3350: Make the Problem the Purpose: Rethinking Innovation with Colin Scott of Innventure
Is innovation failing because we're starting in the wrong place? In this episode of Tech Talks Daily, I'm joined by Colin Scott, Senior Vice President of DownSelect at Innventure, to challenge the default tech-first mindset that dominates R&D and corporate innovation. Instead of asking what a technology can do, Innventure flips the question: what real-world problem needs to be solved? It's a market-first philosophy, not a pitch deck philosophy, and it's led to some fascinating outcomes. Colin walks us through Innventure's DownSelect process, a trademarked, multi-stage approach for evaluating early-stage innovation through the MATCH framework: Market, Advantage, Timeline, Capital, and High Value. The result? Out of over 150 evaluated opportunities, just four companies have cut, including PureCycle Technologies, AeroFlexx, and Rafinity. That 5 percent conversion rate isn't a bug; it's a feature. It's the design. Colin explains why prioritising unmet strategic needs over flashy prototypes leads to better long-term outcomes for customers, partners, and the technology itself. We also explore how Innventure fosters creative tension inside teams through something they call "Tigger Time," a framework that assigns roles for optimists and sceptics to surface risks and possibilities early in the process. It's a smart way to turn internal disagreement into forward momentum. So, how do you approach innovation in your organisation? Are you starting with the technology or the need? Please let me know your thoughts after listening.
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3349: IBM Consulting on Agentic AI and the Reinvention of Business Processes
When AI enters the boardroom, it tends to arrive with big promises: productivity, automation, efficiency. But for Francesco Brenna, Global Leader of AI Integration Services at IBM Consulting, the real opportunity isn’t just faster workflows—it’s rebuilding how business gets done from the ground up. In this episode, recorded in the heat of a New York summer, Francesco joined me to unpack what agentic AI really means for enterprise leaders and why “doing AI right” is about more than picking the latest model. We began by breaking down the term agentic AI, which Francesco defines as the shift from passive assistants to intelligent agents that can actually execute work, not just suggest how to do it. That might sound subtle, but it’s a huge leap. And it’s not one companies can take by simply layering AI on top of broken or inefficient processes. Instead, IBM is helping its clients rethink entire workflows, starting not with the tech stack, but with the business outcome. Francesco explains why data readiness is still the number one challenge. While many companies have talked about modernizing their data foundations, few have done it in a way that supports grounded, contextual, reliable AI agents. He introduces the idea of “data products” as a way to anchor agent behavior in the right context, feeding into IBM’s three-layer model: user experience, orchestration, and data. We also explored the growing role of standards like Model Control Protocol (MCP), which could make secure integration with legacy systems more realistic at scale. Francesco highlights how IBM is addressing access control, security, and governance to ensure agentic systems are not only powerful but also trustworthy and accountable. There’s plenty here for enterprise leaders wondering how to move AI projects out of pilot mode. From real examples in customer service, insurance, and pharma, to IBM’s internal strategies for employee upskilling, Francesco shares what early success looks like and why hackathons, hands-on experience, and human-centered design are critical.
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3348: How Twilio Is Redefining Voice AI for Real-World Customer Support
Voice has always been a powerful way to connect with customers, but until recently, voice AI struggled to deliver the kind of seamless experience we associate with great service. That is starting to change. In this episode, I catch up with Sam Richardson from Twilio to discuss the renewed momentum behind voice AI and what it means for the future of customer experience. Sam explains why voice is gaining relevance again. It is not just because the technology has improved, but because customers still prefer natural conversations when solving problems. According to Twilio’s research, more than half of customers want to know when they are speaking to a bot, while nearly half do not mind as long as their issue gets resolved. That balance is important. It is not about deception. It is about resolving problems efficiently without losing the human touch. We talked about the balance between automation and empathy. Sam emphasizes the importance of escalation paths. When a customer is frustrated, repeating themselves, or directly asking for a person, they should be able to reach one. Without that, companies risk creating what he calls “reality privilege,” where only premium customers receive human support. Voice AI should serve everyone, not create unfair divides. Sam also shared how Twilio is helping businesses adapt without replacing everything. Using API-based tools, companies can integrate voice AI into existing systems. That flexibility matters, especially since 96 percent of Twilio customers are building custom customer experience solutions to fit their specific environments. This is especially relevant in industries like hospitality, retail, and automotive. The early results are promising. Some companies are seeing a 60 to 70 percent increase in call containment and a noticeable drop in contact volume. Customer satisfaction scores have not suffered. Still, Sam is realistic. Long-term impact takes time to measure. The key is testing thoroughly, choosing the right solution, and tracking how customers actually feel.
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3347: Bitsight on the Hidden Risks Inside Global Supply Chains
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
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3346: How Nexthink Is Rethinking IT Support with Proactive, AI-Driven DEX
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.
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