Agentic AI — AI systems that can plan, act, and adapt autonomously — is the buzzword of 2025. Demos show AIs booking flights, writing code, and managing workflows like digital employees. The vision is enticing: an always-on, infinitely scalable workforce that thinks ahead. But behind the hype, most agents are still more intern than executive — helpful, eager, but needing oversight.

In our analysis, we’ve found that agentic systems excel at discrete, well-defined tasks but falter in long, complex workflows without human guardrails. They can navigate a booking process but stumble when business rules change midstream. They can draft an email chain but miss subtle strategic context. Much of the “autonomy” today is a sequence of chained prompts with human-like polish — not true decision-making.

That’s not to dismiss the progress. The leap from static chatbots to task-oriented, multi-step AI agents is real. Models are becoming better at memory, context retention, and tool use. But the industry is still figuring out how to blend reliability, adaptability, and safety at scale — without humans constantly intervention. Enterprises exploring the space are often intrigued but cautious; many want to start experimenting, yet remain hesitant to hand over critical processes. They’re looking for controlled, low-risk entry points — proof that agents can be trusted before making bigger bets..

The takeaway? Agentic AI isn’t vaporware, but it’s not ready to run your business unsupervised. Treat them like capable juniors: give clear goals, monitor outcomes, and iterate. The day they graduate from “intern” to “manager” is coming — but for now, the dream needs patience as much as ambition.