CREOVAI blog

Agentic AI: What contact center leaders need to know (and what's coming next)

Geouffrey Erasmus
Jun 25, 2025
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The contact center's levels of AI maturity are evolving—fast. What began with basic automation and then moved into intelligent assistance is now entering a new phase: Agentic AI.

This isn’t just another buzzword. It’s a redefinition of how work gets done between people, systems, and now AI agents that act autonomously. At Creovai, we see Agentic AI as a necessary evolution—not a trend—that’s reshaping the future of contact center operations and the broader enterprise.

From automation to intelligence to agency

The first era of AI in contact centers was about automation—handling repetitive tasks like call routing, FAQs, and scheduling. Then came intelligent assistance, where AI copilots support agents with real-time suggestions, summarization, and knowledge retrieval.

Now, we’re seeing the rise of Agentic AI—systems that not only support decisions, but initiate actions, coordinate with other AI agents, and pursue goals autonomously within defined guardrails. This shift is being accelerated by two converging trends:

  1. Enterprise adoption of multi-agent systems: virtual agents, workflow bots, and task orchestration tools working together.
  1. Consumer adoption of personal AIs: like ChatGPT, Gemini, and Copilot—shaping customer expectations for how AI interacts on their behalf.

Together, they’re forming a bi-directional, AI-mediated layer between companies and customers. We’re quickly moving toward a world where your customer’s AI will speak directly to your company’s AI. That appears to be the newest frontier—and Agentic AI is how we’ll cross it.

Preparing your contact center for Agentic AI

Agentic AI is powerful. To unlock its full potential, your contact center needs to be ready. That being said, this doesn’t mean you have to become an IT administrator or technology expert. It means understanding where your systems, people, and processes may need to evolve to support more intelligent, real-time enabled operational efficiency.

Here are five key areas to focus on:

1. Modernize for speed and flexibility (Cloud-Native & API-First)

Agentic AI needs to work in real time—not wait for overnight system updates. That means your contact center systems need to be modern, cloud-based, and built so that Agentic AI and your core systems can talk to each other instantly.

By wrapping your core systems in APIs (like REST or GraphQL), you enable AI agents to access the tools and data they need in milliseconds. This is what enables fast, intelligent AI during a live customer interaction—instead of waiting for a slow, behind-the-scenes process to catch up.

2. Make knowledge easy to find and use

Agentic AI needs access to accurate, up-to-date information to be effective. If your knowledge lives across multiple systems or is hard to search, it will slow things down. Make sure your knowledge bases are well-organized, maintained, and easy for AI to access—so it can help agents (or customers) faster and more reliably.

3. Know what the AI is doing—and why

As AI agents become more autonomous, it’s important to be able to see and understand how they’re making decisions. You don’t need to track every line of code, but you should expect visibility into what AI agents are doing during conversations—and have the ability to review or step in if needed.

4. Prepare for continuous change

AI tools evolve quickly. To stay ahead, your organization will need processes that support regular updates, testing, and improvements—without slowing down operations. Work closely with your tech teams to make sure any new AI features can be safely rolled out and adjusted over time.  

5. Reskill and empower your workforce

As AI takes on more routine tasks, your agents' roles will shift. Instead of just handling calls, they’ll be coaching AI agents, managing exceptions, and helping design better prompts and workflows. Investing in training and change management now will pay off as agent roles evolve. Think of your team as becoming supervisors of both people and machines.

At Creovai, we’re building with all of this in mind. Agentic AI is not just a feature set—it’s an architecture.

The role of agentic AI in regulated environments

In industries like financial services, healthcare, and insurance, the promise of Agentic AI must be balanced with clear oversight. At Creovai, we believe this balance is possible—and essential.

Here’s how regulated enterprises can harness Agentic AI responsibly:

  • Bounded autonomy: Define what agents can and can’t do—e.g., offer refunds up to a limit, suggest products, but escalate anything beyond those rules.
  • Runtime guardrails: Use policy engines to redact sensitive data, enforce consent, throttle high-risk actions, and trigger human intervention when needed.
  • End-to-end observability: Every action an agent takes should be auditable, traceable, and explainable.
  • Responsible AI governance: Cross-functional teams must stress-test new use cases and align them with evolving regulations like GDPR, HIPAA, and CCPA.

Agentic AI is not about removing humans—it’s about making AI trustworthy enough to act independently, while humans remain in control.

Where Creovai is headed with Agentic AI

Agentic AI is already influencing Creovai’s product roadmap in strategic ways. Here’s a glimpse at what we’re building:

Autonomous QA Coach

We’re in the research phase of designing AI agents that analyze live interactions in real-time and deliver personalized coaching based on agent performance patterns. That means agents get data-backed coaching on areas they can improve during the interaction rather than having to wait for post-call coaching sessions.

Composable Agent Studio

We’re developing a low-code, drag-and-drop canvas to help teams design their own goal-based agents. Refund bots. Upsell bots. Survey agents. All with runtime guardrails, cost tracking, and compliance baked in.

Real-Time Agent Assist

Our next-gen Agent Assist is powered by Agentic Real Time Agent Guidance, surfacing insights and next-best actions during calls—while proactively helping agents steer conversations toward better outcomes.

Hyper-Personalized Offers

By combining customer context with AI autonomy, we’re enabling agents to adjust offers dynamically—always within policy but tailored to what’s most likely to convert at the moment.

These initiatives are more than the intent to drive contact center efficiency. They’re about aligning the intelligence of AI with the intentionality of human customer service design.

Final thoughts: Why now?

Agentic AI is going beyond experimentation. In 2025, we expect to see real pilots and production rollouts begin in earnest. The contact centers that are laying the groundwork now—modernizing their tech stacks, rethinking their governance models, and upskilling their teams—will be best positioned to lead in this new era.

At Creovai, we believe Agentic AI is the natural next step on the AI maturity curve. It’s how organizations evolve from being supported by AI to being truly collaborative with AI. And the sooner we embrace that shift, the more value we can unlock—for agents, customers, and the business.

Want to learn more about how Creovai is building Agentic AI into the future of the contact center? Let’s talk.

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