According to Fortune, AI spending is set to hit $500 billion this year. Training budgets are shrinking at the same time. That is not a coincidence. That is a decision.

The same reporting found that nearly three out of four knowledge workers are already using AI at work, and more than half of them have never been formally trained to use it well. Companies bought the tool and skipped the person. They are betting that the software will do the job the training used to do.

Here is the part that should actually worry a leadership team: Even where training budgets held steady, the money is buying less.

Research from LMSPedia's 2026 benchmark found the cost of every hour of training an employee actually completes has jumped 34% in a year. Companies are paying more for less learning, and TalentLMS's 2026 L&D report found a large share of leaders admit their AI training exists to automate roles, not to make the people in those roles sharper.

The AI investment is real. The intent behind it is not what employees think it is.

So the analyst sitting in that seat feels it before anyone says it out loud.

Development stalls.
Feedback gets less frequenct.

The "learning platform" turns into a content library nobody has time to open. And the data backs up what that analyst already suspects.

Lack of career growth is the single most common reason people say they'd leave a job. Employees with a real path forward stay noticeably longer than employees without one. Nearly all employees say they would be more loyal to a company that visibly invests in them.

None of this is rocket science. It has been measured for years. Companies keep choosing to test it anyway.

The real cost is bigger than turnover. Most disengaged employees are not quitting. They are staying and coasting. Barely a quarter of employees worldwide say they are genuinely engaged, and Gallup puts the price of that disengagement at close to $9,000,000,000,000 (that's nine trillion dollars) in lost productivity globally.

That is not people walking out the door. That is people showing up and doing the minimum, because the company already told them, through its spending, what it thinks they are worth.

Here is my opinion after reading all of this, and after watching it play out with people I train every week.

If you are the analyst in this situation, waiting for your company to fix this is not a strategy. It might happen. It might not.

Either way, your skills, your judgment, and your ability to do work that matters are yours to build, with or without a training budget behind you.

The companies underinvesting in their people are not making those people less capable. They are just making it someone else's job to notice.

I'd rather it be you who notices first. If you want a way to make the case internally instead of just accepting the gap, I put together a justification letter analysts can use to ask their company to invest in their development. It is built to hand to a manager, not to argue with one.

If you are the leader reading this and recognizing your own budget spreadsheet in it, the fix is not spending more. It is spending on the right thing.

Training tied to a real skill gap, connected to what your team actually needs to execute the strategy, taught by someone who works with the tool every day, outperforms a generic content library every time, at a fraction of the noise.

That is what NLT for Teams exists to do, so I won't belabor it here. But if that is the gap you are staring at, it is worth a conversation.

Here is the uncomfortable version of all this. AI did not create this problem. AI gave companies a convenient new place to hide a decision they were already making.

What is the version of this you are seeing, in your own team or your own company? Hit reply and tell me. I read every one.

Andy

P.S. If you want the justification letter to bring to your manager, reply and I'll send it over.