"Big tech has spent more than a year promising that AI agents can deliver on this promise to an extent that the earliest LLMs couldn't, by automatically completing tasks based on detailed user prompts. And they're not holding back in their predictions for the potential of agentic AI. Microsoft, for one, expects 1.3 billion AI agents to be operational by 2028, having painted a picture of a vast interconnected world of agents that collaborate on tasks."
"This doesn't really mean anything, though. For all IT decision makers know, a billion of those agents could only be capable of carrying out the simplest tasks and may barely move the dial when it comes to productivity. Simply having more agents in your enterprise environment isn't inherently a good thing, in the same way that simply hiring more workers is pointless if they're not very good at their jobs."
AI agents are being positioned as a transformative advance in generative AI and automation, with major firms forecasting massive deployments. Large projected numbers, such as Microsoft's estimate of 1.3 billion agents by 2028, emphasize scale but not capability. Many agents may perform only trivial tasks and deliver little productivity improvement. Quantity without competency can mirror hiring many unskilled workers. Analysts expect a high failure rate, with warnings against solutions that repackage RPA and chatbots. Early implementations often produce confusion, disappointed IT teams, and unclear ROI. Meaningful benefits require capable agents, careful integration, and realistic evaluation of returns.
Read at IT Pro
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