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

Links

Margo's LinkedIn

ProSapient

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

Have a question or would like to suggest improvements, please contact [email protected]

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

Links

Al's LinkedIn

GiantKelp

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

Have a question or would like to suggest improvements, please contact [email protected]

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links

Simon's LinkedIn: https://www.linkedin.com/in/simon-walker-8763b9/

Kubrick Group: https://www.kubrickgroup.com/uk/

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links

Phil's LinkedIn: https://www.linkedin.com/in/philwestcott/

Filament Syfter: https://filament.ai/

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links

Dan's LinkedIn: https://www.linkedin.com/in/dan-thompson-kluster/

Kluster website: https://www.kluster.com/

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links

Richard's LinkedIn: https://www.linkedin.com/in/richardnicholas/ 
Browne Jacobson: https://www.brownejacobson.com/

AI Pathfinder: https://www.aipathfinder.co

Private Equity AI Strategy Day: https://www.aipathfinder.co/ai-strategy-day

Private Equity AI Strategy Breakfast Briefings: https://www.aipathfinder.co/breakfast-briefings

Have a question or would like to suggest improvements, please contact [email protected]

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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.

Links

Tom's Linked In and General Purpose's Website

AI Pathfinder website and more details on the Private Equity quarterly breakfast briefings here

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links
Athena LinkedIn profile
Beacon Thought Leadership

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

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 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

Links
Public version of Johann's hypothesis GPT
Post re AI metrics
Johann's LinkedIn profile and company website 

AI Pathfinder Private Equity AI Strategy Meet-ups:

https://www.aipathfinder.co/ai-strategy-day
https://www.aipathfinder.co/breakfast-briefings

Have a question or would like to suggest improvements, please contact [email protected]