Rich Edwards: Differentiating with Data in a World of AI episode artwork

EPISODE · Mar 7, 2024 · 58 MIN

Rich Edwards: Differentiating with Data in a World of AI

from Scouting for Growth · host Sabine VdL

On this episode of the Scouting For Growth podcast, Sabine VdL talks to Rich Edwards, CEO of Mindspan & former product leader for IBM Watson. He has a knack for demystifying complex topics like machine learning & getting to the heart of how companies can drive real business value. In our conversation, he shares a contrarian view — the biggest differentiation won’t come from algorithms but rather a company’s first-party data assets. KEY TAKEAWAYS Seeing where AI & machine learning was going, it wasn’t quite a mainstream adopted technology in 2017, but it clearly was going to be. Where was the interesting part of that to look at? A lot of the value was going to come from data, particularly first party data, that even now is sitting untapped. Eventually that search led me to the company I’m at now, Mindspan, which is a small business which I eventually bought. The information that they’re entrusted with (when used correctly) can be very, very valuable & allow them to provide very high value services to their customers. The trick is making that come together with the compliance element required in the banking and insurance sector. A lot of the organisations that we work with don’t have the technical skills to build it up which is where a lot of the differentiated value comes from. AI isn’t one thing. Science fiction has portrayed it as a monolithic thing that’s all knowing. In reality it doesn’t work like that, it’s component pieces that work together in a pipeline/flow handling things. It’s more like the summer intern, the person that comes to you from university who is diligent, eager, literate, can follow instructions, can write but doesn’t know anything about your business or background, & has no context or experience to base it from, but can answer simple questions. An important issue that we as a society are stumbling into with AI is similar to healthcare or the extension of credit: Areas where there’s a lot of personally identifiable information that’s out there that businesses have about the people they work with that could be misused or exploited. There’s a lot of regulation around healthcare information in the US that states clearly who’s allowed to possess that information & what they’re allowed to do with it. There’s a lot of stuff we haven’t even thought of yet with AI, for example facial recognition. Data is a valuable asset & requires a level of care around it that isn’t just protection but governance. BEST MOMENTS ‘I had no business being around AI, based on my background, but I was the guy that had been around IBM long enough & knew how to get things done. That afforded me the ability to be at the forefront of this.’ ‘For many use cases with generative AI, the differentiation between the providers is getting less & less & less. It’ll be a thing that you buy, but it won’t be a thing that’s going to make you stand out. ‘Anything we can do today is machine learning, anything we can’t do yet is AI, but the line between the 2 is blurry.’ ‘AI is a superpower that you can give to people that are most responsible for an interaction/experience that your customers have.’ ABOUT THE GUEST Rich Edwards is a veteran technology leader with over 20 years of experience working at the intersection of data, AI, and business strategy. As former product management lead for IBM Watson, Rich helped global banks and financial institutions leverage artificial intelligence to uncover growth opportunities and gain a competitive edge. He currently serves as CEO of Mindspan, a firm focused on helping community banks and credit unions transform through data-driven technologies. Under Rich's leadership, Mindspan turns client data into an operating asset to boost differentiation, create personalized customer experiences, and future-proof their business. With his extensive background in regulated industries like finance and healthcare, Rich understands the importance of building trust and maintaining rigorous data governance. He offers a unique perspective on AI ethics, data privacy, and the responsible use of generative models like ChatGPT. ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you’re interested in sponsoring the podcast, reach out to the team at [email protected]

What if AI isn’t your competitive advantage—and never will be? In this episode of Scouting for Growth, Sabine VanderLinden sits down with Rich Edwards, CEO of Mindspan and former product leader at IBM Watson, to dismantle one of the most persistent myths in AI-driven transformation: that algorithms are where differentiation lives. They’re not. Rich brings a refreshingly contrarian—and deeply practical—perspective shaped by decades at the intersection of machine learning, regulated industries, and real-world execution. His core belief is simple but uncomfortable: as AI becomes commoditised, your advantage won’t come from the model you buy—it will come from the data you already own and how responsibly you activate it. This conversation cuts through the hype. Rich explains why most organisations are sitting on vast reserves of underutilised first-party data, particularly in banking and insurance, and why those data assets—when governed correctly—can unlock entirely new levels of customer value, operational intelligence, and trust. You’ll hear why: Generative AI is rapidly becoming a utility, not a differentiator First-party data is the only asset competitors can’t copy AI is not a single “thing” but a pipeline of components working together Treating AI like an all-knowing brain is a category error The real risk isn’t AI itself—it’s poor data governance Rich uses a powerful analogy to reframe AI’s role: think of it less like a genius and more like a highly capable summer intern—fast, eager, scalable, but entirely dependent on the context, guardrails, and judgement you provide. From there, the discussion moves into territory many leaders are only beginning to confront: ethics, compliance, and responsibility. In sectors where personal and sensitive data is foundational, Rich argues that governance is not a blocker to innovation—it’s the enabler. Facial recognition, behavioural data, and predictive insights all raise questions that technology alone cannot answer. This episode is especially relevant for leaders asking: How do we stand out when everyone has access to the same AI tools? What does “responsible AI” actually look like in practice? How do we turn data into an operating asset—not a liability? Where should we invest when technical talent is scarce and change is accelerating? Rich also shares lessons from his own journey—how being the person who “knew how to get things done” inside IBM put him at the forefront of Watson, and why buying and leading Mindspan became a natural next chapter in focusing on impact over novelty. 🎧 If you’re an executive, founder, or investor who suspects that the AI arms race is missing the point—this episode will validate your instinct and sharpen your strategy. Because in a world where algorithms are everywhere, data stewardship, context, and trust are what will separate leaders from followers. And growth, as ever, belongs to those who understand the difference.

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This episode is 58 minutes long.

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This episode was published on March 7, 2024.

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On this episode of the Scouting For Growth podcast, Sabine VdL talks to Rich Edwards, CEO of Mindspan & former product leader for IBM Watson. He has a knack for demystifying complex topics like machine learning & getting to the heart of how...

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