Topics
Foreword By the numbers
What’s at stake?
The side letter arms race
Overview
PE embracing AI technologies
AI origination for VC investments
The limitations of AI & lack of data
AI in decision making
Using AI to predict future outcomes
Do LPs really need AI to process qualitative information?
AI techniques to predict company director performance
Do large networks and directorships mean poor performance?
What aspects of PE are ripe for AI disruption?
AI for PE: hype vs. reality
What aspects of PE are ripe for AI disruption?
Foreword By the numbers
Retrospective: A bigger picture
Roundtable: Will AI transform private equity?
Understanding LPs performance
The role of academic research in PE
The most influential pieces of academic research
The affect of the 2006-07 credit bubble
Resilience of the PE industry
The the growth of private debt funds
Areas of current research
Areas of research opportunities?
What’s at stake?
PE embracing AI technologies
AI origination for VC investments
The limitations of AI & lack of data
AI in decision making
Using AI to predict future outcomes
Do LPs really need AI to process qualitative information?
AI techniques to predict company director performance
Do large networks and directorships mean poor performance?
What aspects of PE are ripe for AI disruption?
AI for PE: hype vs. reality
Time for a new model?
The side letter arms race
Roundtable: Will AI transform private equity?
What other aspects of PE are ripe for AI disruption?
“AI has the potential to disrupt any task that involves managing and analysing large datasets. This includes document reading and writing, financial analysis, and daily market research. Automating these tasks can free up valuable time for PE and VC investors, allowing them to focus more on strategic decision-making and building relationships with entrepreneurs.”
Maxime Bonelli
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