What happens when you bring together a practicing monk, a seasoned tech entrepreneur, and an AI education pioneer? In this episode of The Tech Talks Daily Podcast, I sit down with Prashant Raizada, the driving force behind Lumi Network, to explore how we can build a workforce ready for the AI era, not just in skills, but in mindset and purpose.
Prashant shares how his journey from global banking and McKinsey to founding five startups worth over $2 billion eventually led him to education technology. But Lumi is not just another edtech venture. It's a mission-driven platform focused on upskilling the current and future workforce through human-AI collaboration, regional transformation initiatives like the Scale Up North East campaign, and a clear-eyed view of what education should look like in a rapidly changing world.
We talk about the need to rethink our approach to curriculum design, the limits of traditional university models, and why collaboration between industry, academia, and government isn’t just helpful, it’s urgent. Prashant explains why AI isn’t a threat to humans but an amplifier of our abilities when used with intention. And he shares how Lumi's "Quest" programme trains participants in collaborative problem-solving while subtly building the 12 essential skills for thriving in an AI-powered economy.
We also tackle the bigger picture: why education has often been overlooked in AI investment conversations, and what needs to change for the sector to finally unlock the $10 trillion opportunity ahead of it. Prashant doesn't shy away from the challenges but makes a compelling case for why the UK could become a global exporter of a scalable, human-centric education model.
So, what would it take to scale this nationally? And if we’re serious about upskilling 7.5 million people by 2030, who’s going to deliver it? Prashant believes startups like Lumi could be a central part of the answer and the time to act is now.
Could meaningful AI education be the missing piece in our national skills strategy? And what does real collaboration between humans and machines actually look like in practice? Let us know your thoughts after listening.
