How to Use AI for Compliance Review: A Practical Guide for Legal and Regulatory Teams
Compliance review is becoming harder to manage manually. Regulations change, document volumes keep growing, and legal teams are expected to spot risk quickly and consistently. For law firms, in-house counsel, and compliance teams, AI can help reduce manual effort, improve review consistency, and surface issues earlier in the process.
This guide explains how to use AI for compliance review, which tools are commonly used, and what to consider when choosing a platform.
Why AI Matters for Compliance Review
Compliance review often involves checking contracts, policies, communications, and other records against legal, regulatory, and internal requirements. That work is time-consuming and repetitive, and it is easy for human reviewers to miss issues when volumes are high.
Common challenges include:
- Time constraints: Manual review of contracts, communications, and policies can slow down business operations.
- Human error: Large document sets increase the risk of missed clauses, overlooked obligations, and inconsistent judgments.
- Scalability limits: As organizations grow, manual review processes often cannot keep pace.
- Higher costs: Large review projects require significant attorney and staff time.
- Inconsistent standards: Different reviewers may apply compliance requirements differently.
AI helps address these problems by identifying patterns, extracting key terms, flagging risky language, and organizing large datasets for faster review. It is especially useful in areas such as:
- Contract review: Finding clauses related to privacy, indemnity, sanctions, data use, and other requirements.
- Policy management: Comparing internal policies against external obligations.
- Communication monitoring: Reviewing emails, chats, and messages for risky or non-compliant language.
- Regulatory change management: Tracking new regulations and assessing their impact on existing documents and workflows.
- Due diligence: Reviewing large document sets during transactions, investigations, or vendor onboarding.
How to Use AI for Compliance Review
The most effective use of AI for compliance review is to treat it as a review accelerator, not a replacement for legal judgment. A practical workflow usually looks like this:
1. Define the compliance issue
Start with a clear question. For example:
- Are data privacy clauses present in vendor agreements?
- Do communications contain language that suggests misconduct?
- Do contracts align with a specific regulatory standard?
2. Collect and organize the relevant documents
AI works best when the source material is well organized. Group contracts, policies, communications, or case files by matter, business unit, or review objective.
3. Use AI to extract and classify information
Depending on the tool, AI can:
- identify specific clauses
- categorize documents
- detect non-standard language
- surface potentially relevant communications
- compare documents against expected terms or requirements
4. Review the flagged issues
AI output should be reviewed by qualified professionals. The goal is to accelerate review, not eliminate oversight.
5. Document decisions and remediate gaps
Once issues are identified, teams can track remediation, update templates, revise policies, or escalate concerns as needed.
6. Refine the process over time
As your team uses the tool, refine review criteria, tagging logic, and workflows to improve accuracy and efficiency.
Best AI Tools for Compliance Review
Different tools serve different compliance needs. Some are strongest for contract analysis, while others are built for eDiscovery, monitoring, or financial crime compliance.
1. Luminance
What it does:
Luminance is an AI-powered legal analysis platform that uses natural language processing and machine learning to review legal documents at scale. It can analyze contracts and agreements, identify key clauses, and flag deviations from standard or preferred language.
Why it is useful:
It helps legal teams review large volumes of contracts faster and more consistently. It is especially helpful for identifying missing or non-standard compliance-related clauses.
Best fit:
Mid-sized to large law firms and in-house legal departments handling substantial contract volumes, especially for transactional work, due diligence, and routine contract review.
Pros:
- Strong document understanding
- Good at identifying anomalies and deviations
- Useful for due diligence and contract review
- User-friendly interface
Cons:
- May be expensive for smaller firms
- More focused on legal documents than broader communication monitoring
2. RelativityOne
What it does:
RelativityOne is best known as an eDiscovery platform, but it also includes AI and machine learning features that are useful for compliance review. It can process large volumes of documents, emails, and other electronically stored information, and tools such as Active Learning and Concept Clustering help surface relevant material.
Why it is useful:
It is well suited to investigations, audits, and regulatory matters that involve large datasets. It can help teams identify potential compliance breaches more quickly than manual review alone.
Best fit:
Large organizations and law firms handling litigation, regulatory inquiries, internal investigations, or compliance audits involving substantial volumes of electronically stored information.
Pros:
- Strong analytics for large datasets
- Highly scalable
- Security and data governance features
- Well-established in legal tech
Cons:
- Can be complex to implement
- May be more than needed for simpler document review projects
- Costs can rise with volume and usage
3. Everlaw
What it does:
Everlaw is an eDiscovery and litigation platform with AI tools that help organize and analyze document sets. Its machine learning features support review, visualization, and issue spotting across large collections of materials.
Why it is useful:
For compliance teams working on investigations or regulatory responses, Everlaw helps surface relevant documents and organize evidence more efficiently. It can also help build a clearer narrative from large review sets.
Best fit:
Law firms and corporate legal teams that want a user-friendly platform for eDiscovery, litigation support, and document review with strong AI capabilities.
Pros:
- Intuitive interface
- Strong visualization tools
- Useful collaboration features
- Good predictive coding and review support
Cons:
- Compliance features come mainly through eDiscovery functionality
- Can be costly depending on deployment and usage
4. Seal Software, now part of DocuSign
What it does:
Seal Software specialized in AI-powered contract analytics and is now part of DocuSign. Its platform uses machine learning and NLP to extract and analyze terms from large contract portfolios.
Why it is useful:
It can help organizations find compliance-related obligations across thousands of agreements, including clauses tied to privacy, regulatory requirements, and contractual risk.
Best fit:
Large enterprises, financial institutions, and regulated companies with significant contract portfolios that need ongoing compliance monitoring.
Pros:
- Strong contract analytics
- Useful for large-scale contract review
- Helps centralize contract insights
- Good for post-signature obligations and lifecycle management
Cons:
- Primarily contract-focused
- Less useful for communications or other non-contract data
- Enterprise pricing may be significant
5. Kira Systems
What it does:
Kira Systems is AI-powered contract analysis software that extracts specific clauses and data points from legal documents. It can be trained to identify provisions related to privacy, sanctions, anti-bribery, and other compliance requirements.
Why it is useful:
It speeds up due diligence and contract review by helping teams quickly find relevant language across large document sets.
Best fit:
Law firms and in-house teams handling M&A due diligence, portfolio reviews, or clause-level audits of contracts.
Pros:
- Accurate clause extraction
- Customizable for specific use cases
- Useful for due diligence workflows
- Good for building tailored review models
Cons:
- May require training for specialized use cases
- Focused mainly on contracts rather than broader compliance data
6. ComplyAdvantage
What it does:
ComplyAdvantage provides AI-driven tools for financial crime risk management. Its platform helps identify sanctions, politically exposed persons, adverse media, and other risk factors through real-time monitoring and risk scoring.
Why it is useful:
It is valuable for organizations with AML and KYC obligations. The platform supports customer due diligence, transaction monitoring, and ongoing screening.
Best fit:
Financial services firms, payment providers, and other organizations with strong anti-money laundering and customer verification requirements.
Pros:
- Specialized for AML and KYC
- Real-time data feeds
- Risk scoring and monitoring capabilities
- Scales well for high-volume screening
Cons:
- Narrower focus than general compliance platforms
- Not designed for every compliance category
- Can be expensive
How to Choose the Right AI Tool for Compliance Review
The right tool depends on your compliance goals, the type of data you review, and how your team works. Use the following factors to compare options:
1. Define the compliance use case
Start with the specific problem you need to solve. Are you reviewing contracts, monitoring communications, screening customers, or tracking regulatory change?
2. Match the tool to the data type
A platform built for contracts may not be suitable for email monitoring or financial crime screening. Choose a tool that fits your document volume and file types.
3. Check the AI capabilities
Look beyond broad AI claims. Understand whether the platform uses NLP, machine learning, predictive coding, or clause extraction, and whether those functions fit your workflow.
4. Review integration options
Consider how the tool will connect with your existing systems, such as contract lifecycle management, eDiscovery platforms, CRM tools, or document repositories.
5. Assess usability and training needs
A strong platform still needs to be usable by the team that will run it. Evaluate the interface, setup process, and training requirements.
6. Confirm security and data governance
Compliance tools often handle sensitive information. Make sure the vendor supports appropriate security controls, privacy protections, and data handling practices.
7. Think about scalability
Choose a tool that can support future growth, larger datasets, and changing regulatory obligations.
Pricing and Value Considerations
AI compliance tools vary widely in cost. Pricing often depends on the tool type, usage level, and deployment size.
Common pricing models include:
- Subscription pricing: Recurring fees based on users, data volume, or features
- Usage-based pricing: Charges based on documents processed, reviews run, or data analyzed
- Implementation fees: Costs for setup, configuration, migration, and training
When evaluating value, focus on more than the sticker price. A tool may reduce review time, improve consistency, and help avoid costly errors. Those benefits can justify the investment, especially for high-volume or high-risk review workflows.
If possible, request a detailed proposal and run a pilot before committing to a long-term contract.
Frequently Asked Questions
Can AI replace human compliance officers?
No. AI is best used to support human reviewers, not replace them. It can handle repetitive tasks and large-scale review, but human judgment is still needed for context, escalation, and final decisions.
What are the main risks of using AI for compliance review?
Key risks include bias, over-reliance on automated outputs, data privacy concerns, and inaccurate or incomplete results. Human oversight remains essential.
How do I know whether an AI tool is compliant with privacy rules like GDPR?
Ask vendors about data handling, storage, residency, security controls, and relevant compliance certifications. Make sure the tool fits your privacy obligations and internal policies.
What training does a team need?
Training depends on the platform. Most teams need basic training on document loading, review workflows, and interpretation of outputs. More advanced tools may require additional setup and model training.
How quickly can I see results?
Many teams see time savings quickly, especially in high-volume document review. Broader benefits, such as better risk management and more consistent review, usually build over time as the team refines the workflow.
Conclusion
AI is becoming a practical part of compliance review for legal and regulatory teams. Used well, it can speed up document review, improve consistency, and help teams identify risk earlier. The best results come from choosing a tool that matches your compliance needs, data type, and workflow.
Whether you need contract analysis, eDiscovery support, or financial crime screening, AI can make compliance review more efficient. But it works best when paired with human oversight, clear review standards, and strong governance.