Insights from the frontlines of VDR due diligence
Prior to generative AI, human capital was the primary edge driving a successful diligence process. Today, that edge increasingly comes from how well firms harness AI.
I work with dozens of firms who use our AI platform to streamline their diligence workflows. As someone who previously ran commercial diligence projects on behalf of PE firms (many of whom are now DiligentIQ pilots or clients), I understand how labor intensive and inefficient the traditional model can be. AI is actively changing how the best teams operate and expanding the realm of what’s possible in the context of diligence.
Here are five ways I’m seeing AI actively reshape the private equity landscape:
The longer it takes to validate or disqualify an opportunity, the more risk you introduce; from internal bandwidth constraints to losing out to faster-moving competitors.
The best AI users are collapsing the time it takes to get to “yes” or “no.” They’re using custom prompts to zero in on key risks, validate core assumptions, and rule out non-starters quickly. What used to take a week of reading now takes an hour of prompting and reviewing.
The upside isn’t just the time savings, it’s increasing confidence in the quality of the workflow. In a competitive market, deciding first - whether it means not burning team time on dead deals, or being able to move quickly on attractive opportunities - directly impacts fund performance.
We often hear AI described as a tool, but in the hands of the most effective users, it also acts as a collaborator.
Rather than just automating tasks, power users are stress-testing theses. They design prompts that function like digital analysts, asking questions they would normally pose in an IC memo or partner meeting. For example: What external conversations have we had that conflict with details in the management presentation? Are there any financial metrics or KPIs that raise red flags?
These users are leveraging AI to not only extract information, but also to help tease out if they are missing anything.
Typically, diligence follows a sequential path: gather documents, read through them, extract insights, compile findings, then analyze. AI allows all this to occur simultaneously.
Users that have invested the time into understanding how AI works are flipping the workflow entirely. They are starting with defining the desired output and designing prompts that extract relevant content immediately. They’re designing logic that tells the AI what to find, flag, and summarize, while also using AI to ensure all relevant documents are considered.
The result? Analysts and deal leads spend less time on doc review, and more time synthesizing and deciding. In this new model, workflows are shifted to concentrate on decision making rather than executing data aggregation.
Proprietary and highly refined prompts are a new class of strategic assets. Firms are able to codify their internal frameworks—how they assess ARR quality, customer concentration risk, growth opportunities—into reliable and consistent prompts that can be quickly adapted across deals and run as playlists.
In effect, they’re turning the firm’s collective knowledge into scalable, repeatable diligence processes.
With AI-driven playbooks, firms can apply the same high bar of scrutiny across every deal, regardless of who’s on the team.
In the past, the mark of a strong diligence professional was how quickly they could read, understand and retain complex information. While that is still relevant, an increasingly valuable skill is the ability to translate repeatable processes into tasks that can be completed by AI.
The best users I work with are inquisitive, curious and the best at asking sharp questions and translating those into structured prompts. They think in frameworks. They know what matters. And they leverage AI to do the heavy lifting.
That shift is creating a new kind of analyst. One who’s less burdened by tedious work and more focused on insight.
AI isn’t replacing human judgment in private equity but it is reshaping where that judgment is applied. The firms we see getting the most value aren’t just using AI tools, they’re rethinking the way they work. They’re moving quickly to build scalable diligence engines. While critical thinking remains the essential ingredient in diligence, firms that can harness AI to augment and accelerate their analytical capabilities will be well positioned for the future.
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