When we talk about cybersecurity, it’s often easy to think in terms of firewalls, passwords, and high-profile breaches. But what happens when the vulnerability isn’t within your own systems but somewhere deep in your third or fourth-tier supply chain? In this episode, I spoke with Ben Edwards from Bitsight about the unseen infrastructure propping up much of the global digital economy and the new risks emerging from it.

Our conversation begins by challenging the assumption that larger technology providers are automatically safer. Bitsight’s research reveals that scale often introduces complexity and a larger attack surface, which can make it even harder to stay secure. In fact, UK supply chains are now around 10 percent larger than the global average, reflecting a more advanced digital economy but also introducing more room for hidden weaknesses.

One of the most sobering parts of the discussion focused on geopolitics. Around 30 percent of UK and US supply chains rely on Chinese military-linked companies like Huawei and China Telecom. That’s not just a cybersecurity concern. It’s a geopolitical time bomb. Ben broke down the ripple effects that potential restrictions or bans could have, including costs, infrastructure overhauls, and widespread operational disruption.

Then there are the “hidden pillars,” smaller vendors like Aptiv and Yardi, which may not be household names but play disproportionately influential roles in sectors like aerospace, education, and real estate. Their obscurity makes them dangerous single points of failure, especially when regional dependencies form without anyone noticing.

The bottom line? End-to-end supply chain visibility remains elusive. Shadow IT, employee workarounds, and a constantly shifting tech landscape mean organizations must approach cybersecurity as an ongoing process, not a checklist. Ben urges companies to continually assess the criticality of their providers and, just as importantly, understand their own role in others’ ecosystems.

If you’re curious about how internet balkanization, AI, and outsourcing are shaping the next phase of cybersecurity strategy, this episode will give you a lot to think about. Y

IT support is changing fast, and the old service desk model is starting to feel like a relic from another era. In this episode, I spoke with Samuele Gantner, Chief Product Officer at Nexthink, about what comes next and what companies need to do now to prepare for it. With Nexthink sitting at the forefront of Digital Employee Experience (DEX) technology, Samuele offers a grounded, thoughtful look at what a "ticketless" future might look like.

One of the boldest predictions shared is a 90 percent reduction in IT support tickets by 2027. That is not marketing spin. It's a vision rooted in practical shifts toward proactive support, real-time observability, and AI-powered automation. Samuele explains how organizations can move away from reactive models by embracing intelligent agents that solve problems before a ticket is even raised. Instead of asking employees to fix things themselves, IT support is quietly transforming into something far more sophisticated and intuitive.

We talked about what drives this change, from millennial and Gen Z expectations to the technological leap enabled by large language models and automation. Samuele breaks down why old attempts at self-service failed and how today's AI agents are finally equipped to handle objective complexity with empathy, scale, and context.

He also shares examples that bring this future to life, including a retailer that avoided a costly outage through predictive alerts, a healthcare provider saving millions through experience-driven device refreshes, and an energy firm preventing disaster in a virtual desktop environment. These are not theoretical case studies. They are live proof that DEX is not just buzz. It works.

We also explored what skills IT teams need to thrive in this shift. It is not all about tech. Emotional intelligence, cross-functional collaboration, and a proactive mindset are just as important. Whether you're a CIO or a support engineer, there is something here that will challenge how you think about IT's role in the business.

AI is racing ahead, but for industries like life sciences, the stakes are higher and the rules more complex. In this episode, recorded just before the July heatwave hit its peak, I spoke with Chris Moore, President of Europe at Veeva Systems, from his impressively climate-controlled garden office. We covered everything from the trajectory of agentic AI to the practicalities of embedding intelligence in highly regulated pharma workflows, and how Veeva is quietly but confidently positioning itself to deliver where others are still making announcements.

Chris brings a unique perspective shaped by a career that spans ICI Pharmaceuticals, PwC, IBM, and EY. That journey taught him how often the industry is forced to rebuild the same tech infrastructure again and again until Veeva came along. He shares how Veeva’s decision to build a life sciences-specific cloud platform from the ground up has enabled a deeper, more compliant integration of AI.

We explored what makes Veeva AI different, from the CRM bot that handles compliant free text to MLR agents that support content review and approval. Chris explains how Veeva’s AI agents inherit the context and controls of their applications, making them far more than chat wrappers or automation tools. They are embedded directly into workflows, helping companies stay compliant while reducing friction and saving time. And perhaps more importantly, he makes a strong case for why the EU AI Act isn’t a barrier. It’s a validation.

From auto-summarising regulatory documents to pulling metadata from health authority correspondence, the real-world examples Chris offers show how Veeva AI will reduce repetitive work while ensuring integrity at every step. He also shares how Veeva is preparing for a future where companies may want to bring their LLMs or even run different ones by geography or task. Their flexible, harness-based approach is designed to support exactly that.

Looking ahead to the product’s first release in December, Chris outlines how Veeva is working hand-in-hand with customers to ensure readiness and reliability from day one. We also touch on the broader mission: using AI not as a shiny add-on, but as a tool to accelerate drug development, reach patients faster, and relieve the pressure on already overstretched specialist teams.

Chris closes with a dose of humanity, offering a book and song that both reflect Veeva’s mindset, embracing disruption while staying grounded. This one is for anyone curious about how real, applied AI is unfolding inside one of the world’s most important sectors, and what it means for the future of medicine.

What does modern cybersecurity look like when you're leading a federally regulated financial institution serving Canadians from coast to coast?

In this episode, recorded at Cisco Live last month, I sat down with Shawn Spurko, VP of Information and Cybersecurity at Innovation Federal Credit Union. Based in Swift Current, Saskatchewan, but now operating across the country, Shawn Spurko has played a key role in building a security posture that treats laptops as offices and supports a workforce no longer tethered to physical locations.

Shawn Spurkoshares his journey from service desk and web design to becoming a cybersecurity leader, and offers a refreshingly grounded view of how to approach regulation, zero trust, and digital maturity. He explains how Innovation CU’s move from a provincial to a federal charter transformed their compliance obligations and how solutions like Cisco Secure Access enabled them to scale security seamlessly for a hybrid workforce.

We explore why transparent, user-friendly security is no longer optional and how mature implementations of SWG, ZTNA, DLP, and management tunnels are quietly solving problems before users even notice them. Shawn Spurkoalso opens up about the practical realities of working with tools that are constantly evolving, and how his team reviews every new feature not just for capability but for how it maps to regulatory controls like Canada’s OSFI B-13.

This episode is a masterclass in modern cyber strategy, but it’s also a reminder that the goal isn't complexity, it’s making things work, everywhere, all the time.

So, as the cybersecurity landscape continues to shift and regulators tighten expectations, how are you designing systems that work for both users and auditors? And what lessons can we all learn from financial services as we navigate this new world of anywhere access?

In today’s episode of Tech Talks Daily, I sat down with Alberto Prado, Head of Digital and Partnerships for R&D at Unilever, to explore how one of the world’s largest consumer goods companies is reimagining innovation using AI. And not just in theory or in labs. This is technology already transforming the stuff most of us use every single day.

From Dove body wash to Knorr stock cubes, Unilever products reach more than 3.4 billion people globally. That scale makes their R&D choices deeply relevant to how we live. What stood out in this conversation is how deeply integrated AI has become across their research efforts. This isn’t about one flashy pilot project. Unilever currently runs over 400 AI initiatives across areas like microbiome science, biotechnology, and next-generation materials. Each one is focused on improving product performance, making items more sustainable, or creating personalized experiences for consumers.

Alberto shared how Unilever’s decades-long microbiome research is being accelerated through machine learning and high-performance computing. With over 30 terabytes of data and more than 100 patents, the company now holds one of the largest collections of human microbiome data in the world. That insight has directly influenced products like Dove and Vaseline and has led to innovations like the POND’S Microbiome Analyzer, which offers personalized skincare recommendations within an hour.

In the field of biotechnology, Unilever is working with partners like Arzeda to create enzymes that outperform traditional cleaning agents, all while being more sustainable. A great example is the breakthrough behind RhamnoClean technology in Sunlight dishwashing liquid. By mimicking natural fermentation processes, Unilever can now produce bio-based surfactants that clean effectively, reduce water use, and are kinder to the planet.

We also discussed how AI-driven virtual testing is replacing thousands of physical prototypes. This shift is helping Unilever rapidly develop new products like the Wonder Wash laundry detergent and Knorr’s Zero Salt Cube. Alberto explained how digital models can simulate everything from stain removal in different wash cycles to how a cube holds together without salt, long before any physical version is made.

And then there’s the R&D Assistant, Unilever’s own AI-powered co-pilot built in partnership with Microsoft. It connects over 150,000 scientific documents from across a century of research, letting scientists query insights in natural language. For Unilever’s 5,000 researchers, it’s not just a time saver. It’s changing how they discover, collaborate, and innovate.

This episode is a window into how legacy companies can drive transformation from within. Innovation isn’t just happening in new industries or through startup culture.

Sometimes it’s happening inside a washing machine cycle or a bottle of shampoo. So the question is, what can other large-scale enterprises learn from the way Unilever is scaling AI across its entire product development ecosystem?

What does it take to build a $100 billion cybersecurity company in today’s cloud-first, AI-infused world? And how do you balance relentless technological change with the practical realities of compliance, risk, and leadership? In this episode of Tech Talks Daily, I sit down with Sumedh Thakar, CEO of Qualys, during his visit to the UK for the company’s QSC conference. From starting out as one of Qualys’ first engineers to leading the company through a new era of risk-centric cybersecurity, Sumedh brings a unique blend of technical insight and lived experience.

We discuss why compliance remains such a challenge for enterprises, how the conversation is shifting from attack surfaces to risk surfaces, and why many businesses are overwhelmed by security signals but underwhelmed by strategic clarity. Sumedh shares his view on the growing importance of the Risk Operations Center (ROC) and how AI is complicating risk profiles in new and unpredictable ways. He also reflects on the future of cloud security and why the market remains wide open for innovation, even as it becomes more crowded.

Beyond the tech, Sumedh opens up about his personal journey from Pune to Silicon Valley, how a threatened farm purchase changed his life, and why leadership is ultimately a game of time, trust, and communication. He leaves us with a powerful book recommendation, Nonviolent Communication by Marshall Rosenberg, which he credits with transforming his leadership style and helping him build stronger relationships across the board.

Are we thinking about risk in the right way or simply throwing money at the latest acronyms? And how do you build a meaningful legacy in cybersecurity without losing sight of the human side?

Join the conversation and let me know what resonated with you most.

Are we preparing people as quickly as we’re preparing machines? That’s the uncomfortable question at the heart of Coursera’s 2025 Global Skills Report, and the starting point for my conversation with Nikolaz Foucaud, Coursera’s Managing Director for EMEA.

As the UK jumps more than 20 spots in global skills rankings and countries like Singapore and Denmark widen the gap with lifelong learning cultures, we explore why mindset may be as important as access when it comes to reskilling for an AI-driven economy.

Nikolaz explains how the newly introduced AI Maturity Index reflects the growing urgency around workforce readiness and why governments and employers need to stop thinking in degrees and start investing in micro-credentials that reflect what learners and businesses actually need. We also unpack the gender gap in AI learning, the alarming lack of growth in cybersecurity skills, and why economic pressure often drives the highest levels of completion and success.

As institutions, employers, and individuals try to catch up with the pace of technological change, what will it take to build a learning culture that keeps momentum? And are we measuring the right things when we talk about readiness? Let me know what you think.

What happens when AI moves from experimental tool to everyday shopping assistant? In this episode of Tech Talks Daily, I’m joined by Liva Ralaivola, Head of the Criteo AI Lab, to unpack how artificial intelligence is reshaping the way we discover, compare, and purchase products online.

Speaking to me from the south of France, Liva shares insights from Criteo’s latest consumer research, revealing that 91 percent of shoppers expect AI-personalised recommendations within the next two years. We explore why that shift is happening so quickly, what it means for retailers, and the challenges of balancing innovation with transparency. From price comparisons to budget planning and dynamic creative generation, shoppers are already using AI tools in ways that few could have predicted even a year ago.

We also discuss the complexity of integrating AI into retail environments, where business constraints, stock levels, and customer expectations vary dramatically. Liva highlights how Criteo is tailoring deep learning models to improve relevance, optimise campaigns, and support ethical outcomes. He also explains why AI is not yet plug-and-play, and why collaboration between AI specialists and business teams is key to unlocking real value.

Looking ahead, Liva shares his thoughts on how data may evolve into a kind of personal currency, with users controlling what they share and how much personalisation they receive. From AI wallets to loyalty programs driven by interaction history, the landscape is changing fast—and businesses need to be ready.

So what’s your take? Are consumers ready to control their own data in exchange for more relevant experiences? And how should retailers rethink personalisation in an age of growing privacy expectations? Let me know your thoughts and join the conversation.