In this episode of AI at Work, I catch up with Amanda Brock, CEO of OpenUK, for a wide-ranging conversation on the changing landscape of open technology, AI transparency, and international collaboration.

We explore how OpenUK is working ahead of the market, helping shape policies and support for open source projects while responding to rising geopolitical tensions and funding pressures. Amanda explains how the UK occupies a unique position between the EU and the US and what that means for future AI standards and regulatory frameworks.

We also discuss:

• The sustainability challenges facing open source communities and maintainers
• Shifts in AI development, including legal and ethical questions around IP and model transparency
• The role of tools like Roost and initiatives like Current AI in creating practical solutions for AI governance
• Why "tools, not rules" may offer a more realistic path than top-down regulation
• The importance of keeping open source accessible as a route into the tech industry

Amanda shares her concerns about the rollback of EDI efforts and highlights how open communities can still offer a clear path into tech for people from underrepresented and underserved backgrounds. We discuss OpenUK's upcoming skills report and how it aims to highlight open source as a solution to address the ongoing talent shortage.

Recorded ahead of International Women's Day, this episode also reflects on the slow progress around diversity and how leadership, policy, and community must come together to drive lasting change.

If you're interested in how policy, law, and open technology intersect with AI development, this conversation offers thoughtful perspective, clear examples, and real-world action.

🎧 Listen now and let us know where you think the future of open innovation is headed.

In this episode of AI at Work, I sit down with Juan Orlandini, CTO North America at Insight, to unpack the often-overlooked side of AI adoption: regulation, data strategy, and governance. While much of the recent conversation around AI has focused on speed, productivity, and experimentation, Juan brings the discussion back to fundamentals. Before you scale that shiny new AI tool across your business, have you classified your data? Have you considered your compliance obligations? And do you understand the different responsibilities that come with being an AI creator, adapter, or consumer?

Juan walks us through Insight’s perspective on the current state of enterprise AI, including how they’ve used their own internal tools like InsightGPT to stress test both opportunities and risks. We discuss why internal use cases are often the best place to start, and how leaders can avoid repeating the mistakes of past tech waves, like the race to cloud or mobile apps without a clear strategy.

We also explore the patchwork of US regulations, with California leading the way, and compare this to the EU’s more prescriptive approach. Juan explains how these emerging policies are shaping real business decisions right now, and what business leaders can do to stay ahead. Throughout our chat, his advice is grounded and practical, offering a steady counterpoint to the noise and hype.

Whether deep in deployment or just starting to explore how AI fits into your business, Juan's insights offer a roadmap to thinking bigger while avoiding costly missteps. How do you keep your organization agile enough to adapt, but stable enough to deliver? And what does it really take to treat AI as an enterprise tool rather than a passing trend?

Tune in to hear Juan’s advice on managing risk, reimagining processes, and building a culture that is ready for what comes next.

What if AI could help us discover new medicines faster, more accurately, and with greater impact for patients?

In this episode of AI at Work, I speak with Dr. Chris Austin, Head of Research Technologies at GSK, to explore how artificial intelligence is changing the way new treatments are developed. Chris brings a unique perspective shaped by decades of experience across academia, biotech, government, and now big pharma. His mission at GSK is clear: to bring science, technology, and talent together to radically improve human health.

We unpack how AI, combined with massive clinical and genetic datasets, is enabling GSK to target disease with unprecedented precision. From identifying the right molecular pathways to simulating clinical trials using digital twins, Chris walks us through how technology is helping reduce development timelines and increase the chances of success. He shares powerful examples including a promising asthma treatment that moved from first-in-human testing to Phase 3 trials across four diseases in record time.

We also explore how GSK uses AI to improve patient selection in clinical trials, design oligonucleotide-based therapies for hard-to-treat conditions like hepatitis B, and incorporate generative AI into everything from drug design to safety prediction. According to Chris, the key isn't just having better algorithms. It's about generating the right data, at scale, to make those algorithms meaningful.

If you're curious about how AI is being applied to some of the most complex problems in healthcare, this episode offers a rare inside look. Chris also reflects on his journey from medicine to data science, and why this is the most exciting time he’s seen in drug development.