Current AI excels at information gathering, similar to a junior analyst. However, it lacks the meta-level learning to develop true expertise from repeated tasks. This makes it a powerful tool for amplifying existing experts by handling tedious work, not replacing their decision-making capabilities.

AI's primary value in pre-buy research isn't just accelerating diligence on promising ideas. It's about rapidly surfacing deal-breakers—like misaligned management incentives or existential risks—allowing analysts to discard flawed theses much earlier in the process and focus their deep research time more effectively.

AI isn't necessarily leading PE funds to do more deals. Instead, it compresses the initial, time-consuming phase of diligence from weeks to a single day, allowing teams to reallocate their energy toward deeper debate on core value creation drivers.

Many firms mistakenly focus on AI outcomes first. True success, as shown by THL Partners, begins with the unglamorous foundational work of establishing a solid data structure, aggregation, and strategy before building tools or chasing insights.

In early 2025, AI adoption in PE-backed companies was often performative. It focused on individual productivity hacks rather than creating quantifiable business value, especially for firms preparing for an exit who needed a good 'AI story'.

Despite a long-standing data-science-driven investment thesis, Foresight Capital's founder Jim Tananbaum states that AI tools have not yet objectively led to increased investment returns. The technology is still maturing, highlighting a reality gap between the hype around AI in VC and its current practical impact.

AI can quickly find data in financial reports but can't replicate an expert's ability to see crucial connections and second-order effects. This leads investors to a false sense of security, relying on a tool that provides information without the wisdom to interpret it correctly.

AI will automate routine but complex tasks like chasing portfolio companies for financials and updating models. The associate's role will shift to managing these automated workflows, setting quality checks, and handling exceptions, much like a conductor leading an orchestra.

A PE firm achieved a breakthrough by first meticulously mapping every single task investors perform. This detailed workflow analysis allowed them to bypass generic solutions and pinpoint precise, high-leverage opportunities for AI, such as drafting investment memos in minutes instead of weeks.