What are the Best Use Cases for AI Voice Agents in Your Contact Center

AI Voice Agents are becoming an integral part of modern contact centers. Whether you believe that shift is happening today, in five years, or further down the road, it’s crucial to identify which use cases are best suited for these agents in your business. Understanding these use cases helps you evaluate whether AI Voice technology can replace 5%, 10%, or even 25%+ of your current human interactions. Additionally, it provides insight into what conditions need to be met in the future to expand AI Agents effectively, ensuring you’re prepared as the technology reaches the necessary level of sophistication.

Framework for Classifying Your Interactions

Here are six key questions to help you categorize and prioritize the interactions AI Phone Agents can handle in your contact center:

1. How many of my interactions have an average talk time under 3 minutes?

While there’s nothing magical about the 3-minute mark, it serves as a useful heuristic. Shorter calls often represent more contained, straightforward tasks—ideal for AI agents. AI tends to perform worse the longer a conversation drags on. This is because longer calls require more instructions, have more potential conversational paths, and demand access to a wider scope of business knowledge. These complexities increase the testing and development time for AI Voice Agents, may introduce latency, and elevate the likelihood of the agent encountering scenarios it can’t handle autonomously.

2. How many of my interactions are already outsourced to a lower-cost locale?

If you’ve already outsourced certain interactions to lower-cost agents, those are more likely to be good candidates for AI Voice Agents. Typically, these calls are simpler, support fast ramp-up times, and don’t demand agents to be deeply immersed in your company culture. By moving these interactions to AI, you can further reduce costs and ensure consistent performance without the need for continuous training or managing high turnover rates.

3. How many of my interactions are prescriptive or guided in nature?

The more an interaction follows a predictable playbook, the better suited it is for AI agents. This doesn’t mean it has to be rigid; even semi-structured conversations, like sales calls that follow a specific process or method, are manageable by AI. Simple inbound calls with just a few questions, or calls where there’s a clear decision tree to follow, are ideal for AI because they reduce uncertainty and require less improvisation.

4. How many of my interactions don’t require licensing or expertise?

AI agents don’t have professional licenses (yet ;-), and they don’t hold advanced degrees (yet ;-). If you operate in a regulated industry (such as Insurance, Wealth Management, Healthcare) where a subset of your calls requires a licensed professional, those calls should remain human-handled for now. However, consider if it’s possible to break up those interactions, and have the pieces that can be managed by non-licensed personnel or assistants be done by AI instead.

5. How many of my interactions don’t require agents to take action in closed systems?

While AI can gather information, make API calls, and pass data to various systems, it can’t handle interactions requiring manual input in systems without open APIs. For calls where the agent needs to physically submit data into a closed system, robotic process automation (RPA) may be required alongside AI. AI alone won’t be able to handle these interactions.

6. How many of my interactions require an especially human touch for sensitive issues?

Phone AI Agents can demonstrate empathy, but when it comes to highly sensitive or emotionally charged interactions, such as an insurance claims call after a natural disaster, customers may especially need a human touch. Where the value of the interaction is in the very fact that it’s a human shoulder to lean on or ear to vent to, AI Agents aren’t the right fit for these situations, as customers may get upset and conclude you don’t value their experience.

What Use Cases Are Best for AI Voice Agents?

With those factors in mind, some combination of the following use cases are likely to qualify as good candidate for AI Voice Agents:

• Qualification Calls: Especially in regulated industries like healthcare or financial services, many businesses already separate initial lead qualification from selling or dispensing advice in order to save the time of the specialized or licensed agents. AI agents can gather key information and pre-qualify leads, ensuring that only high-intent and qualified prospects reach more expensive human agents.
• Data Verification Calls: In some business processes, companies need to reach out to verify customer information already submitted on a form. AI can quickly verify details like date of birth, insurance or address, compare answers to what was submitted, and update the system as needed.
• After-Hours Lead Capture: In industries like home services and legal services, high-intent customers often call to initiate a booking after hours. AI agents can capture the lead and add it to your CRM, so your sales team can follow up during business hours. This allows you to avoid paying for expensive “after hours” call centers that can’t close the sale but only capture the lead.
• Failed Payment Update Calls: For products or services with recurring payments, AI agents can handle calls related to failed payments, contacting customers to resolve the issue by updating their payment methods.
• Collections Calls: For early-stage collections, AI agents can efficiently handle interactions by reminding customers of overdue balances and walking them through payment options.
• Simple Inbound Customer Support: Where the intent of an inbound customer services call is easily detected, AI agents can resolve straightforward inquiries like password resets, order status checks, or FAQ-related questions without the need for human intervention.
• Appointment Setting Calls: Whether it’s scheduling or rescheduling doctor’s appointments, interviews, or meetings, AI agents can handle these simple interactions seamlessly.

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Conclusion

As generative AI technology continues to evolve, the potential use cases for AI Phone Agents in contact centers will only increase. By using the framework in this post, you can identify where AI agents fit best today in your contact center, and plan for future integrations. Another important consideration is exploring the potential for introducing new contact center interactions (especially outbound, revenue-driving ones) that you currently don’t staff due to lack of capacity or ROI. Leveraging AI Phone Agents for these can allow your business to experiment with new revenue opportunities in a low-risk way.

Ready to Learn More about AI Voice Agents? Read about how they Compare to AI Copilots. Or request a demo today.

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