AI Pathfinder for Private Equity Podcast

AI Trends: Closing the Value Gap with Attercop | Part 1 of 3 

Billions have gone into AI experiments, yet for most businesses the return hasn't shown up in the P&L. 

This is the first of three conversations exploring why that gap exists and what it takes to close it. I'm joined by Tiffany Willcox and Graeme Cox from Attercop, an AI consultancy that works with PE-backed businesses, who share the lessons and frameworks from their work.

Key Topics

• The widening gap between AI spending and returns
• Importance of data foundations for AI success
• Challenges in scaling AI from pilot to production
• Business transformation required for AI value
• The concept of AI boost for practical implementation
• Private equity's role in AI adoption
• Technical and strategic hurdles in AI projects
• Measuring AI impact on business metrics

Takeaways

• Most enterprise AI pilots deliver little to no measurable impact without proper infrastructure.
• Closing the gap requires focusing on data quality, business value, and scaling processes.
• AI initiatives often fail due to poor planning, data issues, and lack of business transformation.
• Private equity firms can leverage AI as a repeatable value creation tool.

Links

Tiffany Willcox
Graeme Cox

Attercop website

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 [email protected]

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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.

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In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd brings a venture capital perspective into the AI Operator series, speaking with Ties Boukema, Head of Data Tech and AI at Dawn Capital, one of Europe's leading B2B software investors. Ties shares his path from law and statistics through five and a half years at Google, including a stint in Google Health, into building Dawn's data and AI function from scratch. The conversation covers Rolodex, Dawn's proprietary relationship-intelligence platform and why buying beats building except when nothing comparable exists.

Takeaways

• Relationship intelligence, not sourcing models, became Dawn's highest-value AI use case. Mapping WhatsApp, calendar and work-history data has directly won deals, including preempting a competitive round against Sequoia.
• Buy software wherever possible. Only build in-house when nothing comparable exists and the edge is core to the business. Rolodex took roughly 18 months to prove its value.
• AI has cut Dawn's DDQ turnaround from weeks to as little as 24 hours, and removed hundreds of comment threads from quarterly reporting.
• Deliberate no-AI zones still matter. Original thinking and hard problems deserve time away from the tool, not a prompt.
• PE culture and engineering culture clash, which is why the AI operator role rarely works well when split across internal projects and portfolio support.

Links

• Ties's Dawn Capital profile
• Ties's LinkedIn
• Ties on the Handelsblatt Disrupt Podcast: Listen on Spotify
• Forbes: How Dawn is using AI to supercharge relationships

AI Pathfinder Private Equity AI Strategy Meet-ups: 

https://www.aipathfinder.co/private-equity-ai-events

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Steve Budd speaks with Zuzana Manhart, Portfolio Manager for Data and AI at CBPE, about how the AI operator role has grown from solving narrow technical problems to shaping strategy across a portfolio. Zuzana explains where quick wins are landing, why AI features bolted onto familiar tools keep getting ignored, what's really holding agents back, and what to look for when hiring your first AI operator.

Takeaways

• The AI operator job has grown from technical fixer into a strategic role across the portfolio
• Quick wins like transcription and chat automation land first, the harder stuff comes later
• AI bolted onto tools people already use tends to get ignored
• Agents are stuck less on model capability and more on visibility into what they're actually doing
• Hire someone technical, then let them own the roadmap from the data up

Links

• Zuzana's LinkedIn
• Zuzana's CBPE profile
• CBPE

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 [email protected]

In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd speaks with Aris Valtazanos, Head of Data and Analytics at Oakley Capital, about navigating AI across a diverse portfolio of 30-40 companies. Aris shares his journey from a PhD in robotics at the University of Edinburgh through nearly six years at Quantum Black to his current role supporting founder-led businesses in tech, education and consumer sectors. The conversation explores why bespoke sector-specific AI solutions are creating more value than cross-cutting tools, the critical importance of finding small self-contained problems to avoid becoming a bottleneck, and why firms must start with business pain points rather than asking "where can we use AI?"

Takeaways

• Bespoke sector-specific AI solutions are creating more value than cross-cutting tools like marketing automation
• Avoid becoming a bottleneck by focusing on small self-contained problems that can scale across the portfolio
• Start with the biggest business pain points first, then determine if AI is the right solution
• The gap between what AI can do and where companies actually are has widened despite technological progress
• Successful adoption requires C-suite vision meeting ground-level champions in the middle

Links

Aris's LinkedIn

Aris's Oakley Capital profile

Oakley Capital

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 [email protected]

In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd speaks with John Gunn, Lead Data Science and AI at IK Partners, about building the AI operator role from scratch. John shares his journey from mechanical engineering through AI consultancy into private equity, where he now works across 30-40 portfolio companies as a specialist on the operating team. The conversation explores the untapped potential of second-order data relationships in due diligence, the importance of formalizing workflows to survive platform transitions, and why the current gap between AI-mature and AI-immature companies creates a compounding advantage for those who move decisively now.

Takeaways

• Second and third-order data relationships are massively underexplored in due diligence
• Generative Engine Optimization (GEO) is the new SEO for competitive advantage
• The current maturity gap creates a compounding first-mover advantage window
• Formalizing workflows through agents creates transferable IP across platforms
• AI coding agents have quadrupled technical productivity in three months

Links

• John's LinkedIn
• John's IK Partners profile
• IK Partners

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 [email protected]

Summary

David Whitcombe (Founder & Managing Director, Data Vision Services) explains what it takes for private equity-backed businesses to move beyond “AI as a chatbot” and start embedding it into day-to-day workflows. We discuss why the real bottlenecks are people, unstructured data, and governance, and where the most immediate commercial upside sits, especially around revenue retention, churn, and pricing. David also makes the case that what used to be “exit prep” is increasingly “AI readiness” and should happen earlier in the hold period.

Takeaways

• Move beyond chatbots by embedding AI into core workflows.
• Biggest blockers: people, unstructured data, and sensible governance.
• Fast value: churn prediction, outreach triggers, pricing and packaging.
• Dashboards aren’t enough; push insights to frontline decision-makers.
• Exit prep is AI readiness; start earlier to compound value

Chapters

00:00 Introduction
02:39 The Shift from Chatbots to AI Integration
05:33 Overcoming Barriers to AI Adoption
08:09 Cultural Factors in AI Implementation
10:48 Commercial Opportunities in Private Equity
12:39 Transforming Pricing and Revenue Models
15:21 Democratizing Insights through AI
18:01 Impact on Manufacturing and Reporting
20:39 AI Readiness and Exit Preparation

Links

• David on LinkedIn: https://www.linkedin.com/in/david-whitcombe-4a3bb331/
• Data Vision Services - https://datavisionservices.com

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 [email protected]

Summary

In this episode of the AI Pathfinder podcast, host Steve Budd speaks with Maria Bruun, founder and CEO of Seecon, about the transformative potential of AI in financial due diligence for private equity firms. Maria shares her extensive background in M&A and highlights the inefficiencies in traditional due diligence processes and her current purpose to build an AI business to redefine financial due diligence and deal preparation. The conversation explores how AI can automate data gathering, enhance analysis, and ultimately streamline the due diligence workflow. Maria emphasises the importance of human insight in interpreting data and discusses the challenges of adopting new technologies in a conservative industry. The episode concludes with a vision for the future of financial due diligence, where AI plays a central role in preparing companies for successful exits.

Takeaways

• AI can significantly enhance the efficiency of financial due diligence processes
• Automation can reduce manual errors and speed up data gathering
• Human insight is still crucial for contextualising financial data
• Competitive advantages can be gained by leveraging AI in deal evaluations.

Chapters

00:00 Introduction to AI Pathfinder and Seecon
01:28 Maria's Background and Experience in Financial Due Diligence
03:13 Identifying Inefficiencies in Financial Due Diligence
05:56 The Role of AI in Enhancing Due Diligence Processes
09:56 Automation vs. Human Insight in Financial Analysis
11:53 Adoption Challenges and the Importance of User Experience
15:02 Building Trust in AI Solutions for Financial Teams
15:59 Future of Exit Readiness for PE-Backed Companies
17:08 The CFO's Role in Financial Due Diligence
18:46 Preparing for AI Adoption in Financial Processes
21:17 Competitive Advantages of Using AI in Due Diligence
22:45 Envisioning the Future of Financial Due Diligence
24:20 The Evolving Role of Advisors in Financial Transactions

Links

Maria on LinkedIn

Seecon website

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 [email protected]

Summary

In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd discusses the critical role of AI governance with experts Graeme Cox and Sarah Clarke from Attercop. They explore the misconceptions surrounding AI governance, emphasising its importance as a value enabler rather than a hindrance to innovation. The conversation covers various themes, including the risks associated with AI liability, the parallels between AI governance and cybersecurity, and the necessity for private equity firms to understand and manage AI risks within their portfolio companies. The guests highlight the importance of visibility, education, and a structured approach to governance to leverage AI effectively while mitigating risks.

Takeaways

• AI governance is often misunderstood as a cost rather than a value enabler
• AI governance is becoming essential, akin to cybersecurity hygiene
• AI governance frameworks are still developing and need to be prioritised
• Understanding AI risks requires a focus on use cases rather than tools
• Effective governance can lead to competitive advantages

Chapters

00:00 Introduction to AI Pathfinder and Governance
03:34 Understanding AI Liability and Governance Risks
08:39 AI Governance as Cybersecurity Hygiene
11:09 The Evolution of AI Governance
14:41 Visibility and Management of AI Risks
21:33 The Role of Private Equity in AI Governance
23:50 Linking AI Use Cases to ROI and Risk
26:40 AI Governance as a Competitive Differentiator
31:20 First Steps in AI Governance Implementation

Links

Attercop website
Graeme Cox on LinkedIn and Sarah Clarke on LinkedIn

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 [email protected]

Summary

In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd and Eleanor Hobson discuss the growing liability concerns surrounding AI technologies, particularly for mid-market companies. They explore the risks associated with GenAI, the challenges in contractual agreements, and the implications of the EU AI Act. Eleanor provides insights on how portfolio companies can mitigate risks and emphasises the importance of AI literacy and compliance in navigating this evolving landscape. The conversation highlights the need for a strategic approach to AI adoption and the potential future trends in the industry.

Takeaways

• AI is not just an opportunity; it also brings significant liability
• Mid-market companies are feeling squeezed between AI providers and customer demands
• Generative AI tools create a complex risk landscape for businesses
• Contractual obligations are shifting, placing more risk on AI users
• The EU AI Act introduces new expectations for documentation and compliance
• AI literacy is essential for both providers and customers

Links

Kemp IT Law website

Eleanor Hobson on on LinkedIn

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 [email protected]