Rich Edwards: Differentiating with Data in a World of AI
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 â the biggest differentiation wonât come from algorithms but rather a companyâs first-party data assets.
KEY TAKEAWAYS
- Seeing where AI & machine learning was going, it wasnât 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 Iâm at now, Mindspan, which is a small business which I eventually bought.
- The information that theyâre 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 donât have the technical skills to build it up which is where a lot of the differentiated value comes from.
- AI isnât one thing. Science fiction has portrayed it as a monolithic thing thatâs all knowing. In reality it doesnât work like that, itâs component pieces that work together in a pipeline/flow handling things. Itâs more like the summer intern, the person that comes to you from university who is diligent, eager, literate, can follow instructions, can write but doesnât 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 thereâs a lot of personally identifiable information thatâs out there that businesses have about the people they work with that could be misused or exploited. Thereâs a lot of regulation around healthcare information in the US that states clearly whoâs allowed to possess that information & what theyâre allowed to do with it. Thereâs a lot of stuff we havenât even thought of yet with AI, for example facial recognition. Data is a valuable asset & requires a level of care around it that isnât just protection but governance.
BEST MOMENTS
âI 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.â
âFor many use cases with generative AI, the differentiation between the providers is getting less & less & less. Itâll be a thing that you buy, but it wonât be a thing thatâs going to make you stand out.
âAnything we can do today is machine learning, anything we canât do yet is AI, but the line between the 2 is blurry.â
âAI is a superpower that you can give to people that are most responsible for an interaction/experience that your customers have.â
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
There are over 140,000 FinTech ventures out there, including FinTechs, InsurTechs, HealthTechs, and WealthTechs. And the number keeps on changing every month. One statistic remains the same: 25% of these ventures have received investment and support from the financing world. 75% of these businesses still seek financing support from institutional and corporate investors alongside value-creating commercial collaboration opportunities with Global Fortune 500.
Through this podcast series, I would like to demystify the world of corporate venturing, including how corporations collaborate with growth ventures, how venture capitalists and corporate venture capitalists make investment and collaboration choices in ventures and give tech founders and entrepreneurs, the strategies, tactics, tools, and techniques to build, grow and scale their business by understanding how those with financing power think. So, listen in, share and comment as you see fit.