AI Agents

There’s a growing pressure to turn every process into an AI agent. Probably because the technology is new and hot—but that is not the right approach for everything. Using AI should be strategic. It should not be treated as a silver bullet that can be thrown at every organizational problem. We already have different solutions for different problems: Humans — for high-stakes decisions Rule-based systems — when the logic is known and explicit Machine learning — for predictions GenAI — for unstructured inputs that need interpretation Each comes with its own trade-offs in accuracy, cost, complexity, and risk. ...

In my day-to-day work I see firsthand what companies are planning as part of their AI transformation. Some projects are genuinely exciting and could reasonably be called moonshots. Others, in my view, rest on a basic misconception about what an AI agent actually is. What I keep finding is that many companies are not really looking for an AI agent. They are looking for a business rules engine. When you ask them to describe the specific use case, they describe a deterministic process: a fixed set of steps and rules that must be followed the same way every time. Think of an invoice under a certain amount that needs three matching approvals and an approved vendor before it can be paid. That is classic rules-engine territory—predictable, auditable, and repeatable. ...