Why AI adoption fails

Employees have the best AI models available at work, the connectors are hooked up, they know how to use them, and they have colleagues who already use them. And they still do not. To the point that before a meeting they will not write a single prompt to find the fundamental things in their own advertising account, and would rather risk that someone else spots the problems.

This is happening.

Recently, in a meeting, I found a campaign in an advertising account that someone had written off as ineffective. Among its ads was a video with very high potential on CTR and CPC. I had not seen numbers that good in that account for a long time. But it had not been shown to enough people, so the potential was nowhere near used. Nor even discovered, because the ad specialist had switched it off.

It would not have happened if the colleague had asked the AI model connected to their advertising account.

Why people do not use the AI they already have

When I talk to colleagues from different departments about how they work today, it is like visiting an open-air museum. I think to myself, it is 2026, nobody does these things by hand any more. Then I realise that yes, they do. Real AI adoption is at the very beginning, even in modern, technology-driven companies. In more conservative firms and state institutions it has often not even started.

It is not about time or AI skills. It is the inertia of old thinking. People simply do not stop and ask themselves whether they could do it differently, whether AI could help them with the task.

Understand that it is 2026

Everyone, please stop. Take a step back so you can see the whole of the work you do, the processes you are part of, and ask yourself how a machine could do that work for you. Which tools you need to connect to that machine. For example a newsletter tool, a graphics program or an advertising system. Whatever you need.

If you do not, someone who does will probably replace you.