Use AI tools well, know where they fail, and understand what they change about the work you are aiming at.
AI tools are now part of studying and working in Kenya, and the useful position is neither panic nor faith. They are very good at first drafts, explanations, summarising and getting you unstuck, and they are unreliable about facts, especially local ones. Treat output as a confident first draft from someone who has never been to Kenya and does not know when they are wrong.
The single most important habit is verification. These systems produce fluent text regardless of whether they know the answer, so they will invent a statute, a fee, a deadline or a citation with exactly the same confidence they use for true things. Anything you would act on — a requirement, a date, a number — gets checked against the official source before you rely on it.
Using AI on academic work is a question of rules, not conscience alone. Institutions differ, and the penalty for guessing wrong is severe, so find out what yours actually permits and where the line is between help and submission. Where it is allowed, say what you used it for; being straightforward about it costs far less than being found out.
For work, the honest picture is that AI is changing tasks faster than it is removing whole jobs, and the tasks going first are the routine ones a junior person used to learn on. That makes two things more valuable, not less: judgement about whether an output is any good, and the practical experience that lets you tell. Which is an argument for going and doing real things, not for avoiding the tools.
Finally, be careful what you paste in. Personal data, someone else's information, exam material, anything confidential — once it is sent to a service you do not control, you cannot get it back.