César Gamio, Founder and Managing Director at Dharma Centre for Workplace Wellbeing
Meta’s CTO has admitted, in an internal memo, that the company’s AI reorganisation was “an atrocious job.” It is a rare thing for a technology leader to say so plainly, and it is worth taking seriously, because the pattern behind it is not unique to Meta.
Since the reorganisation, code output has reportedly jumped by 220% among engineers reassigned to AI training work. On paper, that looks like a win. In practice, morale has fallen to a record low, and Meta is still monitoring employee activity even as it introduces new perks to offset the damage. Those two facts sitting side by side, rising output and falling trust, tell you almost everything you need to know about what went wrong, and it was not the technology.
I spent fifteen years in Fortune 500 technology leadership before moving into workplace wellbeing and leadership consulting, and I have watched this same pattern repeat across multiple waves of technological change. It happened with the shift to enterprise software, again with cloud migration, and now with AI. The technology moves fast because it can. Leadership moves more slowly because it depends on trust, and trust is not something you can deploy on a timeline.
What makes the AI wave different is speed and visibility. Employees do not experience an AI rollout as a neutral technology project. They experience it as a direct question about their own value: will I still have a role, will my judgement still matter, is my output being measured in ways I cannot see. When leaders do not answer that question honestly, employees answer it for themselves, usually in the least generous way possible. Output can rise in that environment. Commitment does not.
Meta’s response, adding perks while keeping the monitoring in place, is a common leadership reflex, and it does not work. Perks address comfort. Surveillance signals distrust. You cannot resolve a psychological safety problem with the first while reinforcing it with the second, and employees notice the contradiction immediately.
For founders and leaders building fast-growing companies, the lesson is not to slow down AI adoption. It is to treat the human side of that adoption as seriously as the technical side, and to do it before the rollout, not after morale has already dropped. That means being transparent about what is changing and why, giving people a real voice in how new tools are introduced into their own work, and being honest that AI raises genuine questions about job security and competence rather than pretending it does not.
There is a global standard for exactly this kind of risk, ISO 45003, which addresses psychological health and safety at work, and its logic applies directly here: psychosocial risk has to be assessed and managed with the same discipline as physical safety, not treated as a soft afterthought to a technology decision.
Meta’s admission is unusually candid, and that candour is useful. It gives every other organisation currently rolling out AI a preview of what happens when the technology outruns the leadership around it, and a chance to choose differently before their own employees force the same admission.
César Gamio spent fifteen years in Fortune 500 technology leadership. He is an author, adjunct professor at IE Business School, founder and managing director of the Dharma Centre for Workplace Wellbeing, and a British Standards Institution Associate Consultant for ISO 45003, the global standard for psychological health and safety at work.
