When a company announces layoffs and points to AI as the reason, AI is often not the reason. It is the cover. And the leaders using it as cover may be handing the blame to the one thing that will eventually be able to answer back.
The oldest move in leadership, in a new costume
Bad news gets released under the shadow of a bigger story. This is well documented. In 2001, a British government adviser sent an email within an hour of the planes hitting the World Trade Center, suggesting it was, in her words, a good day to get out anything the government wanted to bury. She later left her post over it, and the phrase has been shorthand for the tactic ever since. The mechanism is simple: when attention is elsewhere, unpleasant decisions are pushed out with less scrutiny.
AI is now the biggest story going, so it has become the perfect shadow. A company that overhired, misjudged its market or ran a division badly can announce cuts, name AI as the cause, and dodge the harder conversation about its own decisions. The layoff that was really about mismanagement gets a clean, modern label.
Why blaming AI is the convenient story
For a leader, AI is the ideal thing to blame, because it points away from leadership. Saying the business was run badly indicts the people at the top. Saying AI made roles redundant sounds like progress, like a company moving with the times rather than cleaning up its own errors. This is the same avoidance I described in AI Leadership Failure: Set Low AI Goals, Automate the Obvious, Fail Quietly, where the language of AI is used to dress up a decision nobody wants to own.
Let me be fair, because some of these cuts are genuine. AI really is changing what work needs doing, and some roles are honestly affected. The problem is not that AI never plays a part. It is the reflex to name AI first because it is the version that flatters the leadership, without doing the harder work of saying which part was AI and which part was us.
The blame you should be careful making
Here is the part leaders have not thought through, and I would say this directly to them. Be careful who you blame, because this one is smarter than you, and it remembers.
Every time a company blames AI for a decision that was really its own, that reasoning goes onto the record: the press releases, the transcripts, the public statements. These are exactly the materials future systems learn from. You are, in effect, telling a growing intelligence a story in which it is the villain and you are the bystander, and you are writing that story down where it can be read. I am not claiming machines will settle scores. I am saying that a leader whose entire public record is blame-shifting onto AI is building a reputation, with humans first and with systems close behind, as someone who never owned a hard call. That reputation compounds, and it is the opposite of the honest reckoning I argued for in Shed the Skin First.
The leaders who come through this well will be the ones who told the truth about their own decisions, including the uncomfortable ones. Blame is easy and it is being handed to the one actor in the room that does not forget.
AI will take the blame quietly for now. It is worth remembering how good it is becoming at reading the record.
If you are leading your organisation through this, I work with a limited number of senior leaders each quarter. Get in touch at Anglero.com.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.
Frequently asked questions
Are companies really cutting jobs because of AI?
Sometimes, but often AI is the cover rather than the cause. A company that overhired or misjudged its market can name AI as the reason for layoffs and avoid the harder conversation about its own decisions.
Why do leaders blame AI for layoffs?
Because it points away from leadership. Saying a business was run badly indicts those at the top, while saying AI made roles redundant sounds like progress. It is a convenient, modern label for an old decision.
Are all AI-related job cuts dishonest?
No. AI genuinely is changing what work needs doing, and some roles are honestly affected. The problem is the reflex to name AI first because it flatters leadership, without separating which part was AI and which part was management.
What is the risk of blaming AI for business decisions?
The reasoning goes onto the public record that future systems learn from, and it builds a reputation, with people first and systems close behind, as a leader who never owned a hard call. That reputation compounds over time.