Meta thought AI could do the job instead of humans — what happened next should surprise absolutely nobody

Imagine AI is the sun and businesses are Icarus .

By now, most of us are basking in the light of this transformative innovation, which sometimes feels too hot and other times disappears behind clouds so dense we wonder why we ever trusted it in the first place.

Some intrepid businesses not only gaze at AI's warm light, but openly worship it.

They don wings, and fly as close as they can to its surface.

The goal: scoop up a bit of that generative magic, and fly back to Earth with agents, which, to carry this insane metaphor further, can be fashioned into people-like workers capable of doing what we do, but at scale and with little-to-no monitoring.

Of course, the flight to AI's core is dangerous, and so we have episodes like Meta's recent Quixotic adventure which, according to an extensive Reuters report , saw it attempt to transform a vast portion of its workforce (reportedly 60%) into AI agents overseen by a much smaller set of highly skilled workers.

That Meta's wings almost immediately started smoking from its proximity to the AI core premise is no surprise, at least not to me.

Slow down I talk and write about AI a lot and have, in truth, been covering it for almost 25 years, back when companies like IBM and Microsoft were the AI leaders, and we thought Deep Blue beating Kasparov was the apex of what we could expect from Artificial Intelligence.

Modern generative AI burns far brighter and shows in real time such vast potential that enthusiasm is not just rampant; it's out of control.

AI agents, which Meta apparently started using at scale, are driving much of its mania.

These automated tools offer the promise of handling drudgery tasks in innumerable businesses and could solve not just productivity problems, but be the answer to workforce issues: including hiring problems, underperformers, and burnout.

Agentic AI can not just handle repetitive tasks; it can cobble together disparate systems to complete work.

From Meta's perspective, especially as a company that is primarily a software business, AI that could work across tools and systems to not only help keep things running but build new work (under the supervision of a smaller set of super-performers) probably seemed like the perfect solution.

Conclusions like this are not exclusive to Meta or companies of its size.