Agentic AI: What Contact Centre Leaders Need to Know (And What’s Coming Next)

Madeline Jacobson at Creovai explains how contact centres can prepare for the rise of Agentic AI, outlining five practical areas leaders should focus on to unlock its full potential.

The contact centre’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.

Agentic AI is a necessary evolution-not a trend-that’s reshaping the future of contact centre operations and the broader enterprise.

From Automation to Intelligence to Agency

The first era of AI in contact centres 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.
2. 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 Centre For Agentic AI

Agentic AI is powerful. To unlock its full potential, your contact centre 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. Modernise 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 centre 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.

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. 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.

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 centres 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.

This blog post has been re-published by kind permission of Creovai – View the Original Article

For more information about Creovai - visit the Creovai Website

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Creovai
Reviewed by: Rachael Trickey