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

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