Global secondary market transaction volume hit a record $226 billion in 2025, up 41% from $160 billion in 2024, according to Pitchbook. To put that growth in perspective: closed transaction volume in 2013 was just $28 billion.
Manual processes, fragmented data rooms, and document overload now constrain how quickly buyers can move and how thoroughly they can assess risk. When the market was a fraction of its current size, teams could conduct confirmatory diligence and work through datarooms methodically. That's no longer feasible.
As deal sizes increase and timelines compress, AI-powered due diligence workflows and purpose-built private equity due diligence software are becoming essential infrastructure for secondaries investors.
From my time in commercial due diligence at L.E.K., where I participated in 150+ due diligence engagements, and now supporting our clients at ToltIQ, I've seen the gap widen between what deal teams must verify and what traditional diligence workflows can realistically process.
This problem is particularly pronounced in secondaries, where the volume of potential opportunities is very high, while the time required to get to yes or no is condensed compared to the scope of a typical buyout.
On any given deal the VDR may contain hundreds of documents of varying file types. Within ToltIQ individual deals average around 300 files comprising thousands of pages of data. In one instance there were more than 100,000 files uploaded for analysis. Without an AI platform it would have been extremely difficult to analyze that volume of information with accuracy and within time constraints.
Under ILPA guidance, LPs often have 30 calendar days to make roll-or-sell decisions in GP-led secondaries. Within that window, diligence teams are expected to review years of quarterly reports, capital account statements, valuation memos, portfolio company financials, side letters, and legal documentation across dozens, sometimes hundreds, of underlying assets.
This leaves LPs with limited time to build conviction on growth prospects across a wide range of investments.
There is no GAAP equivalent for private fund reporting. Every GP reports differently. EBITDA definitions vary. Financials arrive indifferent currencies, fiscal year-ends, and accounting conventions.
I've heard secondaries investors describe reviewing dozens of GP reports as "a headache I’d rather avoid."
The manual effort required to normalize this information is enormous, and it's precisely during this process that material risks are obscured rather than revealed, and performance signals get lost.
Some of the most consequential diligence insights never appear in summary tables. They live in narrative quarterly reports, valuation memos, and Q&A appendices.
Examples recur across deals:
These signals are present in the data room. Traditional workflows simply fail to surface them at scale without AI-driven documentary intelligence.
Across the industry I hear investors expressing similar concerns about doing risk-focused reviews within exceedingly tight time constraints.
The result is growing reliance on risk transfer mechanisms: reps and warranties insurance, GP indemnities, and contractual protections designed to compensate for what diligence couldn't cover. An estimated 20 to 30 percent of GP-led secondary transactions now include RWI, and insurers have adapted their products specifically for secondaries with lighter diligence requirements and tailored coverage. The growth of this market reflects how the industry has adapted to the reality that exhaustive diligence isn't always achievable within deal timelines.
But these tools transfer risk without identifying it, and the premiums represent a recurring cost for diligence gaps that better infrastructure could close.
Secondaries teams are lean by design. Analysts spend weeks extracting data, standardizing formats, tracking quarter-over-quarter changes,and flagging anomalies, often in spreadsheets under intense deadline pressure.
The result is a familiar imbalance where data gathering and clean uptakes an overweighted portion of diligence.
Over the course of the 10+ years that I've been working in the world of due diligence, I've watched these five challenges feed into each other in ways that make the overall problem larger than any single pain point suggests. Document volume forces sampling. Sampling misses signals buried in narrative documents. Missed signals become post-close surprises that erode returns and trust. And with each deal, the cycle repeats.
Firms exploring AI for private equity due diligence quickly discover that general-purpose models fall short. Frontier models like ChatGPT or Claude cannot extract all the data points required for underwriting from fund documents. They lack the ability to pull insights simultaneously from CIMs, IC decks, consulting reports, and interview notes scattered across SharePoint, the web, and local drives. And they offer no bulk-analysis capabilities for reviewing fees, partnership agreements, side letters, and tax structuring across dozens of funds under time pressure.
Documentary intelligence platforms purpose-built for private markets address these gaps directly. At ToltIQ, where I work with secondaries investors daily, we've built capabilities specifically for the confirmatory diligence workflows that matter most:
We've processed roughly 5 million documents and 87 million pages for firms including some of the largest dedicated secondaries managers globally. Those firms report 60-70 percent time savings across key diligence workflows allowing them to expand coverage while compressing cycle time.
The secondaries market will keep growing. It still represents only about 1% of total private equity NAV, and the structural demand for liquidity solutions isn't going away. The question facing every secondaries investor is whether their diligence infrastructure can scale with their deal flow.
Deal flow has outpaced what manual processes can handle. Firms relying on manual processes, offshore teams, or generic AI will continue to sample rather than cover, transfer risk rather than identify it, and hope nothing material was buried in appendix seventeen of a quarterly report no one had time to read.
Purpose-built private equity due diligence software like ToltIQ offers a different path: review more, identify risk earlier, and move faster with confidence.
If you'd like to see ToltIQ in action, please click here to request a demo.
Eric Jacobs is Director of Client Solutions at ToltIQ, where he works with private equity firms and institutional investors on AI-powered documentary intelligence for confirmatory due diligence and investment workflows.
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