"Moving to Agentic AI" Just published at Enterprise AI World. Read Dan's latest analysis

Moving to Agentic AI

Intelligent agents are not new. In its April 15, 1995, issue, Datamation published my 1–3-year forecast. Agents, I predicted, would automate repetitive tasks, help with email, and coach us on managing time wisely. Sound familiar?

I went on to predict agents would customize user interfaces, manage workflows, and make restaurant reservations. By 2000, agents would “begin to understand context.” Socially aware agents would orchestrate interactions, including interorganizational workflows such as supply chain and payment management.

Of course, this did not happen by 2000, but the emergence of Robotic Process Automation, or RPA, the lowest rung of the agent hierarchy, began. RPA provided a reliable foundation for deterministic processes, those driven by predefined rules and repeatable workflows, enabling well-designed interactions between processes and people.

Twenty-five years later, the term “agent,” or “agentic AI,” remains an overloaded one. It generally describes systems that perceive, reason, and act toward goals autonomously. The recent infatuation with chatbot technology and language models has shifted its attention to agents, promising they will do all the things I forecasted and much more.