71% of contact centers use AI today. Here are the top 10 AI use cases

AI agents for contact centers are the modern evolution of the use cases covered here. AI adoption in the contact center has grown quickly, and this post looks at the top 10 ways teams put it to work, from early automation to today's purpose-built AI agents.

Contact center leaders are confident in AI playing a central role in improving their business operations. According to the Post-Pandemic Contact Center Report, more than two-thirds of contact centers (71%) use artificial intelligence for a variety of applications.

Since that survey, the underlying technology has moved forward. Many of the use cases below used to require stitching together several disconnected point solutions: one tool for transcription, another for quality scoring, another for post-call summaries. Today, AI agents for contact centers consolidate that work into a single purpose-built system that can operate across voice and chat and feed insights back into coaching and operations. The result is less integration overhead and faster time to value for contact centers adopting agentic AI. The use cases below still hold, but it's worth reading them with that evolution in mind.

Benefits of AI in the contact center

That adoption has driven substantial benefits for the majority of AI-enabled contact centers.

More than 90% agree that artificial intelligence has enhanced their ability to collaborate, 85% say it has created more transparency, and 77% say it has helped bring down their overall costs.

Artificial intelligence technology adoption

That begs the question, how are contact centers actually using AI today? The chart below shows the top 10 AI implementations in contact centers today.

Analytics use cases

Digging deeper into the analytics use cases - agent analytics, predictive analytics, and interaction analytics, we can paint a clearer picture as to what analytics are actually being analyzed.

In fact, nearly two-thirds believe that they need to implement new analytics technologies to achieve their contact center analytics goals. While a quarter don’t feel the need for new technology, another 17% are not sure.

Below are the 5 primary areas of focus for measurement via contact center analytics.

Use case #11: Agentic AI contact center deployments

Beyond the ten use cases above, more contact centers are now deploying agentic AI across the full operation rather than as a single point solution. Instead of separate tools for voice automation, chat support, and quality monitoring, an agentic AI contact center runs VoiceAI Agents and ChatAI Agents alongside a Companion Agent that supports human and AI agents in real time, plus AI Agents for Operations that evaluate every interaction and turn it into coaching and insights. Bringing voice, chat, and operations into one platform gives leaders a single, consistent view of quality and performance instead of piecing it together across disconnected systems. It's the direction the top 10 use cases above are heading as contact centers move from isolated AI tools to purpose-built AI agents.

Looking for more on the state of contact centers and AI?

The full report dives into AI implementations and decision making in Section 3, but also includes results and analysis on AX/CX technologies and use cases from leading contact center operators. Read the full report here.

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Frequently Answered Questions

What are AI agents for contact centers?

AI agents for contact centers are purpose-built AI systems that handle voice and chat conversations directly, or support human agents in real time, rather than automating a single narrow task. Unlike older bots and scripted IVRs, they can carry a full conversation, pull from company knowledge and systems of record, and hand off cleanly to a human when needed.

How is agentic AI different from earlier contact center automation?

Earlier contact center automation typically handled one step of a process, like routing a call or transcribing it, using separate tools stitched together. Agentic AI in the contact center combines voice, chat, and operations insight in a single platform, so the same AI agent can act on a conversation and feed what it learns into coaching and quality programs.

What are common agentic AI contact center use cases?

Common use cases include AI agents handling full voice and chat conversations end to end, a companion agent assisting human agents during live interactions, and AI agents for operations that evaluate every interaction to generate coaching and performance insights for both human and AI agents.