Tech Talks Daily

What happens when cybercrime becomes as easy to access as a subscription service, and what does that mean for every business connected to the internet today?
In this episode, I sit down with SentinelOne AI and Cloud Security Evangelist Chris Hosking to unpack a shift that feels both inevitable and deeply unsettling. The rise of what Chris describes as an AI threat market is changing the rules of engagement.
Cybercrime is no longer limited to highly skilled operators working in isolation. Instead, it has evolved into a thriving ecosystem where tools, services, and even AI-powered attack kits are bought and sold with alarming ease. As Chris explains during our conversation, "cyber crime is quite an ecosystem… the dark web has always been a place for cyber criminals to meet and to sell their wares."
We explore how AI has accelerated this shift, lowering the barrier to entry to the point where attacks can be launched for as little as £35. That democratization of cybercrime is already having real-world consequences.
Chris shares how individuals without deep technical expertise are now able to orchestrate sophisticated attacks using AI assistance, and why that surge in accessibility is driving both the volume and impact of cyber incidents. It also reframes a common misconception. Smaller businesses are not flying under the radar.
 In fact, many are being targeted precisely because of weaker defenses, with attacks increasingly automated and opportunistic.
The conversation also moves into more complex territory, where organized cybercrime and nation-state activity begin to overlap.
Chris highlights how governments and criminal groups are drawing from the same AI marketplaces, blurring the lines between financial motivation and geopolitical intent. The implications stretch far beyond corporate risk, touching on critical infrastructure and everyday services that people rely on. It raises a difficult question about preparedness in a world where attacks are faster, more frequent, and harder to predict.
At the same time, there is a practical thread running through this discussion. Chris challenges the instinct to immediately invest in more tools and instead encourages leaders to look inward first.
 From improving basic security hygiene to using AI to reduce manual workload and noise, there are tangible steps organizations can take right now. The goal is not perfection, but resilience in an environment where, as Chris points out, incidents are becoming a regular occurrence rather than a rare event.
This episode offers a clear-eyed look at where cybersecurity is heading, without the hype or fear-driven narratives. It is a conversation about scale, speed, and the uncomfortable reality that the threat landscape has changed in ways many organizations are still catching up with.
So as AI continues to reshape both innovation and risk, how prepared is your organization for a world where anyone can launch an attack with a few prompts and a subscription?
Useful Links
SentinalOne Blog
Connect with Chris Hosking
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What happens when the race to deploy AI starts to outpace the ability to control it?
In this episode of Tech Talks Daily, I sit down with Ken Englund from EY to unpack findings from the latest 2026 Technology Pulse Poll, and the conversation quickly moves beyond theory into something many leaders will recognize from their own organizations. There is a growing tension between speed and oversight, a "velocity paradox" Ken describes, in which businesses are accelerating AI adoption while governance struggles to keep up.
The numbers behind that story are hard to ignore. A large majority of tech leaders are prioritizing speed to market over careful vetting, while more than half of AI initiatives are happening outside formal IT oversight. For anyone responsible for security, compliance, or risk, that gap raises immediate concerns. But as Ken explains, it is not as simple as labeling this as reckless behavior. Much of this activity is driven by real innovation happening closer to the business, where teams are experimenting, solving problems, and creating value quickly.
We spend time breaking down what that looks like in practice. From the rise of shadow AI tools to the growing risk of sensitive data exposure, there is already evidence that the consequences are beginning to show. At the same time, nearly every executive surveyed sees autonomous AI as central to future competitiveness, which means slowing down is not really an option either.
One of the most useful parts of the conversation focuses on what organizations can actually do about it. Ken shares practical insight into why architecture matters more than ambition, how companies should think about optionality in a fast-moving AI ecosystem, and why observability is becoming a missing layer in many deployments. We also get into the reality of measuring AI value, where the conversation is shifting from promised returns to the often-overlooked cost side, including token usage and uncontrolled spending across departments.
There is also a broader discussion around leadership and culture. Governance frameworks may exist on paper, but the real challenge lies in operationalizing them across a business that is already moving at speed. Add in geopolitical pressures, evolving regulations, and the complexity of deploying AI globally, and it becomes clear why many organizations feel overwhelmed.
This episode is not about slowing innovation down. It is about understanding where things are breaking, what leaders are getting wrong, and how to build a path forward that balances progress with accountability.
So, as AI budgets continue to rise and autonomous systems become part of everyday operations, how will your organization close the gap between ambition and control, and are you already further along that path than you realize? 
Useful Links
Ernst & Young Technology Pulse Poll
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What happens when your financial advisor is no longer limited by time, availability, or even geography, but is always there when you need them, ready to listen, respond, and guide you in real time?
At Citi's announcement at Google Cloud Next 2026, I sat down with Joe Bonanno, Head of Wealth Intelligence, and Karolina Belwal, Global Head of Data Intelligence and Automation for Citi Wealth, to unpack what could become a defining shift in how wealth management is delivered.
The launch of Citi Sky, built in partnership with Google Cloud and powered by Google DeepMind, is not another digital feature layered onto an existing app. It signals a move toward an always-on, conversational, and highly personalized experience that blends human expertise with AI-driven intelligence.
What stood out in our conversation was how grounded this initiative is in real-world client behavior. Joe explained how traditional engagement models, whether phone calls, emails, or app notifications, often feel disconnected from what clients actually need in the moment.
Life events, changing market conditions, and personal priorities rarely align with scheduled interactions. Citi Sky attempts to close that gap by being present at the exact moment a client has a question, whether that is late at night, between meetings, or during a moment of financial uncertainty.
Karolina brought that point to life with a simple but relatable example. As a working parent, she highlighted how difficult it can be to connect with an advisor during the day. Citi Sky allows clients to engage on their own terms, asking questions when it suits them, in a way that feels natural and responsive. That shift from scheduled interaction to on-demand conversation could change how people think about financial guidance altogether.
Under the hood, the technology is just as ambitious. Built on Gemini models through Google's enterprise agent platform, Citi Sky combines real-time voice, video, and multilingual capabilities into a single experience. But what makes it interesting is how it moves beyond reacting to questions.
The system can anticipate needs, surface insights, and even guide advisors by identifying which clients may require attention during market events. In Joe's words, it becomes a teammate, one that can scale expertise across hundreds of clients while maintaining a sense of personalization.
There is also a broader implication here for the industry. Wealth management has long relied on relationships built over time, supported by human intuition and experience. Citi is not replacing that model, but it is extending it. Advisors are still central, yet their reach is amplified by AI that handles routine interactions, summarizes conversations, and provides context before the next client meeting even begins.

Of course, this raises familiar questions around trust, governance, and the role of AI in financial decision-making. Citi is clearly aware of that tension, emphasizing secure data foundations, regulatory compliance, and the importance of embedding its Chief Investment Office's institutional knowledge directly into the system. This is not positioned as a generic AI assistant, but as a reflection of Citi's own expertise, delivered through a new interface.
What I found most compelling, though, was how both Joe and Karolina kept returning to the human side of the story. Yes, this is about agentic AI and advanced models. Still, it is also about reducing friction, improving access, and helping people answer a simple but powerful question: Am I financially okay?
As Citi Sky rolls out to Citigold clients in the U.S., it will be fascinating to see how customers respond and how competitors react. If this model gains traction, it could reshape expectations far beyond wealth management and into every corner of financial services.
As we move into the next phase of AI-driven client engagement, are we ready to trust a system that listens, understands, and acts on our financial lives in real time, and how much of that responsibility are we willing to share?
Useful Links
Learn More About Citi Sky, the AI-Powered Member of the Citi Wealth Team.
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Are businesses really making progress with AI, or are many still stuck using it for the digital equivalent of making phone calls on a smartphone?
In this episode, I sit down with Alison Kay, VP / Managing Director AWS UKI, to unpack what is actually happening behind the headlines of AI adoption across the UK.
On paper, the numbers look strong. Around 64% of UK businesses are now using AI, a sharp rise from the previous year. But when you look closer, the story shifts. Only one in four organizations have moved into more advanced use cases, where real productivity gains, efficiency improvements, and innovation start to show up in meaningful ways.
So what is holding everyone back?
In our conversation, Alison shares insights from AWS research and her work with organizations ranging from major enterprises like Barclays and the BBC to fast-moving startups. We explore why skill shortages are slowing progress, why many companies struggle to move beyond basic use cases, and how governance and trust are becoming central to scaling AI responsibly.
We also spend time breaking down the rise of agentic AI, a term that is starting to appear everywhere. Instead of simply generating answers, these systems are beginning to take action, writing code, testing software, and working alongside humans to dramatically accelerate delivery timelines. Alison shares a powerful example where a project that might have taken 40 engineers over two years was completed by six engineers in just 76 days with the support of AI agents.
Along the way, we look at real-world examples from companies like Trainline and Evri, showing how AI is already reshaping customer experience and operational efficiency in ways that go far beyond theory.
This episode is a must-listen for business leaders trying to understand where AI is delivering real value today, where the biggest gaps still exist, and how to move from experimentation to meaningful transformation.
So if your organization is already using AI, the real question becomes this, are you using it to improve what you already do, or are you ready to rethink how your business operates entirely?
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Connect with Alison Kay
Unlocking the UK's AI Potential" report.
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What if one of the most influential figures in modern technology had almost ignored the opportunity that would define his career?
In this episode, I sit down with Werner Vogels, Chief Technology Officer at Amazon, to explore the story behind Amazon Web Services as it marks its 20th anniversary, and how a near-dismissed phone call turned into a front-row seat to one of the biggest shifts in computing history.
Werner takes me back to the early days when Amazon was still seen as "just a bookstore," and shares what he discovered when he first stepped inside what he calls Amazon's "technology kitchen." What he found was a company solving problems at a scale that commercial software simply could not handle, forcing them to build everything themselves. That mindset would go on to shape everything from Dynamo to the foundations of modern cloud infrastructure.
We also unpack the thinking behind one of the most important shifts in enterprise technology, the move from upfront licensing to pay-as-you-go. It sounds obvious now, but at the time it challenged how the entire industry operated, giving businesses the ability to experiment, scale, and take control of their own costs in ways that were not possible before.
Looking ahead, Werner offers a refreshing perspective on AI and what he describes as a developer renaissance. While many headlines focus on replacement, he sees AI as a tool that amplifies human capability, placing even greater importance on curiosity, ownership, and collaboration. It is a reminder that while tools will continue to evolve, responsibility and decision-making still sit firmly with the people using them.
This episode is a must-listen for anyone building, leading, or investing in technology. It connects the dots between past, present, and what comes next, showing how today's AI wave echoes the same patterns that shaped the cloud revolution.
So as we look toward the next era of computing, the question is simple, are we ready to think at the scale required to build what comes next?
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