What ChatGPT was to consumer-ready AI, agentic AI is becoming for enterprises. The rapid rise of AI agents from companies like Microsoft and Google is proving to be a tantalizing use case for enterprise adoption. According to a recent survey, 99% of enterprise developers are either exploring or actively developing AI agents. For businesses, change is coming—and the time to get on board is now.

As with any emerging technology, hype can quickly outpace utility. But agentic AI warrants the attention it's getting because its architecture addresses the limitations of general-purpose tools. To understand why, some context is helpful.

If you were building a factory to produce widgets, you wouldn’t rely on one general-purpose machine that “sort of” makes every part. You’d deploy a set of purpose-built machines—each designed to complete a specific task with precision, efficiency and reliability. You’d still need people overseeing the process, but the machinery would be tuned to the job at hand.

That's the logic behind agentic AI. In complex businesses like product development, advertising or market research, generalized AI often falls short. You want specialized agents built for the job. You want the AI equivalent of a well-oiled production line: a group of intelligent tools, each carrying out a distinct role, contributing to a larger, integrated output.