40% of LPs now expect their GPs to use AI in the deal process. 18 months ago, that number was near zero.

In this brief: Why AI moved from competitive advantage to baseline expectation, where private capital firms are seeing the biggest impact, and our recent product updates.

The Shift: 40% of LPs Now Expect GPs to Use AI

The LP conversation around AI has fundamentally changed.

2023-2024: "Are you experimenting with AI tools?"

2025-2026: "How is AI embedded in your deal process? Show us the metrics."

LPs aren't asking for pilots anymore. They're asking for repeatable, embedded capabilities integrated into how deals get sourced, how diligence gets done, and how portfolio value gets created. Firms that operationalised early meet this expectation while firms still experimenting struggle to show results.

Where AI is Landing: Due Diligence Leads

44% of PE professionals now rank due diligence as the #1 area where AI will drive the most value in the deal lifecycle, up from 29% the previous year according to Roland Berger's 2026 European Private Equity Outlook.

Why diligence? Volume, speed, and complexity collide. What slows teams: parallel workstreams across multiple documents, fragmented data sources, repeated questions because context doesn't carry forward, and late-stage IC alignment issues.

Firms seeing leverage embed AI directly into workflows. They build systems where AI maintains context across the entire diligence process, not just individual tasks.

One mid-market fund reduced financial data processing from 48 hours to 5 minutes per company by automating PDF extraction and aggregation. The result: they can now analyse 100x more companies in the same timeframe, shifting effort from manual data work to investment decisions.

The shift is less about AI adoption and more about where you deploy it. Diligence is where the leverage shows up first because that's where the friction costs the most.

The Hidden Cost

Beyond LP expectations, there's an immediate productivity problem.

McKinsey research shows employees spend 1.8 hours every day searching and gathering information. For a 30-person investment team at $200K average loaded cost:

• 9 hours/week × 50 weeks × 30 people = 13,500 hours annually

• $1.3M in lost productivity to scattered data

Beyond that cost: repeated analyses because past work can't be found, slower decisions in competitive processes, and lost institutional knowledge when people leave.

This is the silent tax firms pay for fragmented institutional knowledge and is exactly why we built SharePoint Live Sync - to surface institutional knowledge in real-time so teams stop paying that silent tax. When your SharePoint files and folders change, your team's institutional knowledge updates automatically. No more searching for hours or redoing past analyses.

It's part of how we're building infrastructure purpose-built for private capital workflows, from ad hoc questions to automated intelligence running in the background.

Our recent product updates include:

• SharePoint Live Sync: Enterprise search across all SharePoint content with real-time updates as files change

• Automated Workflows: Recurring analysis to track portfolio companies, monitor markets, and assess competitors on your schedule

• LinkedIn Integration: Company and people data directly in Capsa for talent mapping and relationship intelligence

Read more about our updates → here.

One Thing to Do This Week

Audit your next diligence process. Track hours spent searching for past analyses, hours identifying relationship context, and hours on actual analysis. If 40%+ is spent searching and gathering, that's your opportunity. Firms that operationalised AI are at 20% or less.