AI Agents for Businesses: The CIO’s Guide

It wasn’t one dramatic moment that made me stop and take note of a move toward agentic artificial intelligence (AI). My attention was drawn more and more through increasing questions from clients.

For years, they’d been asking questions like, “Can this model summarize a contract? Can it classify these tickets? Can it draft an email?”

Then, about a year ago, the questions changed. Clients stopped asking whether a model could do a single task and started asking whether it could take action on its own. If you’re a chief information officer (CIO), that shift should change how you think about infrastructure, governance, security, and operating models.

How agentic AI differs from traditional enterprise AI 

Traditional enterprise AI is advisory. It predicts and even recommends. It summarizes and surfaces insights. It can be powerful, but its power is limited by design. That’s because it generally hands the final decision to a human.

Agentic AI is different in one fundamental way. An agent doesn’t just tell you what to do; it can decide to do it.

The system can then chain those decisions through tools and workflows. It can open tickets and query systems of record. It can send approvals and update procurement details. It can trigger supply chain actions and escalate exceptions. It doesn’t pause for permission at every step unless you build it to.