AI Pathfinder for Private Equity Podcast
I'm on a mission to guide private equity from AI uncertainty to empowerment by building a network for successful AI adoption. It's giving me firsthand access to PE leaders and experts across the AI value chain.
AI Pathfinder for Private Equity Podcast
Miles Rowland: Why Every Portfolio Company Needs an AI Engineering Team
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In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd talks with Miles Rowland, Head of Data and AI at Searchlight Capital, a transatlantic mid-market private equity firm. Miles has built data analytics functions from scratch three times, at L.E.K. Consulting, at SHL, and now at Searchlight, where he joined in 2022 as the firm's first AI and data hire. The conversation covers why value creation planning is the natural entry point for AI work, the highest-impact use case Miles has found so far (hooking AI assistants directly into company data warehouses), the real but still unproven case for AI ROI, and why treating AI initiatives as IT projects is one of the biggest mistakes a firm can make.
Links
- Miles's LinkedIn
- Miles's Searchlight Capital profile
- Searchlight Capital
Takeaways
- Value creation planning is the natural starting point for AI and data work. Work backwards from the commercial outcomes a business wants in three years to the data, teams and technology needed to get there.
- Searchlight deliberately keeps its internal team lean. Miles is the fund's only dedicated AI and data hire across roughly 25 portfolio companies, and leans on consultants, contractors and permanent hires rather than building a large internal function.
- The highest-impact early use case: connecting AI assistants like Claude or ChatGPT directly to company data warehouses, turning a days-or-weeks wait for an analyst's answer into a couple of minutes of self-serve querying for non-technical executives.
- AI opportunities split into two buckets: personal productivity tools (fast to deploy, fast becoming table stakes) and agents that take on delegated work end-to-end, with humans reviewing periodically rather than doing the task themselves.
- "These are not IT projects." AI initiatives stall when a CIO or technology leader owns them alone. They need a functional leader, a CRO, COO or CFO, driving the actual change in how a team works.
- Most portfolio companies (aircraft parts, fibre broadband, nursing education, home healthcare) have never needed software engineering capability in-house, and building "AI engineering teams" is the next evolution of what data analytics teams became over the last decade.
AI Pathfinder Private Equity AI Strategy Meet-ups:
https://www.aipathfinder.co/private-equity-ai-events
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
