💬 “When I first started off with data science projects, I had this big poster up that said ‘if it makes money, it makes sense’. And every project, we were measuring it against that. When I look back, I realize that was a mistake and that ethos prevented us from seeing anything other than ROI. When we present the business case now, there’s around seven business benefit areas included, because financial KPIs alone don’t cut it anymore.”

This is a conversation with Frits Bussemaker and Ryan Moore

Frits is the Chair of the Institute for Accountability in the Digital Age and Ryan Moore is Head of Data and Analytics at Aiimi.

🎧 In this episode, Frits and Ryan discuss their experiences with talking about AI in the Enterprise. The challenges they have witnessed around different language, context and nuances that can derail a successful project. We talk about the lack of data literacy in the boardroom, how to think about an AI strategy and how to avoid hype. The conversation moved on to accountability and specifically accountability by design. Both Ryan and Frits talked about the need for self-governance by organisations on their AI projects. Ryan talked openly about how we used to think in a very binary fashion about projects and their return on investment potential and why he no longer feels like this. How he has changed his mind about what matters. I finished the episode by asking these experts what is the biggest misconception about AI in the Enterprise. I hope you enjoy hearing their answers.

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