How to Use Generative AI for Due Diligence

Due diligence stretches internal resources more than almost any other legal workflow. These are all-too-familiar stories for global in-house legal teams: Deals, vendor contracts, and cross-functional requests all have tight timelines and high expectations. Sales wants a 150-page contract reviewed before a deal can close. Finance needs clarity on a target’s obligations. Leadership wants a risk assessment before the next negotiation. …and every delay has a business impact.

It is no wonder so much of this work is delegated to outside counsel, resulting in an inflated outsourcing budget that only compounds the stress.

But today, generative AI (GenAI) is changing the math. A task that would ordinarily take days can be done in a few hours or minutes. That gives in-house teams the capacity to keep due diligence reviews in-house, lessening outside legal spend. 

In this blog, I’ll explore the benefits, risks, and challenges of using generative AI-powered legal tools for due diligence; illustrate what this looks like with an example; and share actionable next steps for adopting this technology to improve your processes.

Related reading: AI vs. Generative AI: What's the Difference? 💡 

What are the benefits of using GenAI for due diligence?

By now, the advantages of using GenAI for legal processes are well-explored: by increasing speed, accuracy, and consistency, AI can help create a significant business advantage, improve consistency, and reduce in-house teams’ reliance on outside counsel.

Additionally, here are some key benefits for using GenAI for due diligence in particular:

Benefit 1: Keeping legal spend down

“There has been a budget crunch in legal, especially in technology, and generative AI is a common solution.” – Legal AI: Driving the Future of the Profession

Due diligence is costly because so much of it must be outsourced to outside counsel. The volume is simply too great for most in-house teams to absorb. 

GenAI tools like Cecilia Q&A empower teams to complete work in minutes that might have taken days to perform manually. These tools can flag inconsistencies and highlight the documents and issues that warrant deeper review, so teams can rely on outside counsel only where it truly adds value, reducing both time and cost.

Benefit 2: Boosting accuracy and consistency

“About two to three weeks ago, the CEO started encouraging each group to explore ways to utilize AI. The goal is to eliminate human error wherever possible.” – Legal AI: Driving the Future of the Profession

Manual diligence invites variation: Different reviewers may flag different issues, interpret clauses differently, or miss anomalies when fatigue sets in. 

GenAI improves consistency by highlighting deviations, spotting missing provisions, and surfacing outliers across a document set. 

It reduces the risk of human error and helps ensure that similar contracts or financial disclosures are analyzed using the same criteria every time — a major advantage when diligence requests come in waves.

Benefit 3: Accelerating deal time

Whether it’s an acquisition, a major vendor agreement, or a strategic partnership, deal velocity matters. Slow diligence can stall negotiations, delay revenue, and frustrate internal stakeholders who need answers quickly. 

Generative AI compresses the critical parts of the review cycle. Instead of reading every document line by line, legal teams get early visibility into the issues that drive deal value and risk within minutes.

Faster diligence gives the business a competitive edge: Teams can make informed decisions sooner, keep deals moving, and respond to opportunities before competitors do.

Benefit 4: Reducing risk

“In addition to cost savings, our use of generative AI is driven by risk mitigation. One area we are considering is how to leverage past experience using generative AI to help us make future decisions or to set a current strategy.” – Legal AI: Driving the Future of the Profession

The sooner in-house teams can identify risk, the better positioned they are to make sound decisions. 

Generative AI can help surface potential issues early in a deal. Think missing terms, unusual obligations, compliance gaps, and financial anomalies. It can highlight patterns that indicate deeper concerns and bring attention to areas that require human judgment. 

By accelerating risk identification in this way, AI helps prevent surprises late in the deal cycle and may even reveal when the company would be better served to leave the table.

These are just some of the benefits of using GenAI for due diligence. But what does it look like in practice? In the next section, I’ll explore this with a business fable-style example.

Example: GenAI-powered due diligence in action

BigCorp is preparing to acquire a fast-growing competitor, FastTech, and the CEO wants to move quickly – a 30-day close if possible. 

For the General Counsel, that means pressure from every direction: confirm the value of the target, surface hidden liabilities, and validate the assumptions driving the deal. 

The business wants to accelerate. But Legal must slow the process just enough to look under the hood and ensure BigCorp isn’t inheriting risk it can’t see.

In the data room, thousands of contracts, compliance documents, employment agreements, financial schedules, and corporate records arrive in varying states of organization. Outside counsel can help, but time and budget are limited. 

The GC knows what needs to happen: identify red flags, compare key clauses across agreements, confirm ownership of IP, evaluate customer obligations, and highlight anything that could require renegotiating the price or restructuring the deal. 

The challenge is the sheer volume of due diligence that needs to take place in a limited amount of time. 

But with generative AI, the team can move immediately. 

Instead of reading every agreement line by line, the team uses DISCO Cecilia to gain insights quickly. DISCO Doc Summaries summarizes FastTech’s top customer and vendor contracts, flagging missing provisions and highlighting unusual terms. And with Cecilia Q&A, the team quickly surfaces issues that could create significant liability. 

Within days — not weeks — the GC has a clear view of the risks that matter: a material IP ownership issue, a pending employment claim not previously disclosed, and several high-value customer contracts with termination rights that could affect valuation. 

Instead of getting lost in the volume, the GC is able to focus on strategy: advising the CEO, proposing revisions to the deal structure, and determining what must be resolved before closing.

Risks and challenges of using generative AI for due diligence

Challenge 1: AI is only as good as the documents you receive

GenAI can accelerate diligence, but it still depends on the quality and completeness of the materials provided. If pages are missing, scans are poor, or key attachments aren’t included, a human reviewer might immediately sense something is off.   AI may not. The model works with what it’s given, which means gaps in the source material can lead to gaps in the analysis.

Solution: Pair AI with early checks and ongoing human review

A strong due diligence workflow pairs AI with human oversight early in the process. Q&A-style interactions — like Cecilia’s Single-Doc Q&A — can quickly reveal inconsistencies, missing attachments, or unusual patterns that signal incomplete information. Cecilia Doc Summaries help reviewers digest dense materials in a fraction of the time, surfacing key themes and allowing attorneys to focus their attention on what matters most.

Together, these capabilities allow legal teams to confirm they’re working from a reliable record before they dive into deeper analysis.

Challenge 2: You still need the legal team to validate the output

Generative AI is not a magic wand. It can review large volumes of material at remarkable speed, but it doesn’t replace legal judgment. Even the most accurate model cannot determine materiality, strategic implications, or how a particular risk fits into the broader transaction. 

Solution: Use AI for the first pass – and attorneys for judgment

Choosing the right generative AI platform matters. A tool like DISCO gives legal teams an organized, high-quality first pass through the material — something that would otherwise take hours of manual review. 

This gives the legal team more time and space to evaluate findings, validate conclusions, and advise the business confidently. AI handles the volume; attorneys handle the judgment.

How to start using generative AI for due diligence: Actionable next steps

For in-house lawyers, ‘good enough’ isn’t an option, but ‘eventually’ is a deal-killer. The challenge is balancing the business’s need for speedy results without sacrificing the accuracy required to protect the company. AI acts as a force multiplier, giving teams the technical infrastructure to deliver results on a compressed timeline.

Here are some steps to ensure successful adoption:

1. Define success metrics early

Effective adoption starts with clarity. Before implementing GenAI, legal teams should identify the specific problems they want to solve — such as reducing outside counsel spend, accelerating contract or diligence review cycles, improving consistency, or giving business stakeholders faster answers. 

It’s also a good idea to define a set of metrics that matter to the business — such as turnaround time, outside counsel spend, faster risk identification, or improved response times — so you can demonstrate that AI adoption is delivering measurable value.

Clear success metrics ensure the technology is evaluated against meaningful goals, not abstract hopes. They also create alignment across legal, business partners, and leadership, making it easier to communicate value as the team begins using AI.

2. Start with a pilot

Small, purposeful pilots help legal teams build confidence and understand how AI fits into existing workflows. By testing the technology with a limited set of diligence materials, attorneys can see where it accelerates review, how it surfaces risks, and what training or refinements are needed before broader rollout. 

Early wins are important — they demonstrate value, build internal momentum, and make change feel manageable rather than disruptive. Feedback from the pilot also helps shape a smoother, more intentional adoption path.

3. Establish oversight and governance early

Generative AI accelerates diligence, but legal oversight remains essential, especially when reviewing large volumes of sensitive documents supplied by a third party. 

Establishing governance upfront clarifies how AI-generated insights will be validated, when human review is required, how confidentiality will be protected within the workflow, and how output will be documented for defensibility.

At a minimum, legal teams should define:

• Where AI is appropriate (and where it isn’t),
• How outputs will be validated and by whom,
• How confidentiality, privilege, and access controls will be protected, and
• How AI-assisted work will be documented for defensibility.

This level of structure reinforces cultural adoption by setting expectations, providing training, creating peer advocates, and encouraging feedback loops so reviewers can flag issues early. 

GenAI due diligence with DISCO

Curious to learn more about how GenAI could transform due diligence at your company? Check out our ebook, Generative AI for In-House Teams 2026: What You Really Need to Know. Or, to see what DISCO can do for you, contact our team and we’ll set up a demo.