The Peter Principle: Using AI Drives Your Promotion

For argument’s sake, let’s start by considering an AI engineer working at a fast-growing tech company. He’s great at building efficient AI models, optimising workflows, and tackling tough technical challenges. His work doesn’t just keep things running smoothly but also pushes the company forward. Naturally, he gets promoted, but not to a more senior technical position. Instead, he’s made head of the AI department.

Suddenly, he’s far from the hands-on work that he was so good at. His days are mostly filled with reviewing team progress, attending meetings, handling budgets, drafting hiring plans, and resolving conflicts. There’s a chance he won’t perform well in this new role. Why? Because being a top engineer doesn’t automatically make him a good manager. And unless he adapts fast, he’ll likely struggle, finding himself stuck between what he used to excel at and what he’s expected to do in his new role.

Now, imagine this happening across every department, in every company, and every industry. Competent individuals are promoted out of their skill zone, becoming leaders who might perform poorly. Eventually, organisations will become filled with people stuck in roles they aren’t suited for, instead of doing the tasks they were good at.

That’s called the Peter Principle. And it doesn’t just impact people who move into higher positions; it also quietly affects teams, collaboration, and employees’ confidence in their own abilities along with the overall productivity, innovation, and even the long-term competitiveness and success of companies. Moreover, in industries where the pace is fast and the stakes are high, it can bring organisations to a halt.

If we start or are already promoting people based on AI-enhanced performance, we risk filling leadership roles with those who aren’t truly equipped to lead. Not because they’re not smart, but because the skills needed to run a team, department, or division don’t come from prompts and algorithms.

That could create a big gap between what an organisation needs and what it actually gets. Over time, it could change companies completely. To get the leaders they need, businesses might stop relying on promoting existing staff to fill leadership roles. Instead, they could adopt flatter structures, with fewer management layers, more sideways moves, and a greater focus on specialist roles.

We might also see a stronger shift towards more flexible roles, with people moving between projects or temporary positions where their skills fit best, rather than being stuck in a rigid hierarchy. AI could speed this up, not just by causing the problem, but also by helping us find new ways to fix it.

So, is the Peter Principle really a problem?

Truth be told, it is, but not in the way most people think. The Peter Principle isn’t necessarily about bad promotions, but a symptom of something much bigger: the way we assess, reward, and move talent is simply wrong.

But here’s where things get interesting. A group of researchers ran computer simulations(pdf) to see how organisations could perform better under the Peter Principle. The surprising outcome was that randomly promoting people often led to better overall results than choosing candidates solely based on their achievements.

Why might this actually work? Simply because if an employee needs completely different skills and expertise in the new role, promoting randomly avoids locking skilled people into roles they’re not suited for. Of course, no one is suggesting we start flipping coins to choose team leaders, but it does challenge the idea that climbing the ladder is always the best use of talent.

However, despite this insight, the Peter Principle remains a challenge that won’t disappear on its own. In fact, industry leaders expect AI to make it worse. On the other hand, it also gives us a reason to rethink how we build and run organisations, which should be done with more awareness, flexibility, and maybe a lot more realism and honesty about what business success actually looks like.