AI has become part of how you work. Whatever your job, there is now a tool that will draft the email, summarise the document, write the first version of the report or the code, or suggest what to do next. Access to that help is no longer the thing that sets anyone apart, because soon everyone in your field will have the same tools open on the same screen. What will set you apart is something the tools cannot give you: knowing how to get good work out of them, and knowing when to ignore what they tell you.

That sounds obvious until you see how differently it plays out for two people using the exact same tool. There is now solid evidence that the same AI can make one person noticeably better at their job and another person worse, and the difference is entirely in how they use it.

Access is not the same as capability

The clearest demonstration comes from a field experiment published in Management Science, where researchers gave a GPT-4 assistant to 640 small business owners in Kenya and tracked what happened to their profits. On average, the assistant made no difference at all. But the average hid two opposite stories.

The people who were already strong at running their businesses used the AI to get just over 15 percent better. The people who were struggling used the very same assistant and ended up nearly 10 percent worse than if they had never had it. Same tool, same access, opposite results. And the reason matters for you, because it was not about who asked better questions or who received better advice. Both groups got broadly similar suggestions. The difference was what each group chose to do with them.

The stronger performers filtered. They took the advice that fit their situation and set the rest aside. The weaker performers acted on more of what they were told, including generic suggestions that did not fit, and their results suffered for it. In other words, the value did not come from having the AI. It came from the judgement the person brought to it. That is the whole game now, and it is worth understanding what it means for your own career.

Your advantage is knowing when to push back

AI suggestions carry a hidden risk. The tool speaks with exactly the same confidence when it is right for your situation and when it is wrong for it, because it does not know your context the way you do. It has never met your client, does not understand your constraints, and cannot see the thing you know from experience that makes a textbook answer the wrong one here. It will still answer with total assurance.

So, the professionals who will be worth the most are not the ones who can prompt the fastest. They are the ones who can look at a fluent, confident AI answer and tell whether it is any good, and who know when to override it with their own expertise. As AI gets more capable, that skill becomes more valuable, because more and more plausible-looking output will need someone who can judge it. Your expertise does not become obsolete. It becomes the thing that decides whether all that AI output is worth anything.

The habits that build the judgement

This kind of judgement is learnable, and it comes down to a handful of habits you can start practising on your real work today:

1. Learn your fundamentals properly. You can only tell that a suggestion is wrong for your situation if you understand your situation deeply. The stronger your grasp of your own field, the sharper your filter. This is why learning the basics matters more since AI arrived, not less.
2. Treat every AI answer as a proposal to weigh. Acting on a suggestion is a decision you make each time, so get into the habit of pausing to ask whether this particular answer fits your situation before you accept it because it sounds right.
3. Ask what the tool cannot see. Before you act on a suggestion, name what the AI does not know about your circumstances, and check whether the advice still holds once you put that context back in.
4. Test before you trust. When an answer looks promising, try it on something small before you build on it, so a poor fit costs you a little rather than a lot.
5. Keep track of your own hit rate. Notice which AI suggestions you accepted, which you rejected, and how each turned out. That feedback loop is how your judgement gets sharper over time.

How you become more valuable as AI improves

The reassuring part is that this points somewhere hopeful. The better AI gets, the more it rewards the person who can direct it well, because the gap between someone who has AI and someone who is good with AI keeps widening. Build real skill in your field, learn to use these tools with judgement, and you become harder to replace as the technology advances, not easier. That combination, deep expertise plus the judgement to steer AI, is exactly what our training programmes are built to develop. Having AI will soon be ordinary. Being good with it is the advantage, and it is one you can choose to build.