My first mathematics classroom was the open ground under a neem tree in northern Nigeria. My twin brother and I walked there each morning and sat with the other pupils while the teacher stood beside a small blackboard leaning against the trunk. We had no books and no writing materials. He gave us classwork, we wrote our answers in the sand with our fingers, and he moved from pupil to pupil, marking each one on the ground. At the closing bell, we left it all there, and by morning, the wind had cleaned it away. Nothing we wrote survived the night, and yet the mathematics stayed with us.

Later, we moved to a school with a classroom and small wooden chairs, and writing on paper felt like a promotion. By the time I reached university, there was still no such thing as AI in my world. The internet was there, but we hardly got connected to it, and we preferred the traditional way of reading books. My Diploma and undergraduate years were spent in the library with mathematics textbooks, copying every formula by hand. It was me, a pencil and paper, and I kept going that way for years, up until my master's degree. Then came computers and the gadgets we use for research today, and the way I worked changed shape again.

So, when the talk about AI began during my years as a PhD research scholar, I already had a history of the ground shifting under me. It still frightened me. The first fear was the noise itself, the loud claims that machines were about to replace us. Then came a sharper one. I imagined waking one morning to hear that somebody, somewhere, had used AI to solve the problem I had worked on for years. Behind both sat the real uncertainty: what happens to research when these machines take over the part of the work we believed was ours?

What steadied me was a simple observation. The machines do not run on their own; somebody has to give the command, to click, to decide that a question is worth asking at all. My visit to Germany turned that thought into a decision. At the 12th Heidelberg Laureate Forum, I spent days among mathematicians, computer scientists and AI researchers, hearing how carefully they spoke about what these tools can and cannot do. I came home and stopped watching from a distance.

The difference has been real since then. Ideas that stayed abstract for years are now practical in my hands, and work that once cost me weeks now takes days. But the help arrives only where I already know my subject. Where I have not built the basics myself, what I get are sentences, not understanding.

So, my approach to this change is to walk into it and learn it, as I once walked from writing maths on the sand to sitting and doing maths on a wooden chair, from the chair to a library shelf, and from the shelf to a computer screen. Every one of those moves looked at first like something being taken away. My work is being redefined, not removed. Ideas will grow bigger, and perspectives will keep shifting, but mathematics is still mathematics, and mathematicians are still mathematicians. The question, the judgement and the duty to know why an answer is true remain ours.

The wind will clean the ground again, and what we understand will remain. AI is a new surface for us to write on.