At L.E.K. Consulting, we’ve witnessed firsthand how generative artificial intelligence (GenAI) is beginning to transform private equity (PE) firms — evolving from hype to strategic solution. Through a survey of over 30 industry leaders, we’ve obtained a front-row view into the GenAI revolution underway.

Read on for exclusive insights into how top PE firms are deploying AI’s power to improve everything from deal sourcing and research to due diligence and back-office operations.  

Staged approach to GenAI adoption

Our conversations revealed that adoption of GenAI remains nascent today, with most PE firms following a phased “crawl, walk, run” strategy (see Figure 1). The vast majority (67%) remain in the early stages of this journey; however, there is a cluster of low-hanging-fruit use cases that are yielding results. 

Phase 1: Initial exploration

In this phase, firms focus on aligning their GenAI strategies and experimenting with high-volume, low-risk applications like summarizing investment memos, drafting interview guides, creating competitor lists, personalizing recruitment emails and summarizing expert call notes. Key actions in this phase include forming strategy committees, educating employees and using public tools like OpenAI’s ChatGPT, Google’s Gemini and Perplexity AI within defined data use policies.

Phase 1 firms usually tap into their existing staff for GenAI initiatives, favoring internal skills enhancement over new specialized hires. Current team members often take on GenAI adoption and blend it with their existing responsibilities, exploring its potential through self-education and experimentation with public tools.


“We are using GenAI to transcribe primary research calls and generate call summaries. This process takes a lot of time and deploying GenAI has helped us save time.”

— Senior Partner, Megafund


Phases 2 and 3: Enhancing productivity

Around 33% of surveyed firms have evolved to phase 2, where activity and investment are more meaningful as firms leverage GenAI to expedite an expanded set of tasks to enable worker productivity. Examples in this stage include integrating proprietary deal or firm data to supplement public research, extracting and summarizing data from deal rooms, and automating industry updates.  

As firms advance to phases 2 and 3, the demand for dedicated talent becomes more evident, but firms don’t typically rush to hire AI-specific experts such as AI developers. Instead, they prioritize the specialized skills of existing staff, such as software engineers, to integrate GenAI into their workflows. This strategy helps assess the existing resource gaps that GenAI can address. This approach also aids in forecasting the evolution and complexity of future use cases, ensuring that the timing and scale of hiring align with their expansion goals.

The GenAI tools utilized in these phases vary but often involve integrating general purpose foundational models with other systems to address specific needs. While many out-of-the-box tools like Hebbia can search for information, advanced firms are also developing customized solutions to optimize workflows, often still leveraging underlying large language models from providers like OpenAI and Anthropic. Examples include:

  • Automating aspects of limited partner outreach by integrating Anthropic into existing customer relationship management (CRM) systems
  • Expediting elements of deal sourcing by using ChatGPT Premium or Anthropic for sentiment analysis of targets and scoring based on predefined metrics
  • Supporting due diligence processes by using ChatGPT Premium or private deployments of Azure OpenAI to summarize confidential information memorandums and synthesize findings 

Correlation between adoption and firm size

Perhaps surprisingly, adoption of GenAI is not correlated to firm size; however, we do see less variability in adoption among larger firms. Some smaller firms are more advanced in their deployment of GenAI and are more aggressively experimenting with the new technology to differentiate themselves from larger players (see Figure 3).


“Bigger firms may be outsourcing the development of these capabilities, but we are developing skills in-house. We want to deploy GenAI on top of our datasets to expedite research.”

— Partner, Midmarket Fund


Barriers to GenAI adoption in PE firms

Navigating the challenges of GenAI adoption, PE firms encounter several key barriers:

  • Understanding GenAI: 63% of firms report uncertainty on how to begin, often leading to a “wait and see” approach
  • Privacy and security: 59% of firms note high-profile data leakage has created unease and a desire to wait until security concerns are resolved before meaningfully proceeding  
  • Cost considerations: 34% of firms note cost concerns have sidelined GenAI for other digital priorities (e.g., CRM change, cloud migration)  

Moving forward with GenAI in PE firms

  • Assigning clear owners to spearhead GenAI strategy across the organization
  • Establishing robust internal policies for safe, ethical GenAI use
  • Investing in education on GenAI tools and practical applications
  • Running controlled pilot projects focused on low-risk, high-impact use cases, with defined key performance indicators to measure benefits
  • Providing portfolio companies with GenAI implementation guides, legal support and proven use cases
  • Proactively evaluating and managing risks across their portfolios

The key to realizing GenAI’s immense potential is translating insight into strategic action tailored to each PE firm’s needs. At L.E.K., we combine our knowledge of PE workflows and priorities with our deep expertise in digital strategies — including GenAI — to unlock value within a firm and across portfolios.

Our ongoing research has identified 39 tactical use cases that leading PE firms can evaluate against their workflows to advance GenAI capabilities.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2024 L.E.K. Consulting LLC

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