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.

AI labs like Anthropic are forming joint ventures with PE firms to create AI consultancies. The PE firms' portfolio companies become a ready-made customer base, solving the difficult go-to-market problem and creating a flywheel for AI adoption and cost reduction within the portfolio.

Instead of only investing in tech, Sequoia builds it. The firm employs as many developers as investors to create proprietary tools. This includes an AI system that summarizes business plans, analyzes team quality, and maps competitive dynamics, giving partners an immediate, data-rich overview of opportunities.

Private Equity value creation has evolved. In the 2000s, it was driven by leverage; in the 2010s, by digital transformation. Today, AI serves as the new foundational "operating system" for growth, embedding intelligence into every process, contract, and customer touchpoint to drive returns.

The rapid evolution of AI means traditional private equity M&A timelines are too slow. PE firms and their portfolio companies must now behave more like venture capitalists, acquiring earlier-stage, riskier AI companies to secure necessary technology before it becomes unaffordable or obsolete.

Instead of being disrupted by new 'AI-native' PE firms, incumbents like Bain Capital and TPG are forming a joint venture directly with OpenAI. This creates a dedicated 'deployment arm' of forward-deployed engineers to embed AI solutions across their vast portfolio of companies, accelerating enterprise adoption at scale.

Private equity firms are adopting AI to quickly screen initial investment memorandums (CIMs) for red flags. This automation handles low-level review tasks, freeing up investment professionals to focus on higher-value activities like building relationships with executives and industry experts.

Private equity firms are aggressively implementing AI across thousands of their portfolio companies. This isn't just for efficiency; it's a strategy to boost profitability and make these companies, particularly struggling SaaS businesses, more attractive for exit in a tough market. This creates a massive, real-world testbed for enterprise AI.

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.