People often ask me, “What’s the best way to use generative AI?” I’ve spent a lot of time thinking about this, experimenting with different approaches, and observing how these tools behave. One thing I’ve learned is that generative AI is not a magical engine that manufactures information out of nowhere. Models are trained on historical data, the information that already exists on the internet or has been fed into them. This means AI can only work with what it has been given. It doesn’t automatically understand your personal context, your unique insights, or your specific research unless you provide that to it.
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WHY YOUR OWN DATA CHANGES EVERYTHING
This is why using your own data is so powerful. When you gather your own information, conduct your own research, or compile your own dataset and then feed that into a generative AI system, something significant happens. The output becomes richer, more relevant, and far more accurate. AI can produce better results because it is working with material that reflects your actual goals and the specifics of the situation you’re studying. It is no different from data science: the quality and relevance of the dataset you provide will determine the quality and relevance of the results you get back.
AI WORKS BEST AS AN ASSISTANT, NOT A REPLACEMENT
A lot of people try to use generative AI as a replacement for effort, approaching it with an empty slate and hoping it will deliver something brilliant. But that approach rarely leads to excellence. The best results come when you have already done the core work, the thinking, the research, the organisation, and then use AI to help refine, simplify, analyse, or shape what you’ve created. When you use generative AI as an assistant rather than the entire workforce, it becomes much more effective. It elevates your input instead of trying to create meaning without any foundation.
MY HONEST OBSERVATION
From my experience, the most brilliant results come when you come prepared. When you bring your work, your research, and your understanding to the table, generative AI enhances what you’ve built. But when you show up with nothing and expect the tool to fill in all the gaps, the output tends to be generic or incomplete. AI is at its best when it is used to boost productivity, expand knowledge, or simplify complexity, not to bypass the effort of learning or creating. That has been my consistent observation, and I believe it’s an important mindset for anyone who truly wants to benefit from generative AI.
Hi, I’m Dr. Mobolanle Bello, a Computer Science Lecturer with over 15 years of experience in software engineering, web development, data science, database management, ebusiness, research, and education. My expertise includes creating bespoke digital solutions such as e-learning platforms and e-commerce sites, alongside conducting research in AI, machine learning, and network optimisation. I have published my work in respected journals and conferences, contributing to advancements in technology. Outside of academia, I am passionate about using technology to improve lives and am committed to inspiring the next generation of tech professionals through teaching and collaboration.
