The jobs market is slowing. AI may not be the cause, but it is changing the rules.

Last week I wrote about something I had been noticing in conversations with highly capable people.

People I know well. People with strong track records. People I would happily hire myself. Many were struggling to find roles.

The response was extraordinary. It clearly struck a chord with many people experiencing exactly the same thing.  Since then I have spent some time looking more closely at the evidence. The first thing to say is that this is not simply a UK problem. The UK labour market is undoubtedly weakening. Unemployment has been rising, job vacancies have fallen significantly from their post pandemic highs, and many employers are prioritising cost control over growth.

However, similar patterns can be seen elsewhere.  The United States is still creating jobs, but hiring activity has slowed markedly. Economists increasingly describe it as a "low hire, low fire" market. Companies are not making dramatic cuts, but they are not recruiting aggressively either.

Across Europe, hiring remains stronger than in the UK, but vacancy rates are falling and employers are becoming increasingly selective.  Something broader is happening.  The obvious explanation is economic uncertainty.  Businesses dislike uncertainty.  Trade tensions, geopolitical instability, inflation concerns, government debt, interest rates and slowing growth all make organisations more cautious. When leaders become uncertain about the future, recruitment is often one of the first things they slow down.

That is not new.  What may be new is how AI is influencing the response.  I am increasingly convinced that AI is not causing the slowdown. But it is changing how organisations behave during a slowdown.  Historically, companies often hired ahead of expected growth, they anticipated demand, they recruited capability, they built capacity before it was fully needed.

Today many leaders appear to be making a different calculation.  Instead of hiring additional people, they are asking whether AI can absorb some of the workload.  Instead of creating new positions, they are redesigning processes.  Instead of expanding teams, they are waiting.

This creates a subtle but important shift because he question is no longer simply "Do we need more people?" It becomes "Do we need more people, or do we need different technology?"  That distinction matters, especially if you are just entering the workforce.

One of the most striking findings I came across was the decline in entry level hiring across many occupations. Software engineering, accounting, data analysis, legal support, graphic design and product management have all experienced significant reductions in advertised opportunities.

These are not manual jobs, they are information processing jobs.  The very kinds of activities that AI is increasingly capable of supporting or partially automating.

This does not mean these professions are disappearing, far from it.  What may be disappearing are some of the traditional routes into them.  Historically, organisations hired junior people to perform routine tasks while they learned the profession. Junior accountants performed basic analysis. Junior lawyers reviewed documents.Junior software developers wrote straightforward code. Junior analysts prepared reports.

Those activities created experience and that experience created expertise.  Then for some that expertise created future leaders.  But AI is beginning to disrupt that pathway.

If technology performs some of the routine work, how do people gain the experience that eventually develops judgement?  That may turn out to be one of the most important workforce questions of the next decade.  The challenge for leaders is that this is not simply a recruitment issue, it is a capability issue.  Every organisation needs experienced people tomorrow.  Those experienced people can only exist if someone creates opportunities for less experienced people today.

The challenge for individuals is equally significant.  Many careers were built on a model of accumulating expertise over time. Increasingly, employers appear to be placing greater emphasis on adaptability, learning agility and the ability to work alongside AI.  The people who thrive may not necessarily be those with the deepest expertise, they may be those who learn fastest and adapt most effectively.

We are still in the early stages of understanding this transition.  The evidence does not support the idea that AI is causing widespread unemployment.

Yet.

What the evidence increasingly suggests is that AI is changing employer behaviour, and employer behaviour ultimately shapes the labour market.  The question is not whether jobs will continue to exist. The question is how organisations will create the next generation of talent if the traditional apprenticeship model of professional work begins to disappear.

That is a question leaders should be thinking about now, because by the time the answer becomes obvious, it may already be too late.  For those interested in AI, the story is not really about technology.  It's about people;  As it always has been