Additional Services & Workshops
Introduction to AI For PE Backed Boards
A 2-hour boardroom primer on how AI drives value creation across the PE deal lifecycle — from diligence to exit — anchored in The AI Fix for PE.
Duration: 2 Hours
Objective: Provide private equity board members with a pragmatic, investor-focused view of AI as a lever for value creation across the deal lifecycle, anchored in the principles from The AI Fix for PE by Mark Rogerson & Gary Pearson.
The session ensures boards can:
Understand the difference between machine learning and cognitive AI, and their relevance to both software and non-software businesses.
Identify where AI can impact diligence, 100-day planning, transformation, and exit preparation — consistent with the four stages outlined in The AI Fix for PE.
Build confidence in overseeing AI adoption, governance, and investment decisions at portfolio level.
Spot red flags (poor data hygiene, lack of governance) that may hinder value creation.
Equip themselves with next steps to commission AI maturity assessments, launch lighthouse pilots, and build AI-enabled equity stories that command premium multiples.
Develop a clear sense of where AI is hype vs. where it delivers measurable ROI, reflecting the book’s emphasis on system-level adoption over “bolt-on tools.”
Position their portfolios to stand out in exit processes by embedding AI into the equity story early and consistently.
Welcome & Framing: AI as the next material shift in PE. Introduce the book The AI Fix for PE as the foundation for this session, highlighting its central thesis: AI is no longer optional, it is the defining lever of value creation in PE-backed businesses.
What is AI? A Practical Primer:
Machine Learning (ML): Optimising structured tasks like churn prediction, credit scoring, and demand forecasting. Highlight the book’s point that these tools are useful but not transformative without a broader AI strategy.
Cognitive AI (Generative & Reasoning): Unlocking unstructured data (text, voice, images) for copilots, customer service, intelligent workflows. Link to The AI Fix for PE’s guidance on system-level adoption as the true differentiator.
Non-Tech Examples: Predictive maintenance in manufacturing, workforce scheduling in services, personalised promotions in retail, compliance in professional services — showing AI’s relevance beyond software, as stressed in the book.
Key Takeaways:
A clear understanding of AI’s role as a driver of PE value creation, linked directly to The AI Fix for PE.
Practical frameworks to identify, prioritise, and govern AI opportunities across the investment lifecycle.
Ability to challenge management teams on data readiness, AI maturity, and whether initiatives align with the investment thesis.
A roadmap for introducing AI across diligence, the 100-day plan, the transformation journey, and exit — mirroring the lifecycle structure of the book.
Confidence in embedding AI into the equity story to command premium multiples, with evidence-based proof points.
Clear oversight questions boards can ask to keep management focused on investor outcomes, as highlighted in the book’s “AI as a differentiator” message.
Early recognition of risks and blockers (data, culture, governance) before they erode AI’s potential.
Practical next steps boards can act on immediately, rooted in The AI Fix for PE: assess → map → govern → pilot → evidence.