How to Use AI for Due Diligence: Streamlining Legal and Business Investigations
Due diligence is a core step in business transactions, from mergers and acquisitions to investment rounds and supplier onboarding. It involves reviewing a company, asset, or individual to confirm facts, identify risks, and check compliance.
Traditionally, due diligence has been manual, time-consuming, and prone to missed details. AI is changing that by helping legal teams, investors, and business leaders review large volumes of information faster and more consistently.
For anyone looking into how to use AI for due diligence, the practical answer is this: use AI to accelerate document review, surface risk indicators, organize findings, and support decision-making, while keeping humans in charge of final judgment.
Why AI Matters in Due Diligence
The risk in due diligence is not just missing a detail. A single overlooked issue can lead to financial loss, legal exposure, reputational harm, or a failed transaction.
The challenge is volume. Due diligence often involves contracts, financial statements, regulatory filings, news articles, court records, and internal communications. Reviewing all of that manually takes time and creates room for error.
AI tools can process large datasets quickly and help teams focus on the issues that matter most. Key benefits include:
- Faster review timelines: AI can help sift through documents, identify clauses, and flag potential issues more quickly.
- Better consistency: AI can support more uniform review across large document sets.
- Lower manual workload: Teams spend less time on repetitive review and more time on analysis.
- Broader insight: AI can help identify patterns, anomalies, and connections that are easy to miss in manual review.
- Improved risk detection: AI can surface issues early so teams can investigate before a deal moves forward.
For lawyers, compliance teams, investors, and business operators, AI is increasingly part of a practical due diligence workflow rather than a novelty.
Best AI Tools for Due Diligence
Different tools support different parts of the process. Some are best for contract analysis. Others are stronger for background checks, adverse media, collaboration, or eDiscovery-style document review.
1. Kira Systems
What it does: Kira Systems is an AI-powered contract analysis tool that extracts and analyzes clauses, terms, dates, parties, obligations, and other data points from large volumes of legal documents.
Why it is useful: Kira automates the repetitive task of reviewing contracts and helps teams quickly locate relevant provisions, summarize key terms, and identify deviations from standard language.
Best fit: High-volume contract review in M&A, real estate due diligence, and corporate finance.
Pros:
- Strong at extracting specific contract clauses and data points
- Useful for large document sets
- Supports custom model creation
- Designed for collaboration
Cons:
- Focused mainly on contract review
- May need to be paired with other tools for broader due diligence
- Can be costly
- Customization may require a learning curve
2. LexisNexis Risk Solutions, including LexisNexis Diligence
What it does: LexisNexis provides risk and investigative tools that analyze public records, news sources, sanctions lists, social media, and other data sources to build profiles and assess risk.
Why it is useful: It helps uncover adverse media, sanctions issues, fraud indicators, politically exposed persons, and other background risks that matter in due diligence.
Best fit: KYC, AML, sanctions screening, third-party risk management, and background checks in transactions or investments.
Pros:
- Broad data coverage
- Strong risk scoring and entity resolution capabilities
- Useful for global risk review
Cons:
- Can be expensive
- Large datasets may require careful filtering
- Best results often depend on skilled analyst review
3. Thomson Reuters HighQ
What it does: HighQ is a secure cloud-based collaboration and workflow platform with AI features for managing documents, tasks, and project communications.
Why it is useful: It works well as a central hub for due diligence projects, helping teams organize work, assign tasks, and manage secure document review in one place.
Best fit: Complex, multi-party due diligence projects, especially in M&A and corporate restructuring.
Pros:
- Strong collaboration and workflow tools
- Secure environment for sensitive information
- Scalable for larger projects
- Useful for team coordination
Cons:
- AI features are less specialized than dedicated contract tools
- Requires implementation and training
- Pricing may be challenging for smaller firms
4. Casetext CoCounsel
What it does: CoCounsel is a generative AI legal assistant that can review documents, summarize information, identify potential issues, and help draft reports.
Why it is useful: It can speed up early-stage review by summarizing long documents, extracting requested clauses, and helping turn findings into draft work product.
Best fit: Early-stage document review, stakeholder summaries, and support drafting for due diligence reports.
Pros:
- Flexible and broadly useful
- Good for summarization and first-pass review
- Built for legal workflows
- Can support a range of tasks beyond due diligence
Cons:
- Outputs require careful human verification
- Not as specialized for granular contract extraction as dedicated tools
- Best practices for LLM use in due diligence are still developing
5. Seal Software, now part of DocuSign Insight
What it does: Seal Software is an AI-powered contract analytics platform focused on extracting data and identifying risk across a company’s broader contract portfolio.
Why it is useful: It helps teams understand obligations, liabilities, and compliance issues across existing agreements, not just the contracts tied to a single transaction.
Best fit: Contract lifecycle management, portfolio analysis, compliance reviews, and broader contractual due diligence.
Pros:
- Wide contract coverage
- Deep visibility into obligations and risk
- Useful for standardization and compliance review
Cons:
- Implementation can be substantial
- May be more than needed for a narrow deal review
- Typically positioned for enterprise use
6. Everlaw
What it does: Everlaw is a cloud-based eDiscovery platform with AI features for search, clustering, and document review.
Why it is useful: It can help teams manage large sets of electronic documents, identify relevant materials, and group similar files during investigations or data-heavy due diligence projects.
Best fit: Due diligence involving large volumes of electronic documents, internal investigations, regulatory reviews, or digital assets.
Pros:
- Strong search and review tools
- AI clustering helps organize large datasets
- Secure and collaborative
- Useful for eDiscovery-style due diligence
Cons:
- More focused on document organization than clause extraction
- Requires familiarity with eDiscovery workflows
- May feel more technical than general business tools
How to Choose the Right AI Tool for Due Diligence
The right tool depends on the scope of the review and the type of information you need to analyze.
Consider the following:
- Scope of the project: Are you reviewing contracts, broader business risks, or both?
- Data type: Are you working with unstructured text, structured records, or public-source data?
- Team expertise: Will your team need a simple interface, or can it manage more advanced setup?
- Integration needs: Does the tool need to connect with your document management system or workflow stack?
- Budget: Are you looking for a single-project tool or an enterprise platform?
- Scalability: Can the tool handle larger reviews as your needs grow?
In many cases, the best answer is not one tool but a combination. For example, a team might use Kira for contract review, LexisNexis for background checks, and HighQ to manage the project.
Pricing and Value Considerations
AI due diligence tools range from individual-user products to enterprise platforms with substantial annual licensing costs.
When evaluating pricing, look at total value, not just the sticker price:
- Return on investment: How much time, labor, and risk reduction does the tool provide?
- Subscription vs. project pricing: Some tools are better for recurring use, while others fit one-off matters.
- Implementation costs: Account for setup, training, and workflow design.
- Scalability: Make sure the pricing structure still works as your volume grows.
If possible, use demos or trials to test whether a tool fits your workflow before committing.
How to Use AI for Due Diligence in Practice
A practical workflow usually looks like this:
1. Define the review scope
Decide what you are trying to uncover: contract risk, compliance issues, background risk, financial red flags, or all of the above.
2. Organize the input data
Collect contracts, filings, reports, emails, public records, and other source material in a structured way.
3. Use the right tool for the task
Apply contract AI for clause extraction, risk platforms for background checks, and document review tools for large file sets.
4. Review AI outputs carefully
Treat AI as a first pass. Human review is still necessary to verify findings and assess context.
5. Summarize and escalate issues
Turn AI-assisted findings into a clear issues list, report, or decision memo for the relevant stakeholders.
6. Document your process
Keep a record of what was reviewed, what was flagged, and how decisions were made.
Frequently Asked Questions About AI for Due Diligence
Can AI completely replace human due diligence analysts?
No. AI is best used as an augmentation tool. Human review, judgment, and legal interpretation are still essential.
What are the biggest risks of using AI in due diligence?
The main risks include data privacy concerns, security issues, algorithmic bias, and inaccurate outputs if findings are not checked by humans.
How can I improve the accuracy of AI-generated due diligence reports?
Use reputable tools, assign AI to specific tasks, and require human verification of critical findings and interpretations.
Do I need specialized IT skills to use AI for due diligence?
Not always. Some tools are designed for legal professionals with minimal technical training, while others require more setup and support.
How can AI help identify hidden risks?
AI can process large datasets quickly and flag patterns, inconsistencies, adverse media, and connections that may be difficult to spot manually.
Is AI due diligence suitable for smaller firms and businesses?
Yes. Many tools now offer more accessible pricing and easier workflows, making AI useful for smaller teams as well as large organizations.
Conclusion
AI is changing due diligence by making document review faster, risk detection more consistent, and investigations more efficient. For lawyers, investors, and business teams, the value is not in replacing human judgment but in improving the speed and quality of review.
If you are deciding how to use AI for due diligence, start with the specific task you need to improve. Then choose the tool that fits your workflow, data type, and budget. Whether you need contract analysis, background screening, project collaboration, or large-scale document review, the right AI tool can make due diligence more practical and more reliable.