Wrong.
Within a few months, several of the people I had expected to keep resigned. Suddenly, in our push to be more efficient in the age of AI, we lost some of the very talent we needed.
The good news: Jonathan came back. In August, he applied for one of our newly-opened roles, and we rehired him. On a Zoom call, he told me sheepishly that coming back felt like “sneaking back in the house after I got kicked out.”
That was a gut punch. But the next part was worse: When we reactivated his account, he said, he found our cold, corporate restructuring announcement still sitting in his inbox. What struck him was how impersonal it felt. In my mind, we were announcing a restructuring. In his, people he knew and worked alongside had just lost their jobs. Why couldn’t we have simply acknowledged them—and said something kind about the people who were leaving?
Cringe. I won’t have to learn that lesson twice.
At a time when every CEO feels they have to move faster, get leaner and reorganize completely around AI, it’s easy to undervalue the people you already have. AI-attributed cuts peaked in May, when US employers announced 97,000 job cuts and blamed 40% of them on AI. Zillow cut more than 500 people earlier this month, announced the day before earnings, according to executive coaching firm Challenger, Gray & Christmas.
The AI excuse is getting old. Former Lululemon executive Julie Averill wrote a piece in the New York Times earlier this month saying you either see leaders believing they can fix a problem by waving AI at it (“AI wishing”) or blaming AI on job cuts (“AI washing”) credited to efficiency that doesn’t exist yet.
Companies are imagining what AI might make possible, and making moves before fully understanding how to get there. Three in 10 employers eliminated positions after implementing AI, only to later add those roles back, according to an April 2026 study by global staffing firm Robert Half.
I’m not saying companies shouldn’t change. That’s not the lesson. We had to change, when we shifted from being more of a pure software consultancy to becoming an AI-centric technology company. Advisory work remains an important part of what we do, but the center of gravity shifted. New priorities required new roles, and inevitably, some restructuring. But I did learn something about the danger of chasing the Next Big Business Model before fully understanding whether the skills, experience, and institutional knowledge you already have can evolve with you.
There’s a refrain in the market along the lines of ‘knowledge work is becoming irrelevant in the age of AI.’ I’ve come to believe almost the opposite: AI can make experienced people even more valuable, if you give them the right tools to adapt. Roles can evolve. Skills can be rebuilt. But that requires leaders to invest in training and creating a path for people to make that transition. And as leaders, that’s on us.
The bottom line is: People aren’t interchangeable parts. Institutional knowledge, trust, relationships, expertise–all those things take time to build and sometimes you don’t fully understand their value until they are gone.
In the end, I share this small yarn about Jonathan because it is ultimately a story of second chances–both for an employee taking another chance on a company, and of a company taking another look at what it values.
It’s also about reinvention. As leaders, we spend so much time looking forward that we forget the value of also looking back, and questioning the decisions we made along the way.
It’s okay to change your mind. To reinvent yourself. Reinvent your company. Reinvent your team. Reinvent your leadership style. Sometimes moving forward means admitting you got something wrong–and getting a second chance to make it right.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune. This is a repost of Pay Dirt, the Substack by regulator Fortune contributor Maria Colacurcio about compensation, AI, and the systems we choose to build.
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