AI Due Diligence Checklist: What PE Firms Automate vs. Keep Manual

The pitch from every AI vendor sounds the same: "Automate your due diligence and close deals faster."

But talk to deal teams at top PE firms and you hear something more nuanced. Yes, they're using AI extensively. But they're strategic about what they automate—and deliberately manual about other things.

We interviewed deal partners and operating teams at 8 middle-market and large-cap PE firms. Here's the real playbook: what they automate, what they don't, and why.

The Automate vs. Manual Framework

Before diving into specifics, here's the decision framework most firms use:

Automate when:

• Volume is high and tasks are repetitive
• Speed matters and errors are recoverable
• The output is an input to human judgment (not the final decision)

Keep manual when:

• Judgment and context are essential
• Relationships are involved
• Errors are costly or irreversible

With that lens, here's how AI fits into the diligence workflow.

What PE Firms Automate

1. Data Room Document Processing

The task: Review thousands of pages in virtual data rooms—contracts, financials, HR records, customer agreements. (For more on the underlying technology, see machine learning applications in due diligence.)

How AI helps: Automated extraction of key terms, flagging of non-standard clauses, summarization of material documents. One firm told us: "AI reviews the data room in 48 hours. Our associates used to need 2 weeks for initial triage."

What stays manual: Final review of flagged issues, materiality judgments, negotiation strategy based on findings.

ROI: Most firms report 60-70% reduction in initial document review time.

2. Financial Data Extraction

The task: Pull historical financials from various formats into standardized models.

How AI helps: OCR and extraction from PDFs, normalization of accounting treatments, automated population of model templates.

What stays manual: Quality of earnings adjustments, pro forma calculations, valuation assumptions.

ROI: 3-4 hours saved per deal on data entry alone. More importantly: fewer transcription errors.

3. Expert Call Transcription & Summaries

The task: Conduct and document 20-50+ expert and customer reference calls per deal. (See our framework for maximizing value from expert interviews.)

How AI helps: Real-time transcription, structured summaries, extraction of key quotes and themes across all calls.

What stays manual: Expert selection, interview strategy, interpretation of qualitative feedback, judgment on reference quality.

ROI: One VP of Operations told us: "We used to have associates spend 2 hours writing up each reference call. Now they spend 15 minutes reviewing the AI summary. On a deal with 40 references, that's 70+ hours saved."

4. Market & Competitive Intelligence

The task: Build market sizing, competitive landscape, and industry trend analysis.

How AI helps: Automated aggregation from industry reports, news monitoring, job posting analysis for hiring trends, web traffic and app download tracking.

What stays manual: Market thesis development, competitive positioning interpretation, strategic implications.

ROI: Faster access to baseline market data. The real value is analysts spending time on insight, not data gathering.

5. Legal Document Review

The task: Review material contracts for change of control provisions, assignment clauses, key customer/supplier terms.

How AI helps: Clause extraction, comparison against standard terms, flagging of unusual provisions across hundreds of contracts.

What stays manual: Legal interpretation, risk assessment, negotiation of carve-outs and amendments.

ROI: Legal review that took weeks now takes days. Outside counsel hours reduced significantly on routine review.

What PE Firms Keep Manual

1. Management Assessment

Every firm we spoke with was emphatic: AI doesn't assess management.

"You can't automate reading a room," one deal partner said. "When a CEO hesitates on a question about customer concentration, I need to be there to see it."

The human edge: Body language, rapport, judgment of character, assessment of coachability.

2. Thesis Development & Deal Structuring

AI provides inputs. Humans develop the thesis.

"AI can tell me what's in the data room," a partner explained. "It can't tell me whether this business fits our fund's strategy or how to structure a deal that aligns incentives."

The human edge: Pattern recognition across deals, strategic judgment, creativity in structuring.

3. Key Relationship Calls

Customer references, key supplier calls, conversations with former executives—these stay human-led.

"The most important reference call is the one where the customer almost says something, then catches themselves. AI can't pick up on that."

The human edge: Building rapport, reading between the lines, adjusting questions in real-time based on subtle cues.

4. Negotiation Strategy

Findings from AI-assisted diligence inform negotiation. But the negotiation itself is human.

The human edge: Reading counterparty motivations, creative problem-solving, relationship preservation for post-close partnership.

5. Final Investment Decision

No firm automates the investment committee decision—nor should they.

The human edge: Integrating quantitative findings with qualitative judgment, weighing factors that can't be quantified, accountability for outcomes.

The Integrated Workflow

Here's how AI and humans work together across a typical middle-market deal:

Phase	AI Handles	Humans Handle
Screening	Automated data gathering, initial scoring models	Thesis fit assessment, go/no-go decisions
Initial Due Diligence	Document processing, market research aggregation	Management meetings, thesis refinement
Deep Due Diligence	Expert call transcription, contract review, pattern flagging	Key relationship calls, risk assessment, judgment calls
Final Due Diligence	Synthesis of findings across workstreams	IC presentation, negotiation strategy
Close	Document automation, checklist tracking	Final approvals, relationship management

Implementation Advice

From firms that have done this well:

Start narrow: Pick one workflow (most start with document processing or expert calls) and implement well before expanding.

Integrate, don't add: AI tools that require separate logins and workflows get abandoned. The best implementations plug into existing processes.

Measure time saved: Track hours before and after. This builds internal support for expansion.

Keep humans accountable: AI assists, humans decide. Make clear that AI outputs require human review and judgment.

The Competitive Reality

AI in due diligence is no longer optional. When you're competing against firms that process data rooms in 48 hours, doing it in 2 weeks puts you at a disadvantage.

But the edge isn't just speed. It's reallocation of human attention.

"We do the same number of expert calls we always did," one partner noted. "But our team spends time preparing better questions and synthesizing insights instead of writing transcripts. The quality of our diligence has gone up, not just the speed."

The firms winning deals aren't fully automating diligence. They're strategically automating the commodity work so humans can focus on what humans do best: judgment, relationships, and creative problem-solving.

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InsightAgent helps PE deal teams capture insights from expert calls and customer references with AI-powered transcription and analysis. Learn more.