Half of 1,000 senior dealmakers use AI regularly or have fully embedded it in due diligence, and only 4% do not use it at all at that stage, according to The New Deal Team, a survey by Datasite with FT Longitude. Due diligence leads every deal stage on regular use.
In sourcing and screening, 96% use or explore AI there, but 43% use it regularly or have fully embedded it, a 53-point gap by our arithmetic. Datasite, which sells AI tools for deals, commissioned the survey.
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The key insight: As we read Datasite’s survey, regular AI use is highest in due diligence, the stage respondents link to the highest return, while the decision to sign stays with people for 45% of them.
Blueflame AI, part of Datasite’s product portfolio, summarised the report by stage. Regular or fully embedded use is 50% in due diligence, 43% in sourcing and screening and 39% in deal marketing. Diligence leads deal marketing by 11 points, by our arithmetic.
In diligence, “only 4% say they do not use it at all at this stage”, the summary says. That leaves 46% who use AI in diligence but not regularly, by our arithmetic. Datasite’s release calls due diligence “the stage delivering the highest reported ROI”.
Share of 1,000 senior dealmakers using AI regularly or fully embedded, by deal stage, from Datasite’s survey with FT Longitude (March 2026) as reported in Datasite’s release and Blueflame AI’s summary. Point gaps are our arithmetic.
Trying vs Embedding
Use or exploration is near universal: 96% for sourcing and screening, and 92% each for strategy and ideation and for deal preparation, the summary says. Regular use is lower at every stage it reports.
In sourcing and screening, 96% use or explore AI and 43% use it regularly, a 53-point gap, by our arithmetic. In diligence the regular share is 50%. The report pages we read give no comparison with an earlier survey, so the change from last year cannot be measured.
Who Answered
Datasite says it commissioned FT Longitude, “the specialist research and content studio of the Financial Times Group”, to survey 1,000 dealmakers at the C-suite or C-1 level across 27 countries in March 2026. Respondents came from corporate development, private equity, law, accounting and professional services.
All had “decision-making responsibility in at least three deals during the previous 24 months”, the release says. It was published on 24 June 2026; wallstengine posted the diligence figures on 12 November.
Where Dealmakers Keep the Final Call
The release says 62% of dealmakers call human-only decision-making no longer defensible in complex transactions, and 71% believe firms that ignore AI today will struggle to compete within five years. It says 43% say AI already makes better deal decisions than humans in some scenarios.
Yet 45% say the decision to sign a deal should always remain a human responsibility, and only 22% say AI should lead that recommendation, the Blueflame summary says. It says 45% believe AI should lead in identifying potential red flags during due diligence, and 58% rely on human review and validation of AI outputs.
Rusty Wiley, Datasite’s chief executive, said: “AI can automate analysis, but it can’t own accountability.” The release says advisors are “slightly ahead of corporates in embedding AI, particularly in due diligence”.
The Structural Read
As we read the stage figures, most dealmakers have tried AI in sourcing, 96%, but 43% use it regularly there, a 53-point gap by our arithmetic.
As we read the release, the survey’s own sponsor, Datasite, sells AI tools for deals, and the figures are self-reported by 1,000 senior dealmakers in March 2026.
Rusty Wiley, President and CEO of Datasite, in the release of 24 June 2026
“As AI takes on more of the heavy lifting in M&A, human judgment becomes more valuable, not less.”
Three Implications
FOR DEAL TEAMS The release says 58% rely on human review and validation to build trust in AI-generated outputs.
FOR AI VENDORS The release says accuracy, cited by 71%, and security, cited by 70%, rank as the two most important requirements for AI in dealmaking.
FOR BOARDS The release says 27% are not using AI for board reporting.
The framework says: “Judgment becomes the highest-value layer of work.”
As we read it, the survey shows that split: half of dealmakers use AI regularly for diligence analysis, while 45% keep the signing decision human.
AI in sourcing and screening: share of 1,000 senior dealmakers using or exploring it vs using it regularly or fully embedded, from Datasite’s survey with FT Longitude (March 2026) as summarised by Blueflame AI. The 53-point gap is our arithmetic.
What Is Not Established
The release and the summaries do not give the full answer scale for each stage, so the 46% in-between share mixes every answer other than regular use and no use. The survey is self-reported and was commissioned by a company that sells AI tools for deals. We did not obtain the full report document.
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In Datasite’s survey of 1,000 senior dealmakers, due diligence leads AI use: 50% use it regularly or have fully embedded it, and only 4% do not use it at all. In sourcing, 96% use or explore AI against 43% who use it regularly, a 53-point gap by our arithmetic.
A note on sourcing. We read Datasite’s release of 24 June 2026, its report page and insight article, and Blueflame AI’s summary of the report in full; Blueflame AI is part of Datasite. We did not obtain the full report document. The survey was commissioned by Datasite, which sells AI tools for deals. Point gaps labelled as ours are our arithmetic. The X post that prompted this piece is a lead; every figure here is from Datasite’s own pages.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
