AI Agents in Private Equity: Hype or Reality?

Unless you’ve been deliberately avoiding tech headlines, it’s hard to have missed AI Agents – the buzzword dominating conversations in 2025.

But beyond the hype, what’s the real opportunity for Private Equity? And what exactly would AI Agents look like in a PE context?

Let’s explore some of our clients’ most frequently asked questions about AI Agents, their practical applications, and potential benefits.

What are AI Agents?

Numerous definitions of AI agents are available. At the simplest level, an AI agent is a system with access to information or a knowledge base capable of executing specific actions.

A more sophisticated approach involves agentic workflows, where a primary AI agent coordinates multiple specialized assistants, each with distinct skill sets.

• For instance, one assistant might excel at interpreting legal language, while another specializes in financial modeling. These assistants can collaborate in a coordinated manner along a value chain to accomplish complex tasks.

This represents the more advanced end of the spectrum when discussing AI agents.

AI Agents in a Private Equity context

Consider a scenario where an AI agent is asked, “What are the key terms for a credit facility agreement?”. The workflow could look like this:

1. One agent identifies the most relevant document based on the query.
2. A specialized legal agent extracts pertinent clauses.
3. Another commercially-focused agent translates legal text into practical business implications.
4. A supervisory AI agent reviews the workflow, assessing accuracy and providing feedback or requesting adjustments.

This iterative process, significantly more advanced than standard outputs from platforms like ChatGPT, delivers more precise results.

However, careful consideration must be given to the use case and whether investing in the necessary infrastructure and architecture justifies the anticipated benefits.

Where AI Agents can be utilized in Private Equity

AI agents are poised to make substantial impacts on Private Equity. For now, we can think of two primary areas:

• The first is investment processes, where complex tasks such as deal origination – collecting, filtering, and scoring data – can greatly benefit from agentic workflows.
• The second area is investor relations, where teams frequently engage with tools like CRM, Word, PowerPoint, Excel, and Outlook. Integrating AI-powered add-ins into these platforms can significantly streamline workflows. For example, automating responses to DD questionnaires using an AI agent with access to a historical knowledge base represents a particularly compelling use case.

Considerations when deploying AI Agents

The primary consideration when implementing AI agents is the rapid evolution of technology. Investments made in agentic infrastructures or workflows today may become outdated within six to twelve months due to advancements and shifting connections.

One specific area worth exploring is the Model Context Protocol (MCP), which enables AI systems, such as Anthropic’s Claude, to interface seamlessly with external services like databases.

This technology offers intriguing possibilities, such as executing tasks directly through AI interfaces, sending emails, or updating databases.