Top 12 Conversational AI Use Cases (and Real-World Examples)

What is conversational AI?

Conversational AI is technology that lets people interact using natural spoken or written language. It combines natural language understanding, machine learning, and, increasingly, large language models to understand what a customer wants, hold a multi-turn conversation, and take action, such as updating an account or booking a reservation, across voice and digital channels.

Unlike rule-based chatbots that follow fixed scripts, conversational AI understands intent even when customers phrase things differently, keeps track of context across a conversation, and connects to back-end systems to get work done. Most enterprise deployments take the form of an intelligent virtual assistant (IVA) or AI agent working alongside human agents. For a full introduction, see the complete guide to conversational AI.

Conversational AI use cases for customer service and self-service

Customer service is a mature area for conversational AI, because it combines high volume, repeatable requests, and a clear cost per interaction.

1. Automated self-service for routine requests

A common conversational AI use case is resolving everyday requests without an agent: checking balances, paying bills, updating account details, tracking orders, and resetting passwords. When the AI is connected to back-end systems, it doesn’t just explain how to do these things. It does them.

Example: A financial services company uses Verint Conversational AI Agents to handle card payments, payment method changes, late fees, card replacements, and account updates across more than 30 conversation flows. It automates 22 million interactions a year, contains 80% of customer interactions in its digital channels, and saves $18 million annually. Read the case study.

2. Conversational IVR

Touch-tone phone menus frustrate customers and send too many calls to agents. Conversational AI replaces “press 1 for billing” with natural speech, so callers can say what they need and get it resolved in the IVR or routed correctly. Verint Voice AI Agents add these capabilities to existing IVR flows without replacing telephony infrastructure.

Example: A telecommunications brand used Verint Voice AI Agents to contain more than 50% of calls, or 3.5 million interactions a year, saving $10.5 million.

3. Digital and messaging support

Many customers would rather type than call. Conversational AI handles support across web chat, mobile apps, and messaging platforms, so customers can resolve issues on the channel they prefer, at any time. It’s a core part of any digital self-service strategy.

Example: After deploying intelligent virtual assistants on its digital channels, a digital identity and security firm raised digital containment from 60% to 75%, reduced escalations to live agents by 29%, and cut service ticket volume by 20%. Read the press release.

4. Intelligent routing and context-rich handoffs

Not every request should be automated. When a customer needs a person, conversational AI identifies the intent, routes the customer to the right agent, and passes along everything already collected, so customers don’t have to repeat themselves. Verint’s State of Customer Experience 2026 found that 61% of customers prefer speaking to a human agent, driven by frustration with AI that doesn’t resolve issues end to end. A good handoff is part of a good AI experience.

Example: Verint Copilots gather context during self-service and deliver it to the agent at transfer, reducing average call time by at least 30 seconds.

5. Proactive notifications and callbacks

Conversational AI doesn’t have to wait for customers to reach out. It can send proactive updates, such as travel disruptions, payment reminders, delivery changes, or outage alerts, and let customers respond in the same conversation. During volume spikes, it can offer a callback instead of a long hold, reducing abandonment.

Example: When a train or flight is delayed, the assistant notifies affected customers and lets them rebook in the same conversation, instead of joining a long phone queue.

6. 24/7 and multilingual support

Conversational AI keeps service available after hours and in multiple languages, without staffing every shift and language with live agents.

Example: A pharmaceutical company uses Verint Conversational AI Agents to answer 20,000 diabetes-related questions every month across web, mobile, and smart speakers, including in Spanish. The assistant helps patients track blood sugar, plan meals, and register for support programs, achieving a 44% registration assistance rate. Read the case study.

Conversational AI use cases for sales and revenue

Conversational AI isn’t only about reducing cost. Well-designed assistants guide customers to purchase and create opportunities to sell more.

7. Guided booking and conversational commerce

Conversational AI can walk customers through complex purchases, such as travel bookings, reservations, and product configuration, answering questions along the way and completing the transaction in the conversation.

Example: Amtrak’s virtual assistant, Ask Julie, helps travelers book rail trips, prefills booking forms, and assists with hotel and rental-car reservations. Julie answers more than 5 million questions a year, has increased containment by 32%, and generates 30% more revenue per booking, delivering an 8x return on investment. Read the Amtrak case study.

8. Personalized recommendations and retention offers

By combining what the customer says with their history and preferences, conversational AI can recommend relevant products, qualify leads for sales teams, and present retention offers when a customer signals they might leave.

Example: A retailer’s assistant recognizes a customer asking about a return, offers an exchange or a size recommendation first, and routes high-value customers to a specialist.

9. Claims, policy, and account servicing

In regulated industries, many high-volume requests follow well-defined steps: checking claim status, explaining policy coverage, updating beneficiaries, or processing payments. Conversational AI handles these securely, 24/7.

Example: A leading life insurance company uses Verint Conversational AI Agents for account management, claim status, policy information, and payments. It achieved a 97.9% IVA containment rate and reduced contact center call volume by 19%. Read the case study.

Conversational AI use cases for agents and employees

Some of the highest-ROI conversational AI use cases never actually talk to a customer directly. Instead, they simply help agents and employees work faster and more accurately.

10. Real-time agent assistance

AI copilots listen to live conversations, understand what the customer needs, and surface answers, next steps, and compliance prompts for the agent. New agents ramp faster, and experienced agents spend less time searching knowledge bases.

Example: The same financial services company that automates 22 million customer interactions also uses Verint Conversational AI Agents to help associates find knowledge during phone calls, across seven departments.

11. Automated call summaries and wrap-up

After every call, agents typically write notes, choose disposition codes, and update the CRM. Conversational AI can do this automatically, freeing agents for the next customer and producing more consistent records. Verint Copilots are built for this job.

Example: UK energy supplier Utilita cut 35 seconds from every call by automating call summary creation with the Wrap Up. Hear Utilita’s success story.

12. Employee self-service for IT and HR

The same technology that serves customers can serve employees. Internal assistants answer benefits and policy questions, reset passwords, check ticket status, and guide new hires through onboarding, reducing the load on IT and HR service desks.

Example: An internal assistant answers questions like “How many vacation days do I have left?” or “How do I reset my VPN password?” from verified HR and IT content, and opens a ticket when it can’t resolve the request.

Conversational AI examples by industry

Every industry has its own high-value conversations. Verint offers industry-specific AI agents pre-trained for many of them. Here’s a summary of real-world conversational AI examples impacting an array of industries.

Banking and financial services

Banks and card issuers use conversational AI for balance and transaction inquiries, payments, card replacement, and fraud questions, with secure authentication built into the conversation.

Insurance

Insurers automate claim status updates, policy questions, billing, and first notice of loss, giving policyholders fast answers when they need them most. See how conversational AI is improving health insurance chatbots.

Healthcare and life sciences

Healthcare organizations use conversational AI to schedule appointments, answer medication and program questions, and support patients around the clock, within privacy requirements such as HIPAA.

Travel and hospitality

Travel brands use conversational AI for booking, rebooking during disruptions, loyalty questions, and reservation changes, where speed matters most.

Retail

Retailers automate order tracking, returns, exchanges, product troubleshooting, and order changes, especially during seasonal peaks.

Telecommunications and utilities

Telecom and utility providers use conversational AI for billing questions, plan changes, outage updates, and technical troubleshooting, often in high-volume voice channels.

Public sector

Government agencies use conversational AI to answer citizen questions about services, permits, and benefits, and to reroute non-emergency calls away from 911 lines.

How to choose the right conversational AI applications

The best application of conversational AI for your organization doesn’t have to be the most ambitious one. To drive conversational AI impact fast, prioritize use cases that score well on these criteria:

• High volume: The request makes up a meaningful share of your contacts.
• Repeatable: The steps are well defined and don’t require judgment in most cases.
• Completable end to end: The AI can access the systems it needs to finish the task, not just explain it.
• Low risk with a clear escape route: Customers can reach a person easily, with context, when they need one.
• Measurable: You can baseline the current cost, handle time, and satisfaction for comparison.

Your own interaction data is the best guide. Analyzing conversations to find the most frequent and most automatable intents shows where conversational AI will pay back fastest. For more ideas across the contact center, see top AI use cases in contact centers.

How to measure conversational AI success

Track containment and resolution together. A high containment rate with low resolution means customers are abandoning the AI, not being helped by it.

How does Verint help drive business outcomes with conversational AI?

Verint Conversational and Agentic AI helps organizations deploy AI agents that resolve customer interactions across voice and digital channels. Verint Agent Factory makes it fast to build and launch conversational AI agents, pre-built industry-specific AI agents accelerate time to value, and Verint Da Vinci AI powers bots that assist human agents in real time. Because Verint’s platform is open, it works with your existing telephony and CRM, so you can start with one use case and scale.

Ready to see what conversational AI can do for your customers? Get a demo today.