Tech Talks Daily

Tech Talks Network

If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change? Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways. Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses. Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords. We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make. Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments. Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas. New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

  1. قبل ٦ ساعات

    Qlik Connect: Ryan Welsh On Turning AI Into Business Outcomes

    What actually separates AI that delivers real value from AI that never makes it past the demo stage? Recording live from Qlik Connect, I sat down with Ryan Welsh, Field CTO of Generative AI at Qlik, to get a grounded, practitioner-led view of what it really takes to make AI work inside a business. While the industry has spent the past few years racing to experiment, build, and deploy new capabilities, many organizations are still struggling to turn that progress into capabilities people use every day. In our conversation, Ryan cuts through the noise and explains why so many AI initiatives fail. Not because the models aren't powerful enough, but because they're not designed to fit into real workflows. He shares why context is far more than just a buzzword and how getting the right data, in the right place, at the right time, enables AI to deliver meaningful outcomes. We also explore the growing shift toward agentic AI and the responsibilities that come with it. From designing systems that can act autonomously while remaining under control to understanding where humans need to stay involved, Ryan offers a practical view of how organizations can move forward without introducing unnecessary risk. There's also a refreshing honesty around where we are right now. After a wave of investment and expectation, many companies struggled to see immediate value from AI. But as Ryan explains, that period is changing, with more organizations finding ways to scale what works and move beyond isolated use cases. So, as businesses look ahead, what does it really take to move from experimentation to execution? And are we focusing too much on building more AI rather than the right AI for how our organizations actually operate? Join me for a candid conversation from the heart of Qlik Connect, and let me know your thoughts. Are you seeing AI deliver real outcomes in your business, or is it still stuck in the demo phase? Useful Links Connect with Ryan Walsh on LinkedIn Learn more about Qlik. Follow on Twitter, Facebook, and LinkedIn   Visit the May Sponsors of Tech Talks Network and learn more about the NordLayer Browser.

    ٢٦ د

  2. قبل ١٨ ساعة

    Qlik Connect: James Fisher On Turning AI Into a Business Strategy

    What does it really take to move beyond AI experimentation and build something a business can rely on? Recording live from Qlik Connect, I sat down with James Fisher, Chief Strategy Officer at Qlik, to unpack what's actually changing as AI moves from hype into real-world execution. Because while many organizations have spent the past few years exploring use cases and running pilots, the harder challenge is now in front of them. Turning that early momentum into something scalable, governed, and aligned with business outcomes.   In our conversation, James offers a candid view of where companies are getting this wrong. He describes a period of what he calls "AI madness," where everything became a potential use case, but very little translated into measurable value. Now, he sees a shift toward more focused, outcome-driven thinking, where success depends on understanding the user, the data, and the specific problem being solved. One of the most thought-provoking moments comes when James challenges the idea of having an AI strategy at all. Instead, he argues that AI should be embedded directly into the broader business strategy, shaping how decisions are made, how processes operate, and how organizations compete. We also explore the realities that many businesses are only just beginning to face. The complexity of data access and governance, the growing pressure around cost and sustainability, and the risks of vendor lock-in in a rapidly evolving AI ecosystem. James shares why openness and flexibility are becoming critical, and why some of the same patterns seen in previous technology waves are starting to repeat themselves. So as organizations look ahead to the next 12 to 24 months, what will separate those that successfully operationalize AI from those that remain stuck in cycles of experimentation? And are we focusing too much on the technology, and not enough on the business problems it's meant to solve? Join me for a grounded and strategic conversation from the heart of Qlik Connect, and let me know your thoughts. Are you still experimenting with AI, or are you starting to embed it into the core of how your business operates? Useful Links Learn more about Qlik. Follow on Twitter, Facebook, and LinkedIn Visit the May Sponsors of Tech Talks Network and learn more about the NordLayer Browser.

    ٢٤ د

  3. قبل يوم واحد

    How Glean Is Securing The Next Wave Of AI Agents In The Enterprise

    What happens when your AI agents start making decisions faster than your security team can even see them? In this episode, I sit down with Sunil Agrawal, Chief Information Security Officer at Glean, to unpack a shift already underway in enterprises. With predictions that 40 percent of enterprise applications will include autonomous AI agents by the end of 2026, we are moving from human-led workflows to machine-to-machine interactions at a scale most organizations are not fully prepared for. Sunil brings a rare perspective, blending more than 25 years of cybersecurity experience with an inventor's mindset shaped by over 40 patents. What stood out to me in our conversation is how quickly the traditional security model is becoming outdated. As he explained, "autonomous agents break those assumptions because they operate across tools, varying permissions and data sources with alarming speed and autonomy." This creates what he calls the "autonomy gap," in which the CIO's drive for speed collides with the CISO's need for visibility and control. We explore how that tension is playing out in real organizations today, and why so many are already falling behind. Nearly half of businesses still lack the AI-specific controls needed to prevent untraceable incidents, and the risks are not always what you might expect. Sunil argues that the first major rogue-agent incident is unlikely to be a malicious attack. Instead, it will come from confusion: a well-intentioned system taking the wrong action in the wrong context, with consequences that ripple across the business. The conversation then turns practical. Sunil breaks down his AWARE framework, a structured way to introduce real-time guardrails that evaluate intent, context, and risk before an agent takes action. Rather than relying on static policies, this approach focuses on continuous runtime enforcement, where systems are constantly assessed based on behavior rather than assumptions.   What I found particularly valuable is how this moves beyond theory into something leaders can act on today. From starting with tightly scoped use cases to investing in full observability, this episode offers a clear roadmap for balancing innovation with accountability. As Sunil put it, organizations that succeed will not be the ones that move fastest, but the ones that prove trust at scale.   So how do you embrace the productivity gains of autonomous AI without opening the door to invisible risk, and are your current security models ready for a world where the "user" is no longer human? Useful Links Connect with Sunil Agrawal on LinkedIn Learn more about Glean Follow Glean on LinkedIn Visit the Tech Talks Network Sponsor NordLayer Browser

    ٣٣ د

  4. قبل يومين

    Qlik Connect: Mike Capone On Agentic AI and Turning Insight Into Action

    What does it actually take to move AI from experimentation into something a business can depend on every single day? Recording live from the show floor at Qlik Connect in Florida, I sat down with Qlik CEO Mike Capone to cut through the noise and get to the reality behind enterprise AI in 2026. Because while the headlines are still dominated by rapid innovation and new capabilities, many organizations are quietly facing a different challenge. They are struggling to turn AI ambition into measurable outcomes. In our conversation, Mike shares what he is hearing from customers around the world and why so many companies remain stuck in cycles of pilots and proof of concepts. We talk about the growing pressure from boards and leadership teams to move faster, and why that urgency is often leading to what he calls a "ready, fire, aim" approach that fails to deliver real business value. We also explore one of the biggest themes emerging at Qlik Connect this year. The shift toward agentic AI. But rather than focusing on the hype, Mike breaks down what this actually means inside a real enterprise workflow, where insights are not just generated but turned into decisions and actions. He also explains why getting the data foundation right is no longer optional, and how poor data quality can quickly turn AI from an opportunity into a risk. From data trust and governance to the challenges of operating across increasingly complex regulatory environments, this episode offers a clear view of what it takes to build AI systems that are reliable, scalable, and grounded in real business context. So as organizations look ahead to the next 12 to 24 months, what will separate those that successfully operationalize AI from those that remain stuck in pilot mode? And are we focusing too much on building more AI, rather than building better AI? Join me for a candid conversation from the heart of Qlik Connect, and let me know where you stand on this shift. Are you seeing real progress, or are the same challenges holding things back?

    ١٩ د

  5. قبل يومين

    Twilio: Demystifying Model Context Protocol (MCP) And Real-World AI Deployment

    How are brands supposed to deliver AI-powered customer experiences when their data is scattered across systems that were never designed to work together? In this episode, I sit down with Peter Bell, VP EMEA Marketing at Twilio, to unpack one of the most important AI topics that still does not get enough attention outside technical circles, Model Context Protocol, or MCP. While many conversations about AI remain stuck on model hype, chatbots, and the latest product launch, Peter brings the discussion back to something far more practical. If businesses want AI to deliver real outcomes in customer service, marketing, and brand engagement, they first need a reliable way to connect large language models to the right data, in the right systems, with the right controls in place. That is why this conversation matters. Peter explains how MCP could become one of the biggest unlocks for enterprise AI by creating a standard way for LLMs to access information across fragmented tools like CRM platforms, marketing systems, and other business applications. Instead of forcing every company to build custom integrations from scratch, MCP creates a more consistent path for connecting models to the context they need. For me, that is where this episode really earns its place, because it moves the AI conversation away from vague ambition and toward the plumbing that actually makes useful AI possible. We also talk about why first-party data remains so important, especially as businesses try to create customer experiences that feel seamless, personal, and trustworthy. Peter makes the point that public models may be useful for general knowledge, but brands cannot rely on generic internet-trained systems to solve precise business problems. If you want AI to support travel bookings, customer service, or commerce journeys, you need specific data, strong governance, and a much clearer understanding of the problem you are trying to solve. That sounds obvious, but it is still where many AI projects fall apart. Another part of our conversation focuses on trust, which feels especially relevant right now. From scams and impersonation to consumer fatigue and poor automation, brands are under pressure to move faster without losing credibility. Peter shares how Twilio is thinking about branded calling, RCS, conversational AI, and voice experiences that feel modern without becoming intrusive or robotic. We also discuss why too many companies still automate too broadly, too quickly, without defining the actual use case first. What I enjoyed most here was Peter's balanced view. He is optimistic about where AI is heading, but he is also realistic about the work still required to get there. This is not a conversation about AI magic. It is about data access, governance, trust, brand experience, and the standards that may quietly shape the next phase of AI adoption far more than the flashy headlines. So if you have been hearing more people mention MCP and wondering why it matters, or if you are trying to understand what needs to happen before enterprise AI can move from promise to practical value, this episode will give you plenty to think about. Is Model Context Protocol the missing layer that finally helps AI connect with the real world of business data?

    ٣٥ د

  6. قبل ٣ أيام

    Invisible Technologies On Building AI Around Real Workflows, Not Hype

    What does it actually take to make AI work inside a real business, where messy data, human judgment, and operational risk all collide? In this episode, I sit down with Matt Fitzpatrick, CEO of Invisible Technologies, to talk about why the biggest barrier to enterprise AI is not model quality, it is everything that comes before the model ever gets to work. Since stepping into the CEO role in January 2025, Matt has moved quickly, raising $100 million and expanding Invisible's footprint across major cities including New York, San Francisco, DC, Austin, London, and Poland. But this conversation is far less about headlines and far more about what happens in the trenches of AI adoption, where companies are trying to move from pilots and PowerPoint promises to systems that actually deliver results. A huge theme throughout our discussion is data readiness. Matt makes a compelling case that most businesses are still dealing with fragmented systems, inconsistent records, and information spread across disconnected tools. That reality makes it incredibly hard to deploy AI in a way that creates trust and value. We talk about SwissGear, where Invisible used its Neuron platform to clean and structure 750 scattered tables in just one week, a task that could have taken a large engineering team months or longer. We also discuss why that kind of work matters so much, because once the data foundation is fixed, companies can start making better decisions on forecasting, operations, and planning with a level of confidence that simply was not there before. We also spend time on Invisible's human-in-the-loop approach, which I think will resonate with a lot of listeners trying to cut through the noise around job displacement and agentic AI. Matt argues that the real opportunity is not replacing people, but giving them better tools to handle repetitive work while preserving room for human expertise, judgment, and oversight. He shares examples from commercial credit workflows, healthcare, and sports analytics, including a fascinating story about the Charlotte Hornets using AI to turn broadcast footage into detailed tracking data. What stood out to me was how practical his perspective felt. This was not theory. It was about building systems around how organizations actually work, rather than expecting businesses to reshape themselves around a generic AI product. Another part of the conversation that deserves attention is governance. As boards rush to understand agentic AI, Matt explains why trust, standards, and responsible deployment are now driving buying decisions just as much as raw capability. We talk about privacy in healthcare, the risks of scaling autonomous systems without mature governance, and why enterprise adoption still trails consumer AI by a wide margin. That gap between excitement and execution may be one of the most important stories in AI right now. If you are wondering why so many AI projects never make it into production, or what it will take for enterprise AI to finally deliver on its promise, this episode is packed with insight. It is a conversation about data, deployment, governance, and the role humans will continue to play as AI becomes part of everyday business operations. After listening, I would love to know where you stand, is the future of AI really about bigger models, or is it about making AI fit the messy reality of how work gets done?

    ٢٩ د

  7. قبل ٤ أيام

    Willow On How AI Is Changing The Way Buildings Operate

    In this episode, I speak with Bert Van Hoof, CEO of Willow, about how AI is starting to reshape the built world in ways that go far beyond smart dashboards and efficiency reports. Bert brings decades of experience from the front lines of digital infrastructure, including his time at Microsoft, where he helped create Azure Digital Twins and Smart Places. Today at Willow, he is focused on a much bigger idea, using AI to help buildings, campuses, hospitals, airports, and other complex environments operate with greater intelligence, lower waste, and better outcomes for the people who rely on them every day. One of the most interesting parts of our conversation is how Bert explains the shift from passive building software to active management systems. For years, many digital twin and smart building tools were good at showing what had already happened. But operators do not need another screen full of charts. They need systems that can connect live data, static records, spatial context, and operational history to help them make better decisions in real time. That is where Willow comes in, creating a digital foundation where AI can reason across everything from HVAC and air quality to occupancy, refrigeration, maintenance history, and even energy usage patterns. We also unpack why this matters right now. Energy costs remain under pressure, sustainability goals are getting harder to ignore, and many organizations are still stuck with fragmented systems that do not talk to each other. Bert shares how AI can help move building teams from reactive maintenance to predictive performance, spotting issues earlier, cutting downtime, reducing waste, and extending the life of expensive assets. He also explains why the future of building operations will depend on a stronger data foundation, operational AI copilots, and systems that can support an aging workforce while making these roles more appealing to the next generation. What stood out for me was how practical this all became once we moved past the buzzwords. This was not a conversation about futuristic hype. It was about real examples, from occupancy-based HVAC control in offices and campuses to leak detection in schools, vaccine refrigeration monitoring, and hospital environments where downtime can carry enormous consequences. Bert makes a strong case that buildings are no longer just static structures. They are living operational environments filled with signals, systems, and opportunities that have been hiding in plain sight. We also touch on the wider picture, including what Bert learned from smart cities and energy grid modernization, and how those lessons now apply to commercial real estate, airports, research labs, and higher education campuses. There is a real sense that the physical world is entering a new chapter, one where AI starts to bridge the gap between digital intelligence and real-world action. If you have ever wondered what AI looks like when it leaves the screen and starts improving the places where people work, heal, travel, learn, and live, this episode will give you plenty to think about. As always, I would love to know what you think, are buildings finally ready to become truly responsive, and what opportunities or risks do you see ahead?

    ٤٩ د

  8. قبل ٥ أيام

    Blumberg Capital On What Investors Really Want From AI Founders Now

    What does it really take to build the next generation of AI companies when the hype around scale begins to fade and real-world impact takes center stage? In this episode, I sit down with David Blumberg, founder and managing partner at Blumberg Capital, to unpack what he believes will define the next wave of AI startups. With a track record that includes being the first investor in companies like Nutanix, Braze, and DoubleVerify, David brings a perspective shaped by decades of identifying breakout innovation early. But what stood out most in our conversation was his belief that 2026 marks a turning point where intelligence moves beyond experimentation and becomes operational. We explore what that shift actually means in practice. David explains how AI is evolving from systems that generate insights into systems that take action, and why that distinction matters for founders, investors, and enterprise leaders alike. He shares how the most compelling startups today are not simply layering AI onto existing products, but embedding it deeply into workflows across industries like finance, security, and supply chain. These are companies built on proprietary data and real operational context, designed to make decisions with precision rather than simply process information. Our conversation also challenges some widely held assumptions about success in the AI space. David makes it clear that scale alone will not separate winners from the rest. Instead, the focus is shifting toward accuracy, reliability, and domain expertise. Founders who have lived the problems they are solving, rather than approaching them from the outside, are far more likely to build something defensible and lasting. It is a subtle shift, but one that could redefine how value is created in the years ahead. There is also a broader discussion about where investment is flowing and why. With the vast majority of companies Blumberg Capital now evaluates being rooted in AI, the bar for differentiation is rising fast. David offers insight into what his team is really looking for in founders entering this next cycle, and how startups can stand out in an increasingly crowded field. So as AI moves from promise to execution, and from experimentation to real-world outcomes, the question becomes harder to ignore. Are we ready to rethink how we measure success in the AI era, and what kind of companies will truly earn their place at the top?

    ٤٨ د
مشاهدة الكل (٢ ألف)

المضيفون والضيوف

٥
من ٥
‫١٩٨ من التقييمات‬

حول

If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change? Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways. Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses. Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords. We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make. Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments. Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas. New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

المعلومات

  • قناة
    Tech Talks Network
  • صناع العمل
    Neil C. Hughes
  • سنوات النشاط
    ٢٠١٥ - ٢٠٢٦
  • الحلقات
    ٢ ألف
  • التقييم
    ملائم
  • حقوق النشر
    © Neil C. Hughes - Tech Talks Daily 2015
  • موقع البرنامج على الويب
    Tech Talks Daily

المزيد من Tech Talks Network

قد يعجبك أيضًا