When access to advanced AI models is no longer the big differentiator, the real advantage comes from how effectively a business can connect those models to its own unique data. That was the central theme of my conversation with Rahul Pathak, Vice President of Data and AI Go-to-Market at AWS, recorded live at the AWS Summit in London.

In a bustling booth on the show floor, Rahul explained how AWS is helping organisations move from AI pilots to production at scale. We discussed the layers of infrastructure AWS provides, from custom silicon like Trainium and Inferentia to services such as SageMaker, Bedrock, and Q Developer, and how these combine to give enterprises the flexibility and performance they need to build impactful AI applications.

Rahul shared examples from BT Group, SAP, and Lonely Planet, each showing how the right blend of tools, data, and strategy can lead to measurable business results. Whether it is accelerating code generation, generating custom travel guides in seconds, or using generative AI to produce personalised content, the common thread is a focus on business outcomes rather than technology for its own sake.

A key point in our discussion was that most companies do not have their data ready to power AI effectively. Rahul broke down how AWS is helping unify siloed data and make it available to intelligent applications, turning a company’s proprietary knowledge into a competitive edge. We also touched on responsible AI, sustainability, and the operational challenges that come with scaling AI, from cost efficiency to security and trust.

For leaders still weighing up whether to invest in generative AI, Rahul’s message was clear: waiting too long could mean being left behind. This episode is a practical guide to what it takes to deploy AI with purpose and how to ensure it delivers lasting value in a fast-changing market.

What if the food we eat every day is silently undermining our health, and AI holds the key to reversing it?

In this episode of AI at Work, I sit down with Jonathan Wolf, co-founder and CEO of Zoe, to explore the intersection of AI, microbiome science, and the future of personalized nutrition. If Zoe sounds familiar, it’s likely because of their groundbreaking COVID study app or their clinical trial published in Nature Medicine proving Zoe’s approach is more effective than standard dietary advice. But this isn’t just about test kits or health trends.

Jonathan shares the origin story behind Zoe, including how a chance meeting with Professor Tim Spector turned a pivot from adtech into a mission-led company focused on improving the health of millions. We explore:

• How AI is powering Zoe’s free new app launching in the US
• The dangers of ultra-processed food and what’s really inside your meals
• Why personalized advice and behavior change, not food tracking or perfection, are key to long-term health
• What shotgun metagenomics can tell you about your gut and why that matters
• The ethical challenge of combating food industry misinformation at scale

From photo-based food recognition to conversational AI that understands your microbiome, Jonathan breaks down how science, data, and product design are working together to make health advice smarter and more accessible.

Whether you're a founder thinking about your next pivot or someone just trying to eat better without obsessing over every bite, this conversation offers real insight and practical steps.

What if your tools could finally talk to each other and reduce meetings, manual tasks, and copy-paste chaos in the process?

In this episode of AI at Work, I sit down with Sanchan Saxena, Head of Product for Work Management at Atlassian, to unpack the thinking behind their new Teamwork Collection. Recorded live at Team 25 in Anaheim, this conversation explores how Atlassian is bringing together Jira, Confluence, Loom, and AI-powered agents into a single, streamlined experience.

Sanchan shares how his team is designing tools that not only integrate more deeply but also help companies work more effectively. We discuss how AI is now summarizing meetings, creating Jira tickets from Loom videos, and pulling historical campaign data directly into brainstorming sessions in a way that fits how teams actually work.

We explore:

• How the Teamwork Collection helps overwhelmed teams cut through digital noise
• Real-world use cases from companies like Rivian saving hundreds of hours a year
• Why context switching kills productivity and what a unified experience can solve
• The growing role of agentic AI in supporting, not replacing, teams
• How Atlassian is helping customers overcome change fatigue and adopt new workflows
• Why AI is no longer a luxury but a critical enabler of business velocity

Whether you're leading digital transformation or just trying to tame your team’s growing tool stack, this episode offers clear insights into where collaboration is heading and why simplicity, clarity, and connectedness are the new competitive edge.

Explore the Teamwork Collection at atlassian.com/collections/teamwork

Ask ChatGPT

In this episode of AI at Work, I sit down with Mike Mason, Chief AI Officer at Thoughtworks, to explore what happens when the generative AI hype starts to settle and businesses begin asking the real questions. What’s working, what’s not, and what does mature adoption actually look like in 2025?

Mike brings a practical, deeply informed view of the AI landscape. We talk about how intelligent agents are evolving well beyond basic chatbots and starting to act as collaborative teammates inside real workflows. From customer support to software development, these agents are now reasoning, adapting, and in some cases, working alongside other agents to get things done.

We also explore the growing shift toward open source AI. Mike explains why some companies, especially in regulated sectors like financial services, are leaning into in-house or fine-tuned small models for better control, data security, and flexibility. We unpack what’s driving the rise of small language models and why in many cases, smaller, more nimble models are outperforming their larger counterparts in speed, privacy, and efficiency.

One of the most thought-provoking parts of our chat was about the diverging paths organizations are taking with GenAI. Mike shares insights from Thoughtworks’ upcoming global survey, which shows that while some are embedding bias detection and strong governance into their strategies, others are focused purely on quick wins and interpretability. That divide is shaping not just how projects are executed but how companies are thinking about long-term AI maturity.

If you're navigating the tension between speed and safety or trying to decide whether to build, fine-tune, or adopt off-the-shelf models, this conversation offers real perspective. We cover explainability, regulation, open ecosystems, and what tech leaders should be planning for next as AI becomes part of everyday business.

This isn’t about future hype. It’s about how AI is actually getting to work.

In this episode of AI at Work, I’m joined by Simon Ranyard, Managing Director for Northwest Europe at Orange Business, to challenge old assumptions about manufacturing and reveal how technology is rewriting the rules.

We discuss how AI, automation, augmented reality and 5G are giving manufacturers the tools to boost productivity, reduce downtime and create high-value careers instead of cutting jobs. Simon shares practical insights on where the UK stands, how to close the skills gap, and why apprenticeships and reskilling are more important than ever.

If you think factories are all grease and gears, this conversation will make you think again. Take a closer look at how Orange Business is helping manufacturers adapt and thrive, and what this means for workers, companies and the wider economy.

In this episode of AI at Work, I sit down with Dennis Woodside, CEO of Freshworks, to uncover how real companies are getting true value from AI.

Dennis shares how Freshworks has built AI tools that help businesses resolve routine questions automatically, boost agent productivity, and give managers clear performance insights without needing complex dashboards. He explains the company’s focus on making AI quick to deploy and simple to buy, so mid-sized companies can see immediate returns without endless consulting bills.

We explore customer stories like Total Expert, which saved thousands of agent hours and saw a 250 percent return on its AI investment. Dennis also talks about the lessons learned from integrating AI internally and how the company stays flexible enough to adopt the latest advances from across the industry.

This conversation is for anyone who wants to see beyond the AI hype and hear how smart companies are using it to save time, cut costs, and let people focus on more rewarding work.

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.