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This article was originally featured in Pitchbook's Q2 2026 US PE Middle Market Report.
Diligence redefined
The differentiator used to be data. Finding it, creating it, and accessing it were how investors and the firms that served them differentiated.
Today, due diligence has never produced more information. Investors have access to extraordinary amounts of data across markets, customers, competitors, financials, technology, and operations, supplemented by internal data, proprietary datasets, and increasingly powerful AI tools.
At the same time, a different generation of assets is working its way through private equity. Stretched hold periods have left a significant inventory of longer-held businesses ready to be brought to market. Many were bought when leverage and multiple expansion were powerful contributors to returns and financing was cheaper. In most cases, the next stage of ownership will need to find another, potentially harder, turn of value.
Both issues land at the investment committee (ICs).
ICs have not changed their mandate, but the questions required to reach conviction are changing. One investor recently described the old model simply: “We always had to present the same six slides in our IC submission, regardless of the asset.” The same metrics and questions would be applied relatively consistently from one investment to the next.
With vast information ecosystems, ICs are tailoring core questions to the asset and its value-creation thesis.
Conviction comes when the evidence around the critical questions is strong enough for an IC to decide on price, risk, and expected return. Across deals, conviction is increasingly returning to three fundamental questions:
- How much value can we create during our ownership?
- How will we create this value?
- What will the next buyer need to believe to pay us more than we paid today?
Diligence may involve hundreds of questions, thousands of slides, and countless data points. But today, only a handful of findings materially change the investment decision and set priorities for the ownership that follows.
The return of the operational investor
The first of those questions has become harder to answer.
Historically, approximately 30% of investments were sold by year four. Of acquisitions made during 2021, only 19% had been sold by 2025. More than 16,000 buyout-backed companies have now been held for over four years, representing over half of the buyout-backed inventory.
As those assets return to market, the next owner needs a different playbook. With multiple expansion becoming less available as an underwriting lever, and buy-and-build alone less valued today, the diligence focus becomes more specific: the durability of the recent growth algorithm, the growth catalysts particular to the asset, and the risks of delivering them. A business may have performed well for current owners while offering insufficient untapped value to generate the next owner’s required return.
The result becomes an operational underwriting question. The next owner needs a credible path from “good to great,” with diligence identifying where the next turn of value will come from, how much it could be worth, and what needs to go right.
The questions are straightforward but demanding: How much value remains? Where will it come from?
Turning information into evidence
Getting to those answers starts with knowing the right questions.
Across diligence disciplines, traditional scope objectives tend to be relatively consistent: Frame the business as it exists today and then assess how it is likely to evolve. That work remains important, but conviction now depends on identifying the issues that really matter and the evidence needed to resolve them, even when the evidence crosses traditional solution lines or sits between them.
Experience, pattern recognition, and judgment become critical when identifying the handful of questions worth spending time on and where the evidence to answer them is likely to sit. Gathering data is getting easier, but pinpointing what to test is becoming increasingly asset-specific. More data and stronger technology can improve the evidence; they cannot provide judgment.
Consider an investment in a company where the thesis depends on the target successfully expanding from enterprise to small and medium-size business (SMB) customers. Customer interviews may say SMB buyers like the product. Win/loss data may suggest the value proposition is not landing. Module uptake data may point to product gaps, while pricing work suggests the assumed economics are aggressive.
While these findings may be true, the job is to determine what the evidence collectively says about the thesis and what it means for the ownership plan.
Answering these questions often crosses traditional diligence boundaries and draws on evidence from multiple sources. Commercial, financial, technological, and operational diligence all remain essential, but the work is most valuable when the key issues are not forced into solution-specific frameworks and outputs but are allowed to bubble across disciplines.
Every investment thesis needs an AI thesis
AI adds another layer of complexity to diligence. It can strengthen or weaken the product, change willingness to pay, or alter the customer profile. It can also take real cost out of the business, require significant investment, or reshape the competitive landscape. And the impact will differ for each asset, further eroding the value of “one-size-fits-all” diligence.
In tandem, AI is changing diligence too. Firms can process more data and test more hypotheses faster. But faster analysis does not strengthen weak evidence, and an informed answer to the wrong question is not useful.
Underwriting today’s acquisition and tomorrow’s exit
The next question looks further ahead: What will the next buyer need to believe?
Sponsors are increasingly looking beyond their immediate ownership period, asking what business they will ultimately sell. Perhaps it needs more recurring revenue, better margins, less customer concentration, a proven runway into new markets, or a real AI advantage. Diligence must establish whether the business can realistically get there and what it will take.
A sponsor is effectively underwriting two transactions. Validating the second transaction requires questions around future value that do not fall neatly within traditional diligence workstreams.
Conviction is the product
These changes are shaping how we approach diligence at Grant Thornton Stax. Starting with investment questions rather than traditional solutions makes for seamless work across disciplines while following the strongest evidence.
Judgment is the key differentiator in identifying what really matters, what is unknown, and which hypotheses are worth testing. And it makes sense of the evidence, particularly when it sits between solutions.
This is closer to what we mean by conviction. It is not certainty. It is knowing what matters, what to believe, where uncertainty remains, and whether the ownership plan can realistically deliver the return.
Sometimes, this means doing the deal. Sometimes, it changes the price or the plan. And sometimes, the right answer is to walk away.
That is conviction.
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