AI is already in our lecture halls and our workplaces, but the real question is whether we are using it to learn faster and build better, or just to cut corners more efficiently. I sit down with Professor Dr Vincent Ginis (VUB Brussels, visiting professor at Harvard) to unpack what he is seeing on the ground as universities rethink assessment, companies scramble for “AI strategy”, and everyone tries to work out what responsible adoption actually looks like.

We get into the messy reality behind the headlines: why focusing only on cheating misses the upside of personalised AI tutoring, why continuous evaluation suddenly becomes feasible, and why some of the healthiest learning environments may be the ones with clear “no screens” time to protect attention. Vincent shares a useful lens: AI puts both good and bad behaviours on steroids, so the challenge is designing systems that reward real understanding rather than outsourced cognition.

From there we move into workplace AI adoption and AI governance. We talk about Goodhart’s law, the traps of measuring the wrong things, the tension inside IT departments between security and experimentation, and why heavy-handed guardrails often produce shadow AI anyway. Vincent makes the case for internal champions, high-variance experiments, and building new products as the gap between idea and execution collapses. If your organisation is stuck rewriting emails, this conversation will help you aim higher.

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