Explore every episode of the podcast AI Pathfinder for Private Equity Podcast
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Title
Pub. Date
Duration
Eleanor Hobson: The AI Liability Squeeze for Portfolio Companies
25 Nov 2025
00:29:46
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
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Brian Briggs: Diligence in the Era of AI
14 Nov 2025
00:28:44
Summary
In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd and guest Brian Briggs discuss the evolving landscape of AI in private equity, particularly focusing on due diligence processes. They explore how AI is reshaping investor inquiries, the risks and opportunities it presents, and the importance of integrating AI considerations into investment strategies. The conversation highlights the need for a robust framework for AI due diligence, the significance of executive buy-in, and the necessity of aligning AI initiatives with core business metrics. Additionally, they provide insights on preparing for AI integration and the importance of education within private equity firms.
Takeaways
AI is transforming the questions investors ask during due diligence
Disruption risk is a significant concern for investors in AI
Investors should assess the maturity of a company's AI initiatives
A strong framework for AI due diligence is necessary for investors
Metrics for AI initiatives should align with core business objectives
Chapters
00:00 Introduction to AI Pathfinder and Today's Topic 02:45 Insights from the AI Diligence Panel 05:16 AI's Impact on Investor Questions 08:18 The Human Element in AI Adoption 10:53 Identifying Opportunities Amid Disruption 13:46 Evolving Diligence Frameworks for AI 16:03 Red Flags in AI Readiness 18:42 Value Creation Post-Deal with AI 21:16 Short-Term vs Long-Term AI Strategies 24:04 Building AI Capabilities in Private Equity 25:54 Conclusion and Key Takeaways
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Hazem Abolrous: The three pillars for AI mobilisation
04 Nov 2024
00:32:33
Summary In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd discusses the critical role of AI in private equity with Hazem Aboris, Managing Partner at RingStone. They explore the importance of AI mobilisation, the evolution of AI technology, and the necessary steps for successful implementation. The conversation highlights the significance of data quality, the need for a top-down approach, and the challenges organisations face in adopting AI. They also discuss the metrics for measuring its impact. The episode concludes with insights on the future of AI in organizations and the importance of a continuous learning mindset.
Takeaways
AI is crucial for business transformation in private equity
A significant percentage of AI projects fail due to lack of readiness
Data quality and strategy are foundational for AI success
AI mobilisation requires a top-down approach from the C-suite
An experimental mindset is necessary to explore AI possibilities
Metrics like R&D spend and revenue per employee will change with AI
Common challenges include messy data and nascent use cases
Organisations must adapt their ways of working to leverage AI effectively
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Johann Van Tonder: Exploring the role of leadership and experimentation in successful AI mobilisation
04 Nov 2024
00:33:39
Summary In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd engages with Johann van Tonder, CEO of AWA Digital (E-commerce CRO specialists), to explore the complexities of AI mobilisation. They discuss the high failure rates of AI projects, the importance of embracing failure as part of the learning process, and the necessity of identifying specific problems that AI can solve. Johann shares insights on how AI could transform the conversion rate optimisation industry, the slow but significant changes occurring across various sectors, and the role of leadership in building a culture of AI adoption. The conversation also touches on the importance of data maturity, the organisation of information for AI utilization, and the selection of appropriate AI tools. They also discuss the need for a thoughtful approach to measuring success in AI initiatives, recognising that not all valuable outcomes are easily quantifiable.
Takeaways
AI has the potential to significantly impact businesses
A high percentage of AI projects fail due to lack of readiness
Embracing failure is essential for progress in AI
Identifying specific problems is crucial before implementing AI
AI is not meant to replace human roles but to assist them
The transformation brought by AI is gradual but profound
Leadership should empower teams to explore AI without pressure
Data maturity is a common challenge for organisations
Organising data effectively is key to leveraging AI
Measuring success in AI initiatives can be complex and subjective
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Pauline Nissen: Building a Culture of Responsible AI
04 Nov 2024
00:30:39
In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd and Pauline Nissen, Ethical AI Lead at ML6 (builder of custom AI systems) discuss the critical importance of ethical AI and AI governance in the private equity sector. They explore how to promote responsible AI practices, the implications of the upcoming EU AI Act, and the necessity for organisations to adopt a culture of ethical AI. The conversation highlights the risks of neglecting ethical considerations in AI development and offers insights into best practices and resources for navigating the evolving landscape of AI governance.
Takeaways
Ethical AI is essential for responsible AI development
AI governance processes help mitigate risks associated with AI
The EU AI Act will significantly impact AI practices in Europe
Organisations must promote a culture of ethical AI
Investing in responsible AI can enhance user trust and reputation
Transparency in AI practices is crucial for ethical compliance
AI ethics involves more than just legal compliance; it requires cultural alignment
Private equity firms should assess the ethical practices of potential investments
AI governance should involve multiple roles within an organisation
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Shaun McGirr: practical considerations for Private Equity firms
09 Sep 2024
00:34:56
In this podcast episode, Steve Budd interviews Shaun, the Chief AI and Data Officer at DevOn, a software development company. They discuss the intersection of AI and private equity, the importance of understanding AI capabilities, and the potential for AI to unlock value in portfolio companies. Shaun emphasises the need for a practical and iterative approach to AI adoption, starting with small efficiency gains and gradually scaling up. He also highlights the importance of blurring boundaries and rethinking processes in order to fully leverage the potential of AI.
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
David Dobrin: seizing AI opportunities in an information rich business
09 Sep 2024
00:32:46
In this conversation, Steve Budd speaks with David Dobrin, Product Director, AI Platform at YouGov, about the potential of AI in the market research industry. They discuss the importance of taking action now and starting to build AI capabilities, even if the technology is not perfect. They also explore the challenges of managing expectations and keeping teams engaged with AI.
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Fernanda Dobal: proving ROI with AI chat and assistants
09 Sep 2024
00:29:40
In this conversation, Steve Budd speaks with Fernanda Dobal, the newly appointed product director of AI and chat at Cleo, a fintech company. Fernanda shares her experience in using AI to develop AI assistants for sleep training and financial coaching. They also explore the importance of user trust and the role of humans in the loop. The conversation emphasises the value of AI in improving efficiency, personalization, and accessibility.
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Will Bailey: using AI in data & information businesses
09 Sep 2024
00:31:30
In this podcast episode, Steve Budd interviews Will Bailey from 67 Bricks about the application of AI in data & information businesses. They discuss the benefits such as improving user experiences, extracting key concepts, and expanding coverage. Will shares examples of successful AI implementations, including semantic fingerprinting. They also address the challenges of cultural adoption and the fear of obsolescence. The conversation emphasises the importance of thinking big, starting small, and continuously learning and iterating with AI.
Keywords: AI, private equity, content management, data management, user experiences, semantic fingerprinting, automated content checking, cultural adoption, fear of obsolescence
AI Pathfinder Private Equity AI Strategy Meet-ups:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Margo Polishchuk: AI Won’t Replace Expert Networks, It Will Supercharge Them
24 Sep 2025
00:30:29
Summary
In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd speaks with Margo Polishchuk, co-founder and president of ProSapient, about the evolution of primary research in private equity. Margo shares her journey from the expert networking industry to founding ProSapient, emphasising the importance of customer-centric innovation and the integration of technology in research workflows. The conversation explores the impact of generative AI on the industry, the necessity of maintaining a human element in AI-driven solutions, and the evolving expectations of private equity firms. Margo also discusses best practices for firms to prepare for tech-enabled research.
Takeaways
Generative AI is reshaping research workflows in private equity
The integration of technology must maintain a human element
AI can enhance the speed and precision of expert intelligence
Firms need to adapt to evolving customer expectations
Chapters
00:00 Introduction to ProSapient and AI in Private Equity 01:07 Margo's Founder Story and Market Insights 03:46 Identifying Gaps in Expert Networking 10:14 Integrating AI into ProSapient's Model 13:04 The Role of Generative AI in Due Diligence 18:13 Customer Expectations and Market Dynamics 21:12 Preparing for ProSapient: Best Practices for PE Firms 23:15 Unlocking Unique Insights through Expert Conversations 25:00 Challenges in Building a Tech-Enabled Service 27:13 Future Directions and Geographic Expansion
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Al Cattell: Practical First Moves for Safe AI Adoption in Private Equity
24 Sep 2025
00:31:38
Summary
In this episode Steve Budd speaks with Al Cattell, founder of GiantKelp, about the practical applications of AI in private equity and business processes. They discuss the importance of using AI to automate workflows, the challenges of managing expectations, and the role of subject matter experts in successful AI deployment. Al shares insights from his experience in helping firms identify use cases for AI and the significance of starting small with controlled projects to build momentum for future initiatives.
Takeaways
AI is not a magic solution; it requires careful implementation
Successful AI projects often start with internal-facing tools
Managing expectations is crucial when introducing AI
Subject matter experts play a vital role in AI success
Small, controlled use cases can lead to significant improvements.
Building momentum is essential for broader AI adoption.
The landscape of AI is rapidly evolving, requiring agile strategies.
Chapters
00:00 Introduction to AI in Private Equity 01:14 The Birth of Giant Kelp and AI Exploration 03:58 Identifying Workflow Automation Opportunities 06:05 Successful AI Deployment Criteria 09:12 Building Minimum Viable AI Products 13:41 Expectation Management in AI Projects 16:01 The Role of Subject Matter Experts 16:09 Trust and Branding in AI-Driven Legal Work 19:50 Case Study: AI Implementation in a Law Firm 28:32 Advice for Scaling AI Strategies
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Simon Walker: Forget 'AI Strategy' How PE Firms Can Drive Real AI Impact Across Portfolios
23 Jul 2025
00:30:22
Summary In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd speaks with Simon Walker, co-founder of Kubrick Group, about the critical role of AI in private equity and portfolio companies. They discuss the evolution of AI capabilities, the urgency for private equity firms to adopt AI, and the importance of collaboration among portfolio companies. Simon shares insights on real-world applications of AI in sales and finance, the necessity of measuring AI success, and the cultural challenges faced in AI adoption. The conversation emphasises the need for proactive strategies and clear ownership of AI initiatives to drive value and innovation in the private equity sector.
Takeaways
AI is becoming essential for competitive advantage in private equity
The urgency for private equity firms to adopt AI is increasing
Collaboration among portfolio companies can accelerate AI adoption
AI initiatives should have clear ownership to avoid failure
AI should be viewed as a tool for tactical wins
Setting realistic expectations for AI outcomes is important
AI products require ongoing investment and development
Chapters 00:00 Introduction to AI in Private Equity 00:57 The Evolution of Kubrick and AI Solutions 02:50 The Urgency of AI in Portfolio Companies 04:32 Use Cases and Real-World Applications of AI 06:13 Mandating AI Implementation in Portfolio Companies 08:40 Accelerating AI Adoption Across Portfolio Companies 11:55 Measuring AI Success and Setting Expectations 13:47 The Importance of Defined AI Use Cases 15:29 Standardizing AI Readiness Across Portfolios 16:18 Identifying Skills Gaps in AI Implementation 19:23 The Role of Stakeholders in AI Projects 21:41 Kubrick's Focus on Talent and Capability 23:46 Preparing for the Future of AI in Private Equity 25:42 Cultural Challenges in AI Adoption 29:13 Conclusion and Key Takeaways
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Phil Westcott: From 'Batch Job' to 'Continuous Intelligence' in Deal Origination
16 Jul 2025
00:28:34
Summary In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd interviews Phil Westcott, CEO and co-founder of Filament Syfter. They discuss the transformative role of AI in private equity, focusing on how Filament Syfter helps firms build proprietary market intelligence to enhance deal origination. Phil shares insights on the inefficiencies in traditional processes, the importance of integrating data, and the competitive edge that AI can provide. The conversation also touches on the cultural shifts within private equity firms as they adapt to new technologies and the strategic steps they can take to leverage AI effectively.
Takeaways
The traditional deal origination process is often inefficient
Private equity firms need to integrate their data for better insights
AI can help firms identify and track the best fit deals
Building a proprietary engine is crucial for competitive advantage
Human insight remains essential in the AI-driven process
Cultural shifts are necessary for successful AI adoption in private equity
Chapters 00:00 Introduction to AI in Private Equity 02:33 The Journey of Filament Sifter 05:22 Identifying Opportunities in Private Markets 07:51 Transforming Deal Origination Processes 10:31 Building Proprietary Market Intelligence 13:09 Leveraging AI for Competitive Advantage 15:51 Measuring ROI in Deal Origination 18:31 Cultural Shifts in Private Equity 20:40 Next Steps for Private Equity Firms 23:17 Future of Data and AI in Private Equity
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Dan Thompson: Using AI to Solve Forecasting’s Hidden Problems
03 Jul 2025
00:33:33
Summary In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd speaks with Dan Thompson, CEO of Kluster, about the critical role of accurate forecasting in private equity. They discuss the challenges faced by private equity firms in forecasting, the concept of private equity grade forecasting, and how Kluster's unique approach leverages AI and data integration to enhance forecasting accuracy. The conversation also touches on the importance of data quality, the dynamics between private equity firms and their portfolio companies, and the future of forecasting in the industry.
Takeaways
Accurate forecasting is crucial for private equity firms
Different stakeholders have varying definitions of forecasts
AI can significantly enhance forecasting accuracy and insights
Data quality is often a major barrier to effective forecasting
Sales cycles are lengthening, impacting revenue predictions
Standardising forecasting definitions across teams is essential
The future of forecasting may involve more autonomous systems
Chapters 00:00 Introduction to AI in Private Equity 00:54 The Importance of Accurate Forecasting 03:07 Challenges in Forecasting 06:41 Understanding Private Equity Grade Forecasting 08:28 Kluster's Unique Approach to Forecasting 12:08 Data Management and Its Impact on Forecasting 14:14 Changing Behaviors in Data Capture 17:06 Surprising Patterns in Sales Data 21:13 The Dynamic Between PE Firms and PortCos 23:55 Turning Forecasts into Action 25:34 Raising the Forecasting Game 27:54 The Future of Forecasting 31:23 Incorporating External Factors into Forecasting
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Richard Nicholas: Legal Foundations for AI in Private Equity
26 Jun 2025
00:32:39
Summary In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd talks to technology lawyer Richard Nicholas to explore the intersection of AI, legal governance, and risk management in private equity. They discuss the challenges and opportunities that AI presents, particularly in terms of legal compliance, data privacy, and the importance of effective governance structures. Richard shares insights on how private equity firms can navigate the complexities of AI implementation, emphasising the need for collaboration, communication, and a proactive approach to risk management. The conversation highlights the critical role of in-house lawyers and the necessity of fostering a culture of trust and innovation within organisations as they adapt to the evolving landscape of AI.
Takeaways
AI projects often stall due to legal and contractual issues
In-house lawyers are crucial for managing AI-related risks
AI governance requires collaboration across various business functions
Trust in AI systems is vital for successful implementation
Policies alone are insufficient; practical governance is necessary
Engaging employees in AI processes enhances adoption and effectiveness
Innovation and governance can coexist to drive value
Identifying potential risks is crucial for AI deployment
Continuous learning and adaptation are key in the AI landscape
Chapters 00:00 Introduction to AI in Private Equity 02:41 Richard Nicholas: Background and Expertise 05:04 Legal Challenges in AI Implementation 07:48 Managing Change and Resistance to AI 10:20 Blockers to AI Adoption 12:42 Ongoing Governance and Responsibility in AI 15:22 Legal Foundations for AI Implementation 17:39 Six Steps for Effective AI Governance 20:09 Building Trust and Managing Risks in AI 22:38 The Role of Private Equity in AI Governance 25:17 Conclusion and Future Insights
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Tom Hewitson: How to Build AI Literacy in Organisations
01 Jun 2025
00:34:20
Summary
In this episode of the AI Pathfinder for Private Equity podcast, Steve Budd and Tom Hewitson discuss the journey of firms in adopting AI technologies. They explore the evolution of AI, the importance of building AI literacy, and the challenges organisations face in moving from experimentation to structured capability. Tom emphasises the need for leadership alignment, effective incentives, and metrics to measure success. The conversation also talks about the concept of 'vibe coding' and how AI can empower individuals to create their own solutions, ultimately transforming the way work is done in private equity and beyond.
Takeaways
Private equity firms are transitioning from AI curiosity to action. AI literacy is crucial for organizations to thrive in the future. Culture change is necessary for successful AI adoption. Leadership alignment is key to driving AI transformation. Incentives should focus on organic usage rather than bribery. Measuring AI usage frequency is a critical success metric. Organizations are in a discovery phase with AI technologies. Vibe coding allows non-programmers to create AI solutions. AI can significantly enhance productivity and efficiency. The future of work will involve everyone writing code.
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Athena Peppes: The three P's of AI Success
05 Nov 2024
00:30:25
Summary In this episode of the AI Pathfinder for Private Equity podcast, host Steve Budd engages with Athena Peppers, a thought leadership expert, to discuss the critical components of successful AI mobilisation in private equity. They explore the current state of AI adoption, the importance of understanding its impact on various industries, and the challenges organisations face in implementing AI strategies. Athena emphasises the need for a clear problem definition, the role of people and culture in AI adoption, and the significance of partnerships in navigating the complexities of AI technology. The conversation also highlights the importance of data readiness and leadership buy-in, as well as the common pitfalls organisations encounter during transformation efforts. Athena shares insights on learning from industry examples and the value of diverse perspectives in understanding AI's potential.
Takeaways
The adoption curve for AI varies by industry and company size
AI transformation is more complex than past IT transformations
Focus on problem definition to guide AI initiatives
People and culture are critical for successful AI adoption
Partnerships can help organisations navigate AI challenges
Data readiness is crucial for effective AI implementation
Learning from industry examples can inform best practices
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Maria Rosenstand Bruun: How AI Could Reshape Financial Due Diligence in Mid-Market Deals
12 Jan 2026
00:25:36
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
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Graeme Cox & Sarah Clarke: AI Governance as the Strategic Enabler
10 Dec 2025
00:34:10
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
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
David Whitcombe: Exit Prep Is Now AI Readiness - Why PE Needs to Start Earlier
01 Apr 2026
00:26:19
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:
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
John Gunn: The AI Maturity Gap is Your First-Mover Advantage
14 Apr 2026
00:32:11
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
Have a question or would like to suggest improvements, please contact steve@aipathfinder.co
Aris Valtazanos: Start with the Pain Point, AI Isn't Always the Answer
21 Apr 2026
00:30:20
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
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