Comparing Telnyx and Twilio in terms of customer support, both offer distinct approaches to assist businesses and end-users. This comparison highlights the key differences in their customer support plans.

Telnyx customer support

Telnyx goes beyond just offering communication solutions. It provides comprehensive, reliable support to ensure your business runs smoothly. Here’s how:

• Free in-house support: Talk to a telecommunications specialist via chat or call, available 24/7, year-round.
• Portal access: Set up, manage, and monitor your telecommunications through the Mission Control Portal.
• Automatic discounts: As your traffic hits higher volume thresholds, Telnyx applies discounts automatically.

Twilio customer support

• Developer plan: Provides basic support with API status notifications and web support, but no guaranteed response times.
• Production plan: Offers more robust support, with guaranteed response times for priority issues (3 hours for P1, 6 hours for P2, and 9 hours for P3), live chat support, and phone support, with a minimum monthly cost based on usage.
• Business plan: Delivers faster response times and higher-touch support, including phone and live chat. The pricing scale depends on monthly spending, starting at a minimum of $250 for the production plan.

Telnyx vs. Twilio: Pros and cons

We’ve outlined Telnyx vs. Twilio reviews to understand which solution provider better suits your business.

Telnyx pros and cons

Pros

• Users appreciate the intuitive and easy-to-navigate dashboard, which simplifies understanding and managing communications. (G2)
• Many reviewers highlight Telnyx's cost-effective pricing structure compared to competitors. (G2)
• Quick response times and effective issue resolution, enhancing user satisfaction. (TrustRadius)
• Developers find the API documentation thorough and intuitive, facilitating seamless integration into applications. (TrustRadius)

Cons

• Challenging to navigate initially, especially setting up SIP trunking and VoIP calls. (G2)
• A few users have pointed out that Telnyx could improve its interface and tools for handling bulk number queries and large-scale operations. (TrustRadius)
• Some users mention occasional latency or delays, especially during high-traffic periods. (Capterra)

Twilio pros and cons

Pros

• Users appreciate Twilio's straightforward API, which simplifies integration into various applications. (G2)
• Users like how it offers a wide range of communication services, including SMS, voice calls, and video conferencing. (G2)
• Highly scalable and reliable, making it suitable for businesses of all sizes. (G2)

Cons

• Some users find that while basic features are easy to use, advanced functionalities can be complex to implement. (G2)
• The pricing may be higher for businesses with high communication volumes, potentially affecting cost-effectiveness. (G2)
• Users report poor communication and a lack of accountability throughout Twilio's regulatory compliance process. (Trustpilot, TrustRadius)
• Their 2FA process is tedious which if you're not careful could result in you losing your number. (Capterra)

Why Plivo is the ideal alternative to Telnyx and Twilio

While Twilio and Telnyx are top players in the CPaaS space, having a second provider in your software stack can add a layer of reliability. As one of the top Twilio alternatives, Plivo can address the most common issues you may have:

• Inconsistent quality and deliverability in some regions
• Rising costs as the business’s customer base grows
• Lackluster customer support
• Ongoing technical issues

With direct connectivity to carriers in over 190 countries, Plivo ensures consistent quality and a 99.99% uptime guarantee, keeping your messages and calls on track.

Plivo also stands out with its six global points of presence (PoPs), strategically placed near high-traffic internet exchange points (IXP). This infrastructure provides your customers with top-tier voice call quality.

Plus, its developer-friendly, straightforward API documentation ensures an easy setup.

Additionally, with Plivo, you can save more as your business scales. It offers competitive pricing, along with volume-based discounts that start as low as $1,000.

Here’s a quick rundown of Plivo’s API solutions:

• SMS API: Plivo’s SMS API lets you send and receive text messages globally. Whether you're sending promotional offers, appointment reminders, or verification codes, Plivo makes it easy to integrate SMS into your application.

• Voice API: Plivo's Voice API allows you to make and receive high-quality voice calls, automate workflows with IVR, and even build custom call centers.

It takes care of three of the major call quality metrics: latency, jitter, and packet loss. You can see and monitor these metrics on the call insights dashboard that provides a quality score as a mean opinion score (MOS).

• Verify API: Plivo’s Verify API streamlines user authentication with 2FA, using SMS, voice calls, or email for businesses that need to securely verify users, or add extra layers of security during sign-ins. Plus, it addresses Telnyx use cases like MFA and fraud prevention like Twilio to secure user interactions.

• WhatsApp Business API: With Plivo’s WhatsApp Business API, you can engage with customers on the world’s most popular messaging platform. Plivo makes it easy to integrate WhatsApp into your business communication, allowing you to send order updates, customer support messages, and promotional content.

You can use Plivo as your primary provider or a failover option, addressing common challenges that Twilio and Telnyx may not fully resolve. Book a demo to know why thousands of businesses trust Plivo for efficient communication.

Managing large-scale conversations can be a challenge—especially for growing businesses.

To meet this demand, Meta launched the WhatsApp Cloud API in May 2022. This API lets businesses quickly connect with customers, offering a secure and scalable way to chat — no matter where they are.

While the Cloud API is easy to set up with no hosting fees, it does limit customization and control.

That’s where Plivo’s WhatsApp Business API comes in. Plivo offers more flexibility and control during setup, which can be beneficial for businesses in need of a more tailored solution.

In this guide, we’ll cover everything from setting up the Cloud API to real-world use cases, and also explore how Plivo’s API can offer more customization for businesses that need it.

WhatsApp Cloud API 101

Before launching the WhatsApp Cloud API, Meta offered three versions of WhatsApp:

• The standard WhatsApp app for personal use.
• WhatsApp Business for small- to mid-sized businesses.
• WhatsApp Business API for companies that needed advanced features.

So, what makes WhatsApp Cloud API different from all of these versions?

Let’s learn more about it.

What is WhatsApp Cloud API?

The WhatsApp Cloud API is a version of the WhatsApp Business Platform that runs on Meta’s cloud servers.

Unlike the older version, which required hosting on private servers or through a business solutions provider (BSP), the Cloud API removed the need for businesses to manage their own servers.

Why did Meta create the Cloud API?

The older on-premises API had its drawbacks. Set up took time, updates were slow to reach businesses, and server maintenance was expensive.

How does WhatsApp Cloud API work?

Here’s how the WhatsApp Cloud API works:

• Cloud-based architecture: Hosted on Meta’s servers, it provides a reliable and scalable infrastructure for messaging.
• Messaging capabilities: Businesses can exchange text, images, videos, and documents programmatically using API endpoints.
• Automation and bots: It supports automated workflows, such as sending appointment reminders or responding to frequently asked questions.
• Integration-friendly: The API connects seamlessly with other tools, streamlining customer communication processes.
• Multi-agent support: Teams can manage conversations collectively, ensuring faster response times and better customer service.

What’s the difference between the WhatsApp on-premises API and Whatsapp Cloud API?

Understanding the differences between the WhatsApp on-premises API and the WhatsApp Cloud API is key to choosing the right solution for your business.

Let’s explore how they compare.

WhatsApp business Cloud API features

The WhatsApp Cloud API comes with features that allow businesses to easily connect WhatsApp with their existing tools and workflows.

Here are its main offerings:

Seamless integration with Meta

Businesses can connect their systems to WhatsApp through Meta’s cloud platform. This ensures smooth and dependable communication with customers.

Versatile messaging options

The WhatsApp Cloud API supports text, media such as images, videos, audio, GIFs, and files, as well as contact cards and location sharing. It also facilitates interactive messages like list messages, reply buttons, and single or multi-product messages.

Additionally, businesses can use message templates for both text and media, incorporating interactive options for customer engagement.

Data access across platforms

The Graph API allows businesses to access and send data easily across different Meta platforms, including WhatsApp, Facebook, and Instagram.

It uses a single point of connection, so businesses don’t need to connect separately to each platform. This makes it simpler for businesses to manage data, whether it's about users, posts, or events, all from one place.

Global accessibility with no setup fees

The WhatsApp Cloud API is hosted in North America, but it allows businesses worldwide to connect with customers. This gives them access to WhatsApp’s large user base.

Meta offers the Cloud API for free, so businesses don't have to pay setup or access costs. However, businesses will still pay for the messages they send.

Easy-to-use API documentation

Meta offers straightforward API documentation, making it easier for developers to connect their systems to WhatsApp. This helps businesses build customized solutions and drive innovation.

Scalable and secure communication

The WhatsApp Cloud API enables businesses to scale their communications as they grow. It meets Meta’s strict security and privacy standards, ensuring both business and customer conversations remain secure.

How to get WhatsApp Cloud API

Setting up the WhatsApp Cloud API can vary depending on the method you choose. Here’s a quick comparison between using a BSP like Plivo and going through Meta directly.

Using an embedded signup

Signing up through a BSP enables you to complete the process in just a few steps. The signup flow is simple and stays entirely within the site.

Here’s how to do it with Plivo:

Step 1: Create a WABA in the Plivo console

To set up your WABA in Plivo, register a phone number that can receive an OTP via text or call. You'll use this number to message customers on WhatsApp.

You can either rent a number from Plivo or use your own. If you’re moving from another provider, you can transfer your number to Plivo.

Be sure to check Meta's guidelines and Plivo’s requirements for registration and migration.

Step 2: Customize your WhatsApp profile

Pick a display name for your WhatsApp account and follow the setup guidelines. Then, grant Plivo the necessary permissions to act as your WhatsApp solution provider.

Step 3: Verify successful onboarding

To confirm your setup is successful, check your Meta Business Account. First, choose your Meta account, then go to Business Settings and click on WhatsApp Accounts.

In the Partners tab, Plivo should appear as your partner.

Then, go to the Settings tab, where you'll find 'PLIVO INC' listed as a payment option.

Once you open "WhatsApp Manager," your number should show as connected.

Step 4: Register WhatsApp templates

Businesses must use WhatsApp messages templates approved by Meta. You can create new templates in WhatsApp Manager.

Meta segments templates into utility, marketing, or authentication categories, based on the message content. The category impacts both the conversation type and the cost.

In the Plivo console, you can find template information. Navigate to Messaging > WhatsApp Business Account > Templates to sync and view details from Meta.

Step 5: Manage your business phone number

Go to WhatsApp > WhatsApp Business Account to manage business phone numbers in Plivo.

Select your account and click on 'Configurations.' To add a phone number, use the ‘+Add Phone Number’ button found under account details.

After adding, you can also unlink numbers if needed.

This section also shows the connection status (whether it’s connected, pending, or disconnected), the name status (which reflects Meta’s verification), and the quality rating, based on how recipients respond to your messages.

Using Meta

Using the Cloud API through Meta requires development skills, such as making API calls to send and receive messages and setting up a webhook endpoint to handle message notifications.

You’ll also need to switch between Meta for Developers, your webhook server (like Glitch), and the WhatsApp application to test everything.

To learn more about these steps, refer to Meta’s documentation.

Note: Meta prohibits independent software vendors from developing the WhatsApp Cloud API for clients. Non-compliance with WhatsApp's Commerce Policy may lead to suspension or removal of API access.

WhatsApp Cloud API pricing

Businesses can access the WhatsApp Cloud API for free, but they pay based on their conversations with users.

Conversations on the WhatsApp Cloud API fall into two categories: user-initiated and business-initiated. A user-initiated conversation occurs when a user sends a message to a business, and the business responds within 24 hours. 

On the other hand, a business-initiated conversation happens when the business messages a user after the 24-hour window following the user's initial message.

WhatsApp offers the first 1,000 conversations each month for free. Once businesses exceed this limit, they must add a credit card to their account to continue using the service.

Even if a WABA has multiple phone numbers, the 1,000 free conversation limit still applies, and it resets monthly. In addition, businesses won’t incur charges when users contact them through the business’s call to action (CTA) button.

Pros of using the Whatsapp Cloud API

The WhatsApp Cloud API offers several advantages for businesses looking to integrate WhatsApp messaging into their customer service and communication workflows.

These advantages include:

Faster approval process

Previously, businesses had to go through BSPs and wait for approval before gaining access to the WhatsApp Business API. With the new approach, businesses can now directly access the API, removing the middleman.

Instant updates

Direct access to the WhatsApp Business API ensures that businesses immediately receive updates, including important security fixes.

Reduced costs

Traditionally, BSPs charged businesses for API access.

Now, with the WhatsApp Cloud API, Meta has eliminated setup charges, meaning businesses of all sizes can use the API at no cost.

Cons of using the Whatsapp Cloud API

While the WhatsApp Cloud API offers many benefits, there are also some potential drawbacks to consider:

Customization and control

The WhatsApp Cloud API is a ready-to-use solution managed by Meta. It makes setup and maintenance easy, but businesses can’t change its main features or underlying infrastructure. However, it allows for flexible integrations and workflow setups within its standard limits. For companies with complex needs or very specific requirements, this lack of control might be a drawback compared to on-premises options.

Support and service level agreement (SLAs)

Meta’s Cloud API support is general, whereas the on-premises API often includes specific SLAs and disaster recovery managed by BSPs. Businesses with high-stakes communication needs may find it challenging to operate without dedicated support. Downtimes or delays in issue resolution can impact critical service levels.

Plivo offers strong support with clear SLAs and disaster recovery measures. This dedicated service helps businesses maintain consistent, reliable communication when it matters most.

Feature parity and updates

The Cloud API may lack certain advanced features or update flexibility found in the on-premises API. Businesses using the Cloud API can face restrictions in accessing new tools or controlling update timing, limiting how they manage feature rollouts.

Plivo gives businesses more options, with multiple engagement channels like SMS, WhatsApp, and voice. Its additional features, such as marketing automation, provide flexibility beyond what the Cloud API offers.

For instance, Plivo allows businesses to provide customer support via a no-code AI-powered WhatsApp chatbot. This bot can handle routine customer inquiries, such as order tracking or store hours, without needing an agent. It reduces the workload on human agents and improves response speed.

Plivo also offers data-led routing, which uses customer data to direct queries to the right agents.

For example, if a returning customer has a technical issue, the system can route their inquiry to a dedicated technical support agent. This ensures the customer gets the right help faster and more efficiently.

Latency and performance

Meta’s North American data hosting can cause delays for international users, as requests must travel across continents. For global businesses, this lag can impact response times, making interactions feel slow and lowering user satisfaction.

Plivo’s network, with connectivity in over 220 countries and territories, routes requests closer to users to reduce latency. This setup helps businesses offer faster, more responsive service worldwide.

Automate your WhatsApp communication with Plivo

The WhatsApp Cloud API is fully managed by Meta, making it easier to set up and scale, but it gives you less control over infrastructure.

If you want something quick and easy, go for the Cloud API. If you need more customization and control, the Business API is the way to go.

Plivo offers a reliable and easy-to-use API platform that consolidates all your communication channels under one bill, contract, and point of contact. With competitive pricing and customer support ranked 99/100 for satisfaction on G2, you can count on us for top-tier service.

Plivo’s WhatsApp Business API makes managing customer interactions at scale effortless. Rich messaging and advanced automation tools not only improve customer satisfaction but also make your communication processes more efficient.

Ready to see how Plivo's WhatsApp Business API works for your business? Book a demo today!

Voice Artificial Intelligence (AI) is no longer just a futuristic concept — it’s here, reshaping how businesses engage with customers. With the conversational AI market set to jump from $13.2 billion in 2024 to $49.9 billion by 2030, voice integration is transforming industries.

From handling customer queries to automating workflows, voice AI redefines e-commerce, healthcare, finance, and many industries. It’s not just about commands anymore; voice AI now delivers context-aware, natural interactions that transform customer experiences with real-time assistance and a sense of personal touch.

In this article, we’ll discuss how voice integration in conversational AI drives change, its industry applications, and the advantages it offers for businesses and customers.

What is conversational voice AI?

Conversational voice AI focuses on voice-based interactions between users and machines under the umbrella of conversational AI. It uses speech recognition and natural language processing (NLP) to understand and respond to voice commands. Speech recognition converts spoken words into text, while NLP uses algorithms to understand the intent of the converted text.

The response then reverts to speech through speech synthesis.

Various devices, such as smart speakers, mobile apps, interactive voice response (IVR) systems, and even in-car voice systems, use conversational voice AI to improve user engagement and operational efficiency.

Sneak peek of conversational AI: The OG

Conversational AI comprises technologies and algorithms that create lifelike conversations between machines and users. Users interact with these technologies via:

• Customer support chatbots found in apps or on websites
• Smart assistants like Google Assistant or Amazon Alexa
• Customer support voice bots that handle queries over the phone

Conversational AI systems process voice commands, understand user queries, and provide relevant responses using NLP, machine learning (ML), and speech recognition.

The rise of voice technology in conversational AI

🗣️: Ok Google, navigate to the closest gas station.

🗣️: Hi Siri, remind me to pick up groceries at 10 AM.

🗣️: Alexa, set a timer for 5 mins.

Google, Amazon, and Apple have transformed voice-based interactions using conversational AI.

Voice integration in conversational AI provides a natural and intuitive way to interact compared to traditional text-based methods. It mirrors human conversation, making it faster and easier for users to communicate with AI systems.

With 97% of mobile users relying on AI voice assistants, voice-based conversational AI is now a regular part of daily life. Businesses are adopting voice AI to offer seamless, hands-free experiences as consumers grow familiar with voice commands.

Looking under the hood: Conversational voice AI and customer service

Conversational AI in customer service helps businesses offer instant support to customers and handle routine tasks with ease. Voice-enabled conversational AI answers queries, processes requests, and speeds up customer interactions. This improves efficiency, reduces wait times, and lets agents focus on complex issues.

Let’s explore the different applications of conversational AI that can amp up the game of customer experiences across the board.

Smart call routing

Voice assistants with conversational AI analyze customer inquiries and route calls to the right department.

Unlike traditional IVR systems that rely on keywords, voice AI maximizes IVR menu efficiency through natural language understanding (NLU), allowing customers to speak naturally.

Voice assistants also capture customer details, like names, account numbers, and requested services, giving agents all information upfront. This saves time for both customers and agents.

Omnichannel support

While text, email, and chat are standard communication channels, voice adds immediacy and a personal touch to customer service interactions, which other channels often lack.

With voice AI in their omnichannel support system, businesses can offer seamless platform transitions. For instance, a customer might use voice commands in-store to check product availability and continue the conversation online later.

This unified experience provides a smooth customer journey and boosts customer satisfaction and brand loyalty.

Pro Tip: Add customizable voice IVR to your omnichannel support and build a better brand perception.

Streamline authentication

Automating customer authentication with voice technology and conversational AI reduces time and costs. Additionally, voice authentication using NLP is a more cost-effective alternative to voice biometrics authentication, providing an equally smooth experience.

Simplify troubleshooting

Voice assistants powered by conversational AI and chatbots can handle much of the troubleshooting process, automating common issues and often resolving them without involving an agent. This reduces agents' time on repetitive tasks and boosts customer service operations.

If the bot can’t resolve the issue, it transfers the customer to a human agent. It also gives the agent a detailed record of already taken troubleshooting steps to ensure a smoother handoff.

More agent efficiency = Better customer experience.

Better security and reliability

In industries like finance and healthcare, security is paramount.

Voice AI integration provides robust security measures, such as encrypted voice recordings and secure data transmission. It protects sensitive customer data while meeting industry regulations.

A dependable voice platform with voice AI reduces downtime and ensures continuous service through a well-designed IVR system. For example, banking IVRs improve security and customer interactions and ensure a smooth, secure flow of information.

Multi-language support

Voice technology with conversational AI allows businesses to support multiple languages and create a more inclusive and accessible customer experience. For example, Plivo’s AI voice agents support speech recognition in 27 languages and their regional variants.

Using speech recognition technology, businesses can engage with diverse customer bases worldwide and offer personalized support in various languages. It helps companies enhance customer interactions and improve overall satisfaction.

Hands-free experience

98% of websites don’t provide basic accessibility features, limiting access to millions of users with disabilities. Voice-enabled conversational AI supports Web Content Accessibility Guidelines (WCAG) and allows more customers to access digital services independently.

Voice technology powered by conversational AI uses advanced speech synthesis to support users with visual impairments. It enables interaction with content through natural-sounding speech, making information easier to understand and more engaging.

These systems convert text into audio, providing access to online shopping, education, and training in a more inclusive way.

Personalization

Conversational AI platforms leverage customer data like browsing history and purchase behavior to offer highly personalized recommendations in real-time. For example, voice assistants can narrow down a general query about a mobile phone to a specific model based on the customer's preferences and budget.

Voice-enabled AI bots, like Plivo-powered voice agents, also guide customers from discovery to checkout, helping them:

• Compare products
• Suggest complementary items
• Offer specific discounts
• Upsell based on past purchases

Unlike text-based bots, voice agents are more personalized, adding a human touch to customer interactions.

Conversational voice AI for different industries

When a customer calls, they want to feel valued and understood. Conversational AI with voice recognition technology puts the customer at the center of the experience.

Here’s how voice AI transforms industries and enhances customer interactions across sectors.

E-commerce

Caption: Personalize customer’s shopping experience with Plivo-powered voice agents

Alt text: Image depicting Plivo-powered AI bots recommending products based on user input

E-commerce customers want quick responses and 24/7 support. If they don’t get it, they may choose a competitor.

While chatbots work well for tasks like answering FAQs or checking order status, voice integration in conversational AI transforms customer service and creates standout shopping experiences by:

• Assisting customers with product selection
• Offering personalized recommendations
• Automating the sales process

Integrating voice agents in customer relationship management (CRM) systems also provides real-time updates, such as order status, with just a voice command. Businesses are better suited to provide a 24/7 personalized shopping experience with quicker response times and higher customer engagement.

Education

AI voice integration with multilingual support can empower inclusive learning experiences in the education sector with personalized tutoring. Voice agents can instantly support students by providing real-time translations and remove language barriers by clarifying complex terms in their preferred language.

This integration reduces the need for multilingual staff, making learning more accessible for global students.

Healthcare

No industry values prompt responses more than healthcare.

Voice integration in conversational AI healthcare sectors improves customer experience, provides timely care, and improves operational efficiency. It simplifies patient care and delivers personalized support through:

• Medication reminders 
• Appointment scheduling
• Preliminary health assessments

In addition, voice agents help healthcare providers automate tasks, improve medication adherence, and lighten their workload, making services more efficient and patient-focused.

Finance

Conversational voice AI supports financial sectors with a forward-thinking approach. Voice agents improve the customer experience by offering quick, accurate responses without wait times. Banks use voice agents to:

• Automate routine tasks
• Provide instant account updates
• Process payments
• Deliver personalized financial advice 24/7

Approaches to deploying conversational AI for voice integration

When you're ready to implement voice-integrated conversational AI, you'll discover several ways to design, build, and deploy a voice assistant. Some approaches may appear cost-effective at first but quickly turn into obstacles, complicating deployment or causing user dissatisfaction.

Here are three primary methods for deploying conversational AI for voice:

1. Partner with a voice-first vendor

Partnering with a voice-first vendor like Plivo is the most efficient and effective way to deploy conversational AI for voice applications.

One of the key advantages of working with a vendor like Plivo is the speed and efficiency it brings to deployment. Instead of building a voice assistant from the ground up, businesses can leverage Plivo’s pre-built solutions and technical expertise. This accelerates time-to-market and reduces the burden on in-house development teams.

Plivo's platform is designed to handle the complexities of voice integration, such as managing call flows, ensuring compliance with global telecommunication standards, and delivering high-quality audio. Additionally, its APIs are highly customizable, allowing businesses to tailor their solutions to fit specific use cases.

2. DIY with a third-party platform

Another approach to deploying conversational AI for voice is using third-party platforms like Google DialogFlow or Amazon Lex. They can handle natural language processing and speech algorithms for your applications.

However, this option may limit control. Performance can vary based on language or application needs, especially in voice-heavy use cases.

3. Port chatbot technology into voice

Many businesses start with chatbots and attempt to convert them into voicebots.

Doing so involves integrating speech recognition and text-to-speech capabilities with the chatbot’s existing NLP engine. This allows the system to understand spoken input, process it, and deliver relevant responses through audio.

Nevertheless, transitioning from a text-based chatbot to a conversational AI voice agent can be challenging.

Chatbots are primarily designed for text-based communication, and the conversion process often leads to issues with speech recognition and intent detection, resulting in subpar performance. It also requires careful attention to voice-specific nuances, such as accommodating variations in accents, ensuring accurate speech synthesis, and optimizing dialogue flow for spoken interactions.

Note: While porting chatbot technology to voice can save time and resources compared to building a voice assistant from the ground up, it may lack the full customization and voice-centric features provided by dedicated voice-first solutions.

Get started with Plivo

Whether integrating AI features into your existing systems or considering third-party solutions, conversational voice AI empowers teams, drives efficiency, and enhances customer experience.

Plivo’s Voice API offers flexibility and seamless integration with your preferred speech-to-text, text-to-speech, and language model providers. It connects directly with OpenAI’s RealTime API through simple integration endpoints for instant deployment. Context-aware AI Voice Agents trained on custom knowledge bases support businesses to:

• Schedule appointments and send reminders
• Offer personalized financial advice
• Boost sales with AI-driven shopping assistance
• Break language barriers with real-time translations
• Deliver exceptional customer support with accurate responses

Plivo’s platform also offers industry-leading performance metrics, including 99.99% uptime reliability and low-latency global connectivity.

To explore the potential of Plivo-powered AI voice agents, contact us today.

Modern customers expect quick, intelligent, and personalized service across all touchpoints—be it phone, web, or mobile. Even small delays or miscommunications can negatively impact customer satisfaction and damage your brand’s reputation. 

AI-powered customer service can help address this challenge by assisting human agents in handling frequent and simple questions. In fact, a 2023 Gartner study notes that 80% of companies are seeking to implement AI-powered chatbots to level up their customer service by 2025.

This blog post will explore the capabilities of AI in customer support, including benefits and use cases. You’ll also learn to implement AI in customer service to enhance customer experience.

What is AI in customer support?

AI in customer support uses technology such as ML, NLP and text analysis to manage customer interactions and optimize the customer experience.

The key idea is to address customer requests swiftly, streamline internal workflows and anticipate customer needs proactively.

Benefits of AI in customer support

A report by Deloitte reveals that 15% of contact centers use Gen AI to drive faster customer authentication, summarize pre-interaction journeys and provide automated call summaries and follow-up recommendations. This reduces human error, saves time, and enables management to make unbiased decisions.

Let’s understand how implementing AI in customer service can further help in boosting efficiency and enhancing customer customer experience:

Round-the-clock support

Unlike humans, chatbots and virtual assistants can operate 24/7 to provide consistent customer service. This means customers don’t have to wait for business hours to receive support. They can connect at any time of the day and have their issues solved, significantly improving the customer experience.

Enhanced customer support workflows

AI can streamline internal workflows in various ways, such as:

• Automate routine tasks
• Prioritize, categorize and route tickets to the appropriate agents based on urgency and complexity 
• Analyze customer history to provide tailored solutions

Data-driven insights

AI’s expertise lies in processing and analyzing large volumes of data. This helps businesses get in-depth insights into customer behavior and preferences.

Based on these insights, business leaders can make informed decisions about product development, marketing strategies and overall customer service improvements.

Reduced employee burnout

Since AI takes over repetitive and mundane tasks, agents have time to focus on more challenging and innovative tasks, such as handling complex queries and tailoring support experiences. This not only improves customer service job satisfaction but also leads to better-quality customer interactions. 

Personalized customer interactions

AI can provide tailored recommendations and solutions by analyzing customer behavior and data, leading to a more personalized support experience. Your team can tailor interactions before and after purchase to ensure customers receive the best experience.

Prediction of customer behavior

Using real-time data, businesses can use AI to determine customer behavior based on their purchase history, buying habits, and personal preferences. This helps you identify customer needs even before they say it and proactively reach out to serve customers in the best way possible.

Challenges of AI in customer support

While AI has several remarkable advantages, it is not free of challenges. Businesses must be aware of its challenges to have a well-balanced and holistic approach to using AI. This will help maximize the benefits of AI while minimizing associated risks.

Here are some common threats associated with AI:

Data privacy and security

Protecting customer data is essential to maintaining customer trust and security. Businesses must comply with data protection regulations like the General Data Protection Regulation (GDPR) to maintain high-security standards and protect sensitive customer information. They must also communicate transparently with customers about processing and protecting their data.

Implementation

Implementing AI customer service solutions requires huge investment in technology, training, and integration. To ensure alignment with existing processes, businesses must meticulously plan and execute the deployment of these systems.

Gartner emphasizes that aligning AI tools with current workflows requires careful analysis of existing systems. Their research shows that 58% of companies experience delays in AI deployments due to challenges with integration into legacy systems.

Additionally, AI depends on large volumes of data to process and analyze behaviors. Inconsistent or incomplete data can lead to inaccurate predictions, which can result in poor customer experiences. 

Inability to handle complex customer issues

Despite being advanced, agile and adaptive, AI still struggles with complex customer queries that require nuanced responses. This can frustrate customers who expect quick and personalized answers. 

To ensure comprehensive customer service, the precision and speed of AI should be combined with empathetic and compassionate responses from human agents.

Adaptability to changes

Businesses need to continuously update and train AI systems to keep them relevant. For example, a predictive analytics tool must be apprised of current market trends and customer behavior to forecast accurately. This need for flexibility can pose a threat, especially for rapidly changing industries.

Lack of emotional intelligence

Interacting with highly automated systems eliminates the human touch of care and empathy. This can make customers feel detached from the brand. Additionally, customers may get frustrated when they receive generic responses for sensitive or complex queries.

Ways to use AI in customer support 

Now, let’s understand some of the most effective ways companies are implementing AI in customer support:

Chatbots

Chatbots are built for real-time assistance to manage large volumes of messages while creating a human-like experience. It can handle basic customer queries, provide instant responses, and assist with tasks such as product recommendation, order tracking, and troubleshooting.

Omnichannel customer service platform Plivo CX's self-service chatbot, developed and powered by OpenAI, can support businesses to resolve customer queries quickly.

The chatbot is suitable for businesses of all sizes and has these stand-apart features:

• In-app customer service enables customers to send and receive photos and documents easily
• 24/7 availability to resolve  queries instantly, allowing customers to pause and resume conversation at their convenience
• Complete customer context and interaction history from multiple channels available in a single platform
• Can be easily updated with new product information, promotions or policy changes
• Summarizes and transfers complex queries to human agents with complete context
• Accurately reflects your brand identity while adhering to the company’s policies and guidelines 

Self-service resources

AI can synthesize existing information and create answers for popular customer inquiry topics. This can be used to develop self-service resources to help customers find answers independently. Some of the common self-service resources include:

• Knowledge bases featuring house articles, how-to-guides, troubleshooting tips, and more
• Frequently Asked Questions (FAQ) pages containing answers to customer’s most common queries
• Interactive Voice Response (IVR) to provide pre-recorded answers 

Sentiment analysis

Sentiment analysis can uncover insights from customer conversations across channels to tailor responses based on the client’s needs and emotions. It can monitor and analyze customer feedback, reviews, and interactions to identify areas of improvement, respond appropriately and provide personalized experiences.

Speech analysis

AI-powered speech analysis can provide insights into customer interactions by evaluating vocal tones, pitch, and speech patterns to detect emotions like frustration, anger, or satisfaction during a call.  This helps agents tailor their responses in real time and show empathy and care during critical situations.

Omnichannel routing

Customers are usually frustrated when they have to repeat their problem every time they switch channels. Omnichannel routing is the best way to ensure customers have a consistent experience across all channels. It provides a complete history of customer interactions so that reps can easily handle every communication with continued context.

As a true omnichannel contact center, Plivo CX features a unified agent desktop, allowing your team to manage interactions in every channel (live chat, voice calls, SMS, email, or WhatsApp) from a single platform, eliminating the need to switch between channels. This can help simplify the communication process and improve response times. 

Predictive analytics

Predictive analytics can analyze large volumes of data and draw actionable insights to forecast trends, anticipate customer needs, and solve future problems. This helps businesses reach out to customers proactively and solve possible problems. For example, if a shipment delay affects the delivery schedule, you can proactively communicate and even offer a discount coupon to appease the customer.

Automated call transcription

Call transcriptions are essential to review customer conversations, quality assurance and training, and maintain compliance with legal requirements. It makes it easier for teams to reference past conversations, particularly in cases of follow-ups or escalations and identify trends and recurring issues. 

Analyzing call transcriptions can also help businesses identify opportunities for upselling.

Routing and prioritization

AI in customer service can analyze incoming inquiries and automatically direct them to the most appropriate agents or teams. This is done by evaluating factors such as urgency, customer history, and issue complexity.

AI can also identify high-priority cases to address them promptly while managing routine inquiries efficiently. 

Real-time data and analytics

Automating customer service with AI can help you get granular insights into critical customer interaction metrics such as AHT, FCR, and CSAT.

Businesses can use this data to evaluate agent performance, find areas of improvement and tailor strategies accordingly.

Steps to implement AI in customer service

A report by IBM revealed that 42% of enterprise-scale organizations with over 1,000 employees actively use AI in their business, and 59% of enterprises already working with AI want to increase their investment in the technology. 

If you are yet to implement AI in customer service, follow these key steps:

1. Evaluate business needs

Evaluate your existing customer service processes to identify pain points, areas that require faster response times or staffing needs. This will help you pinpoint areas where AI can be most effective, providing a solid base for implementing AI in customer service.

2. Define goals and objectives

Based on your business needs and requirements, set clear and measurable goals. These might include goals like increasing first-contact resolution, reducing average response times or improving overall customer satisfaction scores. Specific goals help you pick the right AI tools and measure their impact effectively.

3. Choose the right AI software

Once you’ve sorted your needs and objectives, select a tool that aligns with your requirements. Consider scalability, integration capabilities, user reviews, pricing, long-term viability and support when evaluating different options.

4. Integrate with existing solutions

The tools you choose must work well with your existing current customer systems, which may include API integrations, data sharing, or other technical setups. Ensure to conduct pilot tests to identify and address any integration issues before full deployment. This will help you resolve potential problems early in the implementation process.

5. Train your employees 

Deliver in-depth training for your customer service representatives on operating and integrating the AI tools into their workflows. Focus on covering technical functionalities and how to partner with AI to provide the best customer experience. Offer ongoing training and guidance and encourage feedback on the new processes.

6. Ensure compliance and data privacy

Ensure the AI tools can securely handle and store customer data by maintaining strict compliance with data protection and privacy regulations. Also, regularly review and update your privacy policies and practices to align with evolving regulations. 

7. Monitor and optimize frequently

Lastly, continuously review the performance of your AI strategy. You can track performance by assessing relevant metrics such as response times, CSAT scores, and resolution rates. Based on data insights, make necessary changes and adjustments to improve your AI systems and processes to meet customer needs better.

Examples of AI in customer support 

From chatbots, personalized recommendation engines, to more innovative uses, let’s discuss how some brands are implementing AI in customer support to offer superior experiences: 

Encore

Encore uses a GPT-4 model to allow users to find and buy second-hand items. The idea is simple, you have to type your query and get results from multiple resources, including Poshmark, Grailed, Etsy, and eBay.

For example, if you are looking for outfits like Carrie Bradshaw, typing “Carrie Bradshaw” in the search bar will give you an AI summary of the fashion statement along with all possible product recommendations.

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Stitch Fix

Stitch Fix uses machine learning algorithms alongside human stylists to tailor recommendations for its 3.5 million customers. Their AI systems analyze customer preferences and broader fashion trends to refine suggestions over time.

Additionally, the platform utilizes generative AI, specifically GPT-3, to automate the creation of high-quality, branded product descriptions. This process enables the company to generate 10,000 descriptions in 30 minutes, helping scale their catalog management and improve search engine visibility. 

Shein

Shein uses AI to create rapid design by analyzing global fashion trends, with new styles developed in just 25 days. A smart design system streamlines production, while AI-powered personalization enhances customer experiences through tailored product recommendations.

It also uses AI to automate warehouse management and delivery scheduling. This strategic integration of AI has allowed Shein to scale globally, redefine fast fashion, and establish itself as a tech-driven leader in modern e-commerce.

Plivo CX: The future of AI in customer support 

Plivo CX is an all-in-one, cloud-based omnichannel platform designed to help businesses provide top-notch customer support across various channels. It is built to integrate effortlessly into your business and support mechanisms.

The platform also enables businesses to train OpenAI-powered chatbots using unique datasets, ensuring customer queries are answered with the most relevant and accurate information.

Some of its top features include:

• Omnichannel capabilities: Unify, track, and manage customer conversations across channels, including email, voice, SMS, WhatsApp, and live chat
  
  
• Visual workflow builder: Create custom workflows and use automations using a simple no-code drag-and-drop builder

• Integration: Integrate seamlessly with your existing tools, such as homegrown systems, ERP, CRM, and helpdesk tools

• Real-time analytics: Analyze real-time customer interactions to identify areas of improvement  and create targeted training for agents

• More productivity: Streamline agent workflows with message templates and internal notes to facilitate efficient conversation, transfers and task management
  
  
• Agent coaching tools: Train your support agents to monitor real-time performance with features such as call recording, barge, and whisper

• Security and compliance:  Offers enterprise-grade security features complying with SOC-2, GDPR, HIPAA, and PCI DSS. This ensures your customer data is safeguarded and your support processes align with industry regulations

‍Book a demo to learn more.

While voice assistants like Alexa and Siri have become familiar names, the next wave of AI customer service agents is more than that. They're designed to handle nuanced conversations, anticipate customer interactions, and deliver consistent, human-like support 24/7.

This has profoundly impacted customer expectations to the point where 68% of customer support teams believe AI has directly influenced them.

This blog post will help you understand the concept of an AI agent and how it improves customer service. It will also discuss real-life use cases and challenges to help you choose the perfect AI agents to provide unmatched service.

What is an AI agent?

AI agents are software programs designed to replace or augment the work of human agents. They are trained to understand the user's needs, respond to inputs, and act without human intervention.

They rely on ML and NLP to execute diverse tasks, from answering simple questions to resolving complex issues such as sentiment analysis, fraud detection and customer issue prediction.

How does an AI agent work? 

AI agents don’t just follow orders. They set tasks, determine priorities, and reprioritize tasks until the overall goal is achieved. The fundamental design of AI agents revolves around three key components: perception, decision-making and action.

Let’s understand how they work:

Perception: AI agents gather data from various sources, including customer interactions, transaction histories and social media. This helps them understand the context and nuances of customer queries.

Decision-making: The AI agent uses sophisticated machine learning models to identify patterns and make decisions based on the collected data. The agent improves decision-making by learning from past experiences and continuously refining responses.

Action: Once the decision is made, AI agents can execute tasks such as answering a customer query, processing a request, or escalating complex issues to a human agent.

How do AI agents improve customer service?

Parul Mishra, VP of product management in digital labor at IBM, says, 

“While the capabilities of AI agents across specific domains will vary depending on industries and use cases, the key point is that those agents will work in collaboration with AI assistants alongside a suite of other tools to transform a chatbot experience into a multi-dimensional system that can plan, test, write, and autonomously implement solutions.”

Here is how AI agents can improve customer service:

Faster response times

AI agents are available 24/7, ensuring customer inquiries are answered promptly, regardless of time zones or business hours. Being continuously available enables customers to meet their needs via self-service while improving satisfaction.

Personalized customer interaction

With AI entering the scene, 73% of customers feel they are treated as unique individuals in 2024, up from 39% in 2023.

This is because AI analyzes important information such as customer name, location, and past purchases in real time to tailor services to customers so that they feel valued and important.

Managing large-scale inquiries

AI agents can handle thousands of queries simultaneously without delays. They integrate with knowledge bases to provide instant and accurate information and automate routine tasks such as order tracking and password resets.

This ensures they maintain consistent service levels and enhance overall customer satisfaction.

Proactive customer support

AI customer service agents can determine the next best action for your customers by analyzing information from customers' contracts, warranties, and purchase history. For example, AI can set email alerts when it’s time to renew a subscription or when a product upgrade or discount is available.

Improved accuracy and consistency

AI agents can improve the accuracy of responses through agentic loops and human-like reasoning. This ensures consistent and accurate responses to customer queries and reduces the risk of errors.

Delivering consistent results helps build trust and confidence in the brand by meeting customer expectations.

Data-driven insights

Incorporating AI can help you gain deeper insights into every interaction to understand customer satisfaction levels. It enables you to track key metrics such as CSAT, CES, and NPS to optimize processes and proactively address customer needs.

Types of AI agents in customer service

From a support tool to a strategic game-changer, here are the most impactful ways you can use AI agents in customer service:

Chatbots

According to a study by Simplr, in 2022, chatbot usage doubled compared to 2020. This is because chatbots are fast, convenient and available 24/7.

Apart from just answering questions, chatbots can:

• Provide the most relevant information about your products and services
• Book appointments or make reservations
• Offer personalized product recommendation
• Handle refunds, product returns, and exchanges
• Guide customers to solve technical problems

Plivo CX's self-service chatbot, developed and powered by OpenAI, is available 24/7 to resolve queries instantly. With in-app customer service, customers can easily send and receive photos to report issues and queries, making the interaction much more convenient.

Voice assistants (IVR)

AI voice agents or voice bots are popular among businesses looking for additional ways to automate customer service operations. Just like chatbots, interactive voice response (IVR) can answer incoming calls, provide product/ service information, recommend relevant products, update account information and much more.

Sentiment analyzers

Sentiment analysis is a key component of speech and voice analytics that uses NLP and ML to capture customers’ emotions by analyzing vocal and speech characteristics such as pitch, tone, words, volume and other variables. 

Based on that, sentiment analyzers assign a score to each positive, neutral, or negative conversation.

Predictive AI agents

Predictive AI agents can analyze historical customer data, browsing history, and purchase patterns to predict issues and needs such as product failures, churn risks, or future purchase preferences.

Depending on the data, it can offer tailored recommendations and prevent potential problems.

Call transcribers

With real-time transcription and analysis, agents can quickly retrieve customer histories and previous interactions. 

These transcripts are especially useful for reviewing agent performance and ensuring calls adhere to regulatory requirements. Businesses can also identify recurring issues, customer preferences, or opportunities for upselling and cross-selling.

Omnichannel AI agents 

Sophisticated omnichannel platforms offer agents tools and contextual insights to effortlessly carry on a conversation across multiple channels. Although modern chatbots are more effective, they still fall short of managing all inquiries entirely. Omnichannel agents bridge this gap by facilitating seamless handoffs from self-service to live agents when necessary.

Plivo CX’s true omnichannel solution brings frequently-used communication channels, such as voice, SMS, WhatsApp, and live chat, together in a single platform, allowing agents to monitor, track, and manage customer interactions effortlessly.

Uses cases of AI agents in customer service 

Let’s have a look at how businesses worldwide are using AI agents to boost customer satisfaction and agent productivity:

Function of Beauty

This American brand uses AI to build products that are unique to each customer. Upon signing up, customers must complete a survey that understands their hair type, styling preferences, and texture. 

These responses are then analyzed with an AI-powered algorithm to design a unique formula for the customer.

Once the formula is generated, the brand employs AI-powered manufacturing to produce customized items at scale. The final product is sent to the customers, who are asked to give feedback. AI then analyzes this feedback to understand customer satisfaction and improve the customization process.

Lily AI

Lily AI is an AI tool designed to enhance product discovery and conversions in eCommerce, specifically for fashion, home, and beauty retailers. It uses sophisticated technology to match product attributes with consumer preferences.

For example, in fashion, it analyzes attributes like fabric, style, and neckline to recommend similar items, such as white crewneck t-shirts. For homeware, factors like product type, color, and wood tone are considered when displaying relevant products.

eBay

eBay has introduced its AI-powered “Shop the Look” feature, which offers personalized fashion recommendations based on users’ shopping history. The goal is to offer products that align with individual style preferences. 

Shoppers who view at least 10 fashion items in 180 days will see “Shop the Look” on their homepage and fashion landing page. The tool evolves with customers over time to enhance their shopping experience. 

Risks of AI customer service agents

As AI technologies become more common, 61% of customers highlight the need for trust, though fewer than half feel businesses use AI ethically. This gap allows companies to stand out by upholding ethical practices, transparency, and fairness in AI.

To create a secure customer experience, watch out for these potential risks associated with AI customer service agents:

Complexity with existing tools

Implementing AI systems can be complex and expensive, especially for smaller companies with limited resources. The initial investment, maintenance and training costs, and integration with existing tools can pose financial challenges when establishing commercially viable AI operations.

Data privacy concerns

As AI systems rely on large amounts of data, customers’ private information is at risk of being misused and manipulated. To maintain customer trust, companies must comply with legal regulations such as the General Data Protection Regulation (GDPR) and be transparent about processing and protecting customer data.

Lack of emotional intelligence

AI interactions can feel impersonal and lack the emotional connection customers crave, as they often involve robotic messaging. While AI enhances efficiency, it doesn’t offer the empathy many customers seek. 

How to choose the right AI agent for your business

With the wave of AI sweeping in, every business wants to hire an AI agent to make work simpler and more efficient. But every business is different, and so are the capabilities of an AI agent.

If you are new to the AI realm, consider these tips to find a tool that is most compatible with your business needs:  

Assess your needs

Determine the specific functions you want the AI agent to handle. Evaluate the tasks it should automate or support, such as responding to queries, managing orders, or providing recommendations.

Ensure it integrates with existing tools

The AI agent you select should easily integrate with your existing systems, tools, and workflows. To speed up implementation, prioritize tools that provide pre-built APIs or connectors. 

Moreover, a seamless integration process ensures the AI agent adds value without causing delays or technical difficulties.

Consider scalability

Select an AI agent that can scale its processing power, storage, and analytical capabilities to meet future demands. Evaluate its ability to handle larger datasets, integrate with evolving systems, and maintain performance under heavier workloads. 

Scalability is essential for businesses looking to expand, ensuring the AI solution remains effective and reliable as the company grows.

Ensure compliance and security

Finally, ensure the AI agent safeguards the data by using data encryption, controlling access, and adhering to industry standards. Learning and utility-based agents, which process large amounts of data, require stronger security to prevent unauthorized access. 

Opt for AI solutions that offer regular security updates, comply with regulations, and minimize risks like data breaches or cyber-attacks. 

Make interactions more personal with Plivo CX’s AI agents

Going forward, there is a need for seamless integration between artificial and human intelligence. This collaboration will give humans the wings to be creative and build meaningful bonds, while AI agents will ensure fast, proactive and accurate services.

Plivo CX is a complete cloud-based platform that can support this partnership and make customer service more empathetic. It is built to integrate effortlessly into your business and support mechanisms.

You can also train OpenAI-powered chatbots using your company’s unique datasets, ensuring customer queries are answered with the most relevant and accurate information.

Some of its top features include:

• AI-powered chatbots: Interact seamlessly with customers by providing accurate responses at speed
• Simplified escalations with notes: Summarize conversations and pass them to human agents whenever needed
• Unified agent desktop: Visualize complete customer context and insights on a single, easy-to-use application
• CRM integration: Access customer details from your existing CRM and tech stack for a more personalized experience
• Detailed customer insights: Examine live or recorded interactions to uncover opportunities for growth and improvement
• Automated ticket management: Automatically organize and prioritize incoming tickets, ensuring critical issues are addressed promptly
• Interactive voice response (IVR): Set up automated menus to efficiently direct callers to the appropriate team or agent
• Integration: Integrate seamlessly with your existing tools, such as ERP, CRM, and helpdesk tools

• Enterprise-grade security:  Protect customer data with enterprise-grade security features complying with SOC-2, GDPR, HIPAA, and PCI DSS

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Managing customer support is hard. Agents spend valuable time switching between tools, handling repetitive inquiries, and struggling to keep up with the sheer volume of tickets—all while customers expect lightning-fast resolutions.

Delayed responses lead to frustrated customers, lower satisfaction scores (CSAT), and even churn. Meanwhile, your team faces burnout as they try to balance speed with quality in a system that isn’t built for scale.

AI is changing the game. In HubSpot’s recent customer service report, 92% of companies said AI has dramatically improved response times, while 82% credited it with boosting CSAT. By automating repetitive tasks, providing instant responses, and scaling effortlessly, AI equips your support team to meet today’s demands. Here’s how it works.

The Challenges with 100% Human Customer Support 

As your business grows, customer inquiries increase, and keeping up becomes a challenge. Here’s where many customer support teams hit roadblocks:

Constant Hiring
To handle rising demand, you hire more agents. However, research shows that 43% of customer service leaders identify hiring and training as their biggest challenges.This often leads to rushed decisions, high turnover, and operational disruptions.

Training Under Pressure
Every new hire needs time to understand your products, tools, and communication standards. But with tickets piling up, training is often rushed, leading to mistakes and decreased customer satisfaction.

Burnout Takes Hold
High turnover means frequent backfilling, rehiring, and retraining - adding to operational costs. The pressure on existing agents intensifies, resulting in burnout and inconsistent service delivery. Breaking this cycle is critical for delivering reliable, scalable support.

The Heavy Human Toll

This isn’t just about tools and processes—this is real life. Your agents are exhausted, your customers are irate, and you’re stuck in a loop that wears on everyone involved.

• Overworked Agents, Frustrated Customers:
  When your team juggles too many roles and tools, the result is inconsistent service. Customers wait too long and end up frustrated. Over time, lost trust hurts retention and your brand’s reputation.
  
  
• Too Many Tools:
  CRM systems, ticketing tools, chat apps, and more—each one meant to help ends up fragmenting your agents’ workflow. They lose time hopping between platforms, adding stress and slowing things down even more.
  
  
• Scaling Struggles:
  During rush periods, the cracks widen further. Bringing in temporary staff is costly and training them on the fly barely works. Instead of steady support, you’re left in constant damage-control mode, stuck with a team that’s stretched too thin.
  
  
• The Leadership Burden:
  As a manager or team lead, you’re carrying the weight of every decision. The constant juggling act and the emotional toll of trying to keep everyone afloat often go unspoken—but they’re deeply felt.

A Moment to Reflect

77% of CRM leaders believe that AI will handle most ticket resolutions in 2025. This isn’t just a prediction. This data reflects the increasing need for faster, more efficient customer support driven by AI.

To achieve this, you have to pick a tool that supports your support partners and makes their job easier. 

Meet Plivo AI: Your New Support Partner

Plivo AI is an intelligent agent designed to ease the load for your support team. It isn’t here to replace your team. It’s here to empower them. 

💡An AI Agent is a pre-programmed workflow that follows specific steps to complete tasks, like a customer service representative with a detailed manual. It can respond to customers, ask them for details, and take actions on behalf of the company - like updating addresses or processing refund. It combines AI language abilities with access to necessary tools and information, but always works within defined boundaries and processes. 

Here’s how it can change the game:

• Always On, Always Ready:
  Plivo AI works around the clock, making sure your customers get quick, reliable help anytime—whether it’s late at night or during a holiday rush. This consistent support builds trust and gives both your customers and team peace of mind.
  
  
• Effortless Scalability:
  When ticket numbers suddenly spike, Plivo AI scales up instantly—no need to rush through hiring and training. This keeps your service smooth, even during the busiest times.
  
  
• Personalized Problem Solving:
  63% of customers expect customer service agents to know their unique needs and expectations. With a knack for analyzing and learning from past interactions, Plivo AI offers tailored responses for each customer.
  
  
• Smart Automation and Guided Workflows:
  Plivo AI agent simplifies complex tasks by guiding your customers through step-by-step workflows. It’s like having your best agent handling every ticket, reducing mistakes and lightening the load on your team.
  
  
• Less Burnout, More Balance:
  By taking over the repetitive tasks, Plivo AI gives your human agents a chance to focus on high-value interactions. This cuts down on stress and helps create a more balanced work environment.
  
  
• Future-Proof Your Support:
  As your business grows, Plivo AI grows with you. It adapts to rising customer expectations and scaling demands, keeping your support team agile and ready for any challenge. It’s not just a tool—it’s a long-term partner in success.

Agent-Based Model vs. AI-Based Resolution: A Clear Comparison

Implementing AI in customer support offers distinct advantages over traditional human-agent models. Here’s a detailed comparison highlighting key aspects:

Cost Efficiency

Scalability

Efficiency and Consistency

Flexibility and Adaptability

Measuring the ROI of AI-first Customer Support 

One of the most compelling reasons to switch to an AI-based support model is the return on investment (ROI). Here’s how Plivo AI makes a strong case:

95% Query Resolution:

Imagine this: about 95% of customer queries get resolved by AI without the need for human intervention. That’s a massive reduction in workload for your team, allowing them to focus on higher-value tasks.

Cost Savings:

When AI handles most inquiries, you save significantly on salaries, overtime, and training expenses. With fewer errors and faster resolutions, the cost per support ticket drops dramatically.

💡With Plivo, the cost per resolution starts as low as $0.35/resolution. 

Higher Customer Retention:

Faster response times and consistent service mean happier customers. Loyal customers stick around longer, boosting your revenue and reducing the churn that can erode your bottom line.

Measurable ROI:

With the predictable expense model of AI and the dramatic drop in support ticket costs, you can easily measure ROI. Consider that a reduction in support costs, combined with increased customer retention, can lead to a significant boost in profit margins over time.

Energy Reinvestment:

Instead of spending resources on constant hiring and training, those saved funds can be reinvested into business growth, innovation, and even further enhancing customer support strategies.

It’s time to add AI customer support

AI-powered software—especially options with free plans or trials—can offer high potential for ROI, making it an attractive solution for service teams. 

The traditional agent-based model, like Zendesk, has served us well but the rising costs, scalability issues, and inconsistencies in service are clear signs that the old ways are no longer enough—especially when your team is already stretched thin.

Plivo AI offers a fresh perspective. It’s like having your top agent available 24/7, ready to handle demand spikes, keep costs predictable, and deliver a seamless, consistent experience for every customer.

From faster responses and in-depth personalization to a bump in satisfaction levels, AI has spurred a number of positive changes in how we provide support services to our customers. But that’s just the beginning.

According to McKinsey’s State of AI report, “If 2023 was the year GenAI was discovered, then 2024 is the year organizations truly began using and deriving value from this new technology.” 

Interestingly, 2025 holds even more potential for AI in customer service, with promises to transform our delivery and elevate customer experiences.

To help you stay ahead of the curve, we’ll share a few AI-powered drives you should keep on your radar.

AI in customer service: Current overview

According to Salesforce, 85% of decision-makers expect customer service to contribute a larger share of their company’s revenue in the coming years. So, it’s unsurprising that AI adoption in service operations and other departments surged to 72% in 2024.

AI has proven its worth through several automation use cases, too. For instance, 92% of organizations say it has helped improve their customer service operations. Merchants have also reported a 52% increase in ticket resolution speed.

Brands like Klarna, a buy-now-pay-later fintech company, used AI to resolve two-thirds of its customer service chats. If this had been done manually, it would have required a ridiculous amount of human resources and resulted in a high rate of inefficiency due to repetitive tasks.

As AI adoption is already in full steam across multiple business functions, starting now can make the biggest difference in the race to dominate your market space.

AI in customer service: 4 key trends you must look out for

To get started, we have compiled some major trends below to help you implement them without a hitch:

1. AI-powered chatbots are shaping customer service

A Deloitte survey shows that 76% of service agents in contact centers are overwhelmed by systems and information. However, the bulk of this problem is due to the increase in contact volume. 

For example, your complaint backlog scales synonymously with your business growth, overloading human agents with tons of data to analyze when providing services.

However, AI-powered chatbots are changing the scenario. These NLP and ML-trained bots can efficiently handle bulk customer data and leverage them to address customer queries and provide personalized resolutions.

In return, businesses see results such as:

• 37% faster first response time
• 46% agent occupancy rate and a 35% reduction in the likelihood of agents getting overwhelmed
• 27% decrease in ticket-to-order ratio and 1% increase in customer satisfaction score
• $11 billion in annual cost savings for ecommerce brands and other industries in 2023. Chatbots also saved 2.5 billion hours in customer service hours

Personalization

Beyond boosting ROI and saving time, chatbots will also change personalization. As a case in point, 73% of customers already anticipate improved personalized experience as technology advances. This experience includes customer service interactions—an area where 76% of service agents feel overwhelmed due to data load, thus making personalization a daunting task.

Chatbots, on the other hand, can accurately process large amounts of data in a shorter time, analyze even the smallest bits, and combine insights with predictive analysis to provide a hyper-personalized experience. This enhances customer satisfaction levels.

According to Statista, eight in ten satisfied customers are more likely to become loyal advocates.

Returns and refunds

Thanks to digitalization, customers rarely need to queue up in front of your office to return a product. Just a click on the ecommerce store app’s refund button will do. However, some businesses still struggle to streamline this process and pacify their turned-off customers.

When that happens, customers escalate the issue to social media, which can quickly sour your brand reputation. AI chatbots will help avoid such issues in 2025 by simplifying returns and refunds in seconds.

As a comprehensive, AI-driven customer service platform, Plivo CX offers an OpenAI-powered chatbot trained to handle returns and product exchanges, escalate complex issues to human agents, and enhance service delivery.

Implementation: Adopt chatbots to reduce the time to first response and time to resolution, eliminate customer complaint backlogs, free up agents for more complex tasks, and provide the much anticipated hyper-personalized experience to customers in 2025.

2. Omnichannel AI will take a leading role

Invoca’s 2022 survey shows customers prefer to communicate mostly via phone calls, followed by email, in-person communications, live agent chat, and chatbots. In 2024, chatbots and direct messaging via social media have also picked up more pace than before.

That means utilizing multiple channels to meet individual customers where they are comfortable. This leads to a chaotic multichannel communication process, as you have to switch between email tabs, social media, calls, and so on.

As a result, customers feel like they’re talking to different units within the same organization. This poor communication is a major reason 46% of businesses say they’ve lost a customer before.

Omnichannel, AI-powered customer service bridges this gap and unifies customer preferences on a single screen. Your agents can seamlessly move between voice, chat, text/SMS, and WhatsApp or use multiple channels simultaneously to address customers’ complaints.

While omnichannel communication is not a new approach, it will see greater adoption in 2025 as businesses seek to centralize issues and customer communication for increased efficiency.

According to a Gartner report from 2024, over 30% of Fortune 500 companies will offer service through only a single AI-enabled channel by 2028.

Most importantly, advanced AI solutions will provide far more benefits than channel unification, such as live AI suggestions when your agents resolve customer queries. 

Plus, AI’s ability to leverage customer data can also help predict customer preferences, including their top communication channel, language, cultural nuances, and sentiment score when the query was logged.

Eliminating silos

Siloed communication data can worsen a customer’s image of your brand. Because no customer wants to narrate their issue in case of a query again after they’ve initially done so with the first service representative.

Also, not all queries end at L1 or L2; some are escalated to agents for resolution. However, each stage of interaction contains useful information the next correspondent will find useful.

With the appropriate AI-powered omnichannel platform, your agents can simply scroll up to access previous communication summaries or review full notes and utilize them to provide a unified experience for the customer.

An example of such a platform is Plivo CX’s unified agent desktop, which helps you break the barriers between your communication channels, centralize customer interactions on a single window pane, and eliminate communication silos.

Implementation: Adopt an AI-driven omnichannel communication tool to prevent disconnect in your customer-brand interactions.

3. AI and humans will collaborate seamlessly

The surge of AI in customer service has stoked job insecurity and unemployment fears in recent years. At the recently concluded World Economic Forum (WEF), AI was predicted to eliminate 14 million jobs in the next five years.

Gartner’s report also shows that AI will become the primary customer channel over phone calls for a quarter of organizations by 2027.

While there’s no doubt AI will handle some roles in customer operations better, it’s far-fetched to think these models are here to replace humans. On the contrary, AI will become service agents’ ideal assistants in 2025.

For instance, AI-powered self-service is expected to reduce ticket load via automated allocation, prioritization, and workload reduction. This will enhance agents' ability to focus on more complex tasks. Omnichannel AI tools will also provide helpful, live suggestions to agents based on customer data and improve overall delivery. 

AI makes sticky rerouting possible, ensuring the same callers stay routed to the same agent for a consistent experience. Plivo CX’s drag-and-drop workflow builder tool helps create escalation and communication pathways that both your agents and chatbots can use.

Besides, AI is still in its developmental phase and cannot totally replicate empathy. So, 2025 will see a seamless collaboration between humans and AI to provide both accuracy, which humans can’t offer all the time, and emotions, which AI lacks.

Gartner also predicts AI will reduce the number of customer service agents by 20-30% in 2026, but this does not mean humans will cease to exist. Instead, these changes will create new roles for agents instead of handling the same repetitive tasks as before.

Another report shows that AI will take the guardian seat and provide service reps with detailed contexts, insights, and suggestions instead of replacing agents.

Implementation: Embrace AI and equip your customer service team with result-oriented platforms like Plivo CX. Don’t leave AI to do the heavy lifting; instead, build a collaborative flow between your AI and human agents. 

4. Use of AI for quality management

Traditional quality management has long been a go-to for most customer service teams. However, it is inconvenient, time-consuming, requires extensive resource use, and provides slow feedback to agents on the frontline of your business operations.

Besides, traditional QM only allows analysis of a fraction of customer interactions—just the most concerning ones. This makes it impossible to paint a full picture of your service delivery and can result in subpar operations over time.

Given how customer service plays a major differentiating role between businesses, it’s no longer ideal to rely on traditional approaches for QM. In 2025, this trend will take a different turn.

As AI’s adoption for global customer service operations grows, companies are also expected to embrace it for quality management. Primarily, AI can handle vast amounts of customer data and provide a bird’s-eye view of the state of your customer service.

For instance, Plivo CX’s AI-powered Metrics can analyze customers’ past interactions, agents’ activities, and other data to provide useful insights for improving delivery.

AI in QM will also facilitate sentiment analysis, allowing you to determine whether your customers are happy and what’s driving their sentiment so you can promptly address it.

With predictive analysis, businesses will find it easy to identify trends and patterns and make healthy decisions that enhance customer satisfaction.

Enter the future of AI customer service with Plivo CX

The future of AI in customer service means taking proactive steps like integrating chatbots, embracing omnichannel AI, encouraging AI-human collaboration, and using AI for QM, which will help you gain a competitive edge in 2025.

To help you achieve that, Plivo CX equips your team with a scalable AI-driven omnichannel communication platform that boasts an OpenAI-powered self-service chatbot. Our award-winning platform also features the following:

• Effortless workflow design: Visually build custom workflows and automation with a drag-and-drop interface, no coding required.
• Seamless integrations: Connect Plivo CX with your existing tools, including CRM, ERP, helpdesk, and more.
• Data-driven optimization: Track real-time analytics and generate custom reports to gain insights into customer interactions and agent performance.
• AI-enhanced efficiency: Prioritize urgent tickets, ensure brand consistency, and adapt quickly to changes with AI-powered support.
• Rich communication: Enhance interactions with multimedia support, including images, videos, and documents.
• Increased productivity: Streamline workflows with message templates, internal notes, and skills-based routing.
• Comprehensive features: Leverage call recording, fully-customizable IVR, multi-language support, and robust security features for a complete solution.

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According to Microsoft’s State Of Customer Service Report, 90% of consumers consider good customer service when choosing a brand, and 58% say they will switch to competitors if their former brand fails to meet up.

Without a doubt, customer service has become a brand differentiator.

Moreover, 55% of respondents in the same report also expect a year-on-year (YoY) increase in better service delivery. This implies customer support can no longer play a backseat role, especially in 2025, and you need to double down on your investments.

However, providing prompt and purposeful customer service has its ups and downs. In this article, we’ll discuss these challenges and offer proven solutions to tackle them.

Top 10 customer service challenges you must tackle

A typical customer service workflow consists of several touchpoints, ranging from customer inquiry and ticket creation to ticket closure and follow-up. 

Along these, several challenges often pop up. Take, for example, slow response times and dissatisfied customers, which can disrupt your delivery. In fact, as we noted above, this invariably risks losing out loyal customers to your competitors. 

So, what exactly do the challenges imply, and how do you handle them? Let’s take a look:

1. Slow response times

Hubspot’s survey report shows that 90% of consumers consider immediate response very important, and 60% define “immediate” as 10 minutes or less. The longer it takes to respond, the more likely your customers are to seek other alternatives.

Solution

• Implement chatbots for instant responses: Use smart chatbots to quickly handle L1 requests and escalate only complex issues to your agents.
  ‍
  As an omnichannel customer service platform with several AI-powered features, Plivo CX offers an OpenAI-powered self-service chatbot capable of reducing your response time to a negligible fraction and boosting customer experience.

• Monitor response times with real-time analytics. Assess metrics like time to first response and overall time to resolution. Review each touch point in your workflow to determine which part is taking longer to complete and optimize accordingly.

2. Lack of personalization

The latest Salesforce research report highlights an increase in the number of customers who feel treated like unique individuals from 39% in 2023 to 73% in 2024.

 While that’s good news, approximately 27% still feel like they are being treated as numbers. Such customers feel frustrated and are not likely to become loyal to your brand.

Solution

• Integrate data for personalized delivery: Collate customer data into CRM software and integrate with communication tools to eliminate data silo. 
  ‍
  Plivo CX simplifies this process by providing a unified agent desktop that presents a granular view of customer issues and previous communications. This allows customer service agents to tap into necessary information for personalized support right from a single dashboard without needing to switch channels.

• Train customer service agents: They should pay attention to cultural and language barriers when communicating. Also, equip your team with essential soft communication skills to make your customers feel valued at every point of interaction.

3. Handling multiple customers

As your business scales, the number of customer queries you handle daily also increases. However, this can expose your customer service workflow to errors, such as losing track of unresolved queries, unsatisfactory resolution, inappropriate rerouting, ticket collision, and prolonged time to resolution.

Solution

• Implement ticketing system: Use a ticketing system to consolidate all customer queries on one platform. This enables you to track each ticket efficiently, prioritize, and minimize ticket collision.
• Use AI-powered chatbot and routing software: Integrate chatbots to handle basic and common requests in order to free up your agents for other core tasks.
  For example, Plivo CX’s OpenAI-powered chatbot, trained on company datasets, helps resolve simple queries quickly. Also, it automatically escalates complex and nuanced issues to human agents, along with detailed notes and summaries.
• Expand support team: AI bots are powerful, but you shouldn’t leave them to do the heavy lifting. If necessary, acquire a few more agents with the needed expertise to boost response time and reduce the workload on other team members.

4. Answering challenging questions

Let’s face it: There are times you’ll receive some queries that are unscripted and out of the playbook. In such situations, you can’t possibly turn your customers away or tell them you have no answer.

Solution

• Offer a callback: If it’s a phone call, ask customers to give you a minute while you gather more information on their queries. This doesn’t reduce your professionalism but instead assures customers that you’re deeply concerned about them. 
  ‍
  With Plivo CX, optimize call routing by leveraging customer data to connect callers with the right agents, and improve customer experience with a convenient callback option.

• Escalate to senior agents: Different customer complaints require different levels of expertise. Ensure your agents have the tools and orientation necessary to escalate queries without delay. 
  ‍
  You can also use Plivo CX’s call whisper feature to coach your agents live on the phone without the customer's knowledge.

‍

5. Handling dissatisfied customers

Sometimes, getting complaints from annoyed customers is unavoidable, even if you provide the best services. What matters is how you respond. Not handling situations like this appropriately can damage your business reputation, especially since most customers will escalate the issue to social media for visibility.

Solution

• Apply H.E.A.R.D: The HEARD (Hear, Empathize, Apologize, Resolve, and Diagnose) approach focuses on empathizing with your customers and acknowledging the error. This helps diffuse the situation and preserve customer relationships. Once you’ve resolved the issue, immediately figure out why it happened and proactively prevent its recurrence.
• Provide updates on resolution: Keep your customers informed about the resolution process, progress, and possible challenges. This will get them involved and let them know you’re not slacking off.
• Offer a freebie after resolution: Appeal to their emotions with a discount, free subscription, or a limited-time offer. This ensures the resolution ends on a good note and boosts your chances of retention regardless of what has happened before.
• Escalate when appropriate: If all the options above are ineffective, bring in a senior person by hierarchy. In such cases, customers are more likely to listen if they communicate with someone whose words hold more authority than a frontline customer support agent.

6. Managing service outages

A number of factors, like hardware failures, software bugs, network issues, cyberattacks, or human error, cause service outages, which can upset your customer service workflow.

While not a common situation, a single occurrence can result in tons of angry and frustrated customers overwhelming your support, whether on social media or on calls.

Solution

• Proactive communication: When the light’s off, your customers need to know what’s going on even before they reach out. Let them know what has happened, why it’s happening, and what you’re doing to resolve it while assuring them accordingly. You must also communicate time-to-resolution and empathize genuinely with them to avoid unpalatable outcomes.

Plivo CX’s proactive service excels in situations like these to reduce your inbound requests and manage crises before they escalate.

• Develop a crisis management plan: A crisis management plan outlines the steps your agents should take to resolve each outage systematically. It includes a playbook of responses to use when reaching out to customers, escalation pathways where necessary, and internal communications.
• Compensate losses: Restoring services after an outage does not resolve your customers’ dissatisfaction and anger, especially since they may have suffered a few or large losses. So, develop a compensation plan and communicate it to them after the crisis.

7. Dealing with customer requests that are outside of your offerings

It’s not uncommon to see customers request a feature you don’t offer yet or something totally out of your industry. If the entries are high and align with your vision, that’s a good sign, and you can possibly use it as feedback when upgrading your product library.

But if the requests are not entertainable, whether now or in the near future, it can put your support team in a tight spot.

Solution

• Clearly communicate service boundaries and limitations: Train your agents on your full catalog of offers, including detailed information on future inclusions. They should be able to explain the services you provide comprehensively and help customers understand what you can’t.
• Suggest alternative solutions or third-party services: If a complementary brand provides the requested service, you can refer your customers to them to build a brand-brand relationship. However, you can’t do the same if the other providers are your direct or indirect competitors.
• Sell other offers: While you can’t address exact requests, let customers know about other alternative services you provide and how you can still assist them.
• Deliberate inclusion: Going forward, communicate these requests with the product and development team for inclusion where possible.

8. Providing omnichannel customer support

Customers have different communication preferences, which can lead to a disjointed support delivery if you cannot unify these channels. For instance, Mulesoft’s survey report finds that only 26% of organizations provide a connected experience across all channels, surprisingly leaving a whopping 74% out.

To put it simply, disconnected delivery makes your customers feel like they’re talking to multiple businesses instead of just one when interacting with your support team.

Solution

• Implement omnichannel support tool: Omnichannel support tools centralize your channels and eliminate the need to switch tabs. An example is Plivo CX’s unified desktop agent, which lets your customers conveniently reach out to the contact center via channels such as email, voice, chat, text/SMS and WhatsApp. 

9. Service ticket overload

Ticket overload occurs when the volume of customer queries exceeds the support team's capacity to handle them efficiently, leading to delays and decreased service quality.

Sometimes, it is caused by a growing backlog of queries that have stayed beyond the agreed SLA.

Solution

• Embrace automation: Automation tools like AI-driven chatbots can accurately handle most repetitive customer queries and significantly ease your ticket load. Use ticketing and routing automation programs to stepwise manage each query until it is resolved.
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  To achieve this without resorting to multiple tools, try out Plivo CX’s full-packaged service, which offers all these features and more.

• Build automation workflows: Workflows are predefined instructions your automation should follow from entry to resolution of every query to improve customer service efficiency. 
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  In this case, Plivo CX’s drag-and-drop workflow automation builder allows you to design a custom automation workflow that aligns with your objectives.

10. Choosing the right tools and software

Owing to the shift from brick-and-mortar to digital interactions, there is an increasing need to integrate technology for customer support. However, choosing the right tools from so many different options with varying feature sets can be daunting. In a worst-case scenario, you might end up with a bunch of siloed, inefficient software programs.

Solution

• Assess needs: A customer service team needs an omnichannel support tool, a CRM, a ticketing and routing system, a knowledge base, an analytics tool, and automation software. Review whether your current systems or software of choice are scalable as your needs grow; if not, replace them with modern alternatives.
• Keep the tech stack simple: More is not always better, and too many tools lead to inefficiency, as you need to switch tabs often. To avoid that, use a comprehensive platform like Plivo CX and integrate with CRM like Hubspot to unify data and conversations.

Increase customer satisfaction with Plivo CX

By addressing these common challenges head-on and continuously optimizing your support processes, you can create a customer service experience that not only meets but exceeds expectations, ultimately driving business growth and success.

To help you achieve this, Plivo CX equips customer support teams with a robust omnichannel platform that boasts features and functions such as an OpenAI-powered self-service chatbot, visual workflow builder, inbuilt routing, agent coaching, and a single window pane to unify all communication. 

To learn more, book a demo now!