Top :Harvey: AI Use Cases Across Legal Practice Areas
Harvey’s most common applications across practice areas and groups within law firms and in-house legal teams.
What does Harvey do for legal teams, and where is it being used today? This is the first question we hear from law firm partners running an AI evaluation, in-house counsel scoping a rollout, and innovation leads mapping AI into firm strategy. Over the last two years, AI use cases in law have grown from pilots to daily practice across law firms and in-house teams. Harvey’s AI legal platform is built for use across both types of organizations. This guide answers the question with a structured view of how Harvey is being used across transactional work, litigation, in-house teams, and the industry workflows that cut across both.
The data behind this analysis comes from anonymized customer activity inside Harvey Assistant, processed through machine learning classifiers and grounded in Harvey's enterprise security standards. More than 142,000 lawyers across 1,500+ organizations in 60 countries use Harvey to research, draft, review, and collaborate. For deeper takes on specific workflows, see our companion piece on how legal teams use Harvey across daily work, and the Harvey In Practice series covering M&A teams and litigation teams.
Key Takeaways for Top Harvey Use Cases:
- For transactional teams, the most common Harvey use cases are drafting (generating clauses and full agreements), due diligence (review at portfolio scale), and deal management (coordination across signing and closing).
- For litigators, the most common uses are drafting and case management, with substantial application in regulatory and advisory analysis, case law research, document review (discovery), and trial preparation.
- In-house legal teams use Harvey for contract review, supplier agreement management, regulatory tracking, and portfolio-level visibility, with users saving an average of more than 25 hours per month.
- Harvey is in production across more than 500 practice groups, with 25,000+ custom Workflow Agents codifying firm-specific and organization-specific expertise across every matter.
- Adoption is consistent across firms and in-house teams: Harvey maintains a 92% monthly adoption rate across the customer base.
What are Harvey AI Use Cases?
Harvey AI use cases are the legal tasks that lawyers and legal teams complete using the Harvey platform. The most common use cases fall into four buckets: transactional work (drafting, due diligence, deal management, research and strategy, corporate advising), litigation work (drafting, case management, regulatory and advisory analysis, case law research, document review, trial preparation), in-house legal work (contract review, regulatory tracking, supplier agreement management), and the industry-specific workflows that span both private practice and in-house teams.
Every use case maps to one or more product surfaces on the Harvey platform: Shared Spaces for seamless client collaboration, Assistant for natural-language analysis and drafting, Vault for large-scale document review, Knowledge for research grounded in authoritative sources, Workflow Agents for codified multi-step processes, and Harvey for Word for in-document drafting and redlining. The methodology below explains how we identified these use cases from real customer activity rather than an internal hypothesis.
How We Identified These Use Cases
All data referenced in this analysis was collected anonymously, with explicit customer approval, under Harvey's enterprise security and data privacy standards. The data is treated as eyes-off, meaning the Harvey team does not view the underlying queries. Machine learning classifiers group queries into use cases and practice groups, eliminating the risk of data contamination or exposure.
We analyzed tens of thousands of queries from Harvey Assistant across large law firms, mid-sized firms, in-house legal departments, and professional services teams. The resulting use case map covers more than 500 practice groups and continues to expand as customers codify new workflows. The two heat maps below visualize the most prevalent practice groups within transactional and litigation work; the shading reflects how prevalent each use case is within each practice group.
Top Harvey AI Use Cases for Transactional Work
For transactional work, the heat map below reveals broad use cases for Harvey in drafting (generating clauses and documents), due diligence (reviewing documents and identifying risks), and deal management (planning and coordinating processes).
We also see substantial use cases in research and strategy, with additional applications in broader corporate advising and compliance. The transactional heat map covers the most prevalent practice groups: Public Company M&A, Banking and Finance, Capital Markets, Private Equity, Tax, Real Estate, Compensation and Benefits, Funds, Public Company Advisory, and IP Transactions. Use cases shown across the columns include Risk Assessment and Compliance, Due Diligence, Drafting, Negotiation Strategy, Legal Research, Transaction Structuring, Deal Management, and Corporate Strategy and Advising.
1. Contract and Document Drafting
Transactional lawyers use Harvey to generate clauses, sections, and full agreement drafts grounded in firm precedent. Drafting and redlining happen inside Microsoft Word through Harvey for Word, the in-document add-in that places AI in the same surface where lawyers already work. Custom Workflow Agents codify firm-specific drafting patterns so the same standards apply across every matter.
Customers have built more than 25,000 custom Workflow Agents on the platform, with drafting and document generation among the most common patterns. Custom workflows for lease summarization compress hours of manual review into minutes, a pattern that recurs across firms that have invested in workflow customization.
Within Harvey: Assistant, Harvey for Word, Workflow Agents, Agent Builder
2. Due Diligence and Document Review
For diligence, Harvey handles document review at a portfolio scale through Vault, which supports up to 100,000 documents per project. Review tables extract structured data across the full agreement set in a single query, parsing customer contracts, supplier agreements, leases, employment files, and IP assignments in parallel. The reviewer's time shifts from confirming whether every document was opened toward working through the structured exceptions Vault surfaces, which is the core mechanic of AI legal due diligence at portfolio scale.
GSK Stockmann, a European corporate law firm, partnered with Harvey to co-design a generative AI (GenAI) workflow for the end-to-end due diligence process, from scope determination through report delivery. PwC's deal team has documented similar gains across live M&A engagements. The compounding effect is meaningful: the diligence workflow that took hours on the first matter completes in minutes on every matter that follows.
Within Harvey: Vault, Workflow Agents, review tables.
3. Deal Management and Coordination
Beyond drafting and diligence, transactional teams use Harvey for the coordination work that runs alongside every deal: signing checklists, closing checklists, post-close integration tracking, and structured summaries shared with the broader deal team. Workflow Agents codify these patterns so the same checklist runs against every deal of a similar type, with the partner reviewing structured output rather than starting from scratch.
For smaller teams and boutique firms where deal staffing is leaner, the workflow scaling has an outsized impact. A single Workflow Agent built once runs across every matter that fits the pattern, freeing associates to focus on judgment-intensive work.
Within Harvey: Workflow Agents, Agent Builder, Microsoft integrations.
4. Corporate Advising and Compliance
Transactional teams also use Harvey for ongoing corporate advisory work: regulatory tracking, policy analysis, and structured responses to business-team questions that draw on both firm precedent and external regulatory materials. Harvey Knowledge connects Assistant to more than 500 legal data sources, including LexisNexis for US case law, statutes, and regulations, so answers are grounded in authoritative external sources alongside the firm's institutional knowledge.
Within Harvey: Assistant, Knowledge, Vault.
For a deeper look at how full M&A teams put Harvey to work across the deal lifecycle, see Harvey In Practice: How M&A Teams Use Harvey. To explore Harvey for transactional work specifically, see our transactional solutions overview.
See how Harvey fits your transactional workflow. Request a Demo.
Top Harvey AI Use Cases for Litigation
Like transactional lawyers, litigators frequently use Harvey for drafting and case management. They also consistently find use cases in regulatory and advising work, reviewing legislation and regulation, and how they apply to particular fact patterns. Other substantial legal AI use cases include case law research, document review and analysis (discovery), and advocacy strategy for trials and oral arguments. The litigation heat map covers the most prevalent practice groups: Antitrust, Bankruptcy, Data Privacy and Cybersecurity, Employment Litigation, International Arbitration, IP Litigation, Product Liability, Regulatory and Public Policy, Securities Litigation, and White Collar Investigations. Use cases shown across the columns include Case Law Research, Transcript Analysis, Regulatory and Advising, Drafting, Trial Preparation and Oral Argument, Case Management, Document Review and Analysis, and Analysis of Litigation Filings.
1. Case Law Research and Authority Analysis
Harvey supports case law research grounded in authoritative legal sources through Assistant and the connected Knowledge sources. Through Harvey's partnership with LexisNexis, answers to questions involving US case law, statutes, and regulations are accessible directly inside Harvey. Lawyers ask questions in natural language, receive cited answers, and click into source authorities to verify reasoning before relying on it. The output is structured for the next step of the work, whether a memo, a brief section, or a client update, not a generic summary.
For litigation teams, the highest-value applications are first-pass issue spotting and authority analysis across large source sets, with the lawyer applying judgment on materiality and strategy. Citation grounding matters here: every output ties to the source authority that supports it, consistent with the ABA's Formal Opinion 512 guidance on competence with GenAI tools.
Within Harvey: Assistant, Knowledge, LexisNexis integration.
2. Discovery and Litigation Document Review
Harvey supports review across discovery productions and large litigation document sets at portfolio scale, with Vault supporting up to 100,000 documents per project. Review tables extract data points across the full document set in a single query, surfacing patterns that would be difficult to spot through document-by-document review. Transcript analysis and analysis of litigation filings run on the same underlying capability. For the underlying speed-up, see our breakdown on how Harvey accelerates diligence review.
Within Harvey: Vault, review tables, Workflow Agents.
3. Drafting Briefs, Motions, and Client Memos
Litigation drafting work, including briefs, motions, client memos, and deposition outlines, moves from blank page to first draft significantly faster with Harvey. Drafting happens inside Harvey for Word, with firm precedent and prior work available alongside the document being edited. Workflow Agents apply firm-specific drafting patterns consistently across matters, so the standards a senior partner sets at the firm level travel into every associate's draft.
Within Harvey: Harvey for Word, Workflow Agents, Knowledge.
4. Regulatory and Advisory Analysis
A substantial share of litigation use is in regulatory and advisory work: reviewing legislation, regulation, and agency guidance, then producing a structured analysis of how those authorities apply to a particular fact pattern. Harvey Assistant handles this end-to-end, from initial research through structured analysis, with every citation traceable back to its source.
Within Harvey: Assistant, Knowledge.
5. Trial Preparation and Oral Argument
For trial preparation and oral argument, Harvey supports authority analysis, deposition review, exhibit organization, and structured argument synthesis across the full case record. The output is built for active use in trial, with citations that the lawyer can verify under time pressure.
Within Harvey: Assistant, Vault, Workflow Agents.
For a deeper look at how full litigation teams put Harvey to work across the case lifecycle, see Harvey In Practice: How Litigation Teams Use Harvey. To explore Harvey for litigation work specifically, see our litigation solutions overview.
See how Harvey fits your litigation workflow. Request a Demo.
How In-House Legal Teams Use Harvey
In-house legal teams run a distinct usage profile shaped by lean headcount, high contract volume, and constant pressure between business-team velocity and risk oversight. Harvey customers in this segment have published consistent results across the most common in-house workflows.
The work centers on first-pass review of NDAs, supplier agreements, customer contracts, and partner agreements, with firm playbooks applied automatically inside Harvey for Word. Routine deviations are flagged for review; standard agreements move through the workflow with minimal manual intervention. HubSpot's Legal Operations team selected Harvey for exactly this pattern. Beyond individual review, in-house teams use Vault review tables for portfolio-level analysis across thousands of contracts: clause prevalence, renewal exposure, change-of-control coverage, and risk concentration in specific contract types.
Adoption signals across the in-house base are consistent. Repsol reported 96% Harvey adoption across its legal department after integrating Harvey into existing workflows, and Harvey users save an average of more than 25 hours per month. For the full picture on in-house workflows, see our in-house solutions overview, how Harvey's own legal team uses Harvey, and our breakdown on how Harvey saves lawyers' time.
Harvey AI Use Cases Across Industries
Beyond the practice-group view, Harvey usage also organizes around industry-specific workflows. Private equity teams use Vault and custom Workflow Agents for portfolio-scale diligence and side-letter analysis. Real estate teams use Harvey for lease summarization and acquisition document review. Banking and financial services teams use it for multi-jurisdiction regulatory tracking. Insurance, healthcare, and life sciences teams use it for compliance and regulatory advisory work. The codified expertise behind each industry workflow lives in Agent Builder, where customers have built reusable processes across more than 500 practice groups. For practice-area depth across industries, see Harvey Agents.
The Harvey Platform Powering These Use Cases
Harvey is a unified legal AI platform. The use cases above surface through integrated capabilities, not separate point tools, and that integration is what lets the same firm precedent, the same playbooks, and the same source-grounded answers flow from research to analysis to drafting to bulk review without leaving the platform.
The capabilities behind the work include Assistant for natural-language analysis and deep reasoning, Knowledge for connection to legal data sources alongside firm institutional knowledge, Vault for large-scale document organization and review, Workflow Agents and Agent Builder for codifying firm expertise as reusable multi-step systems, and Harvey for Word for drafting and redlining inside Microsoft Word. Document management system integrations cover iManage, NetDocuments, SharePoint, and Google Drive, available through the broader Harvey ecosystem. Harvey shared Spaces make it easy to build collaborative experiences so clients can work alongside your team on key documents, knowledge gathering, and more.
Harvey is built on enterprise-grade security: SOC 2 Type II, ISO 27001 and 27701, GDPR and CCPA compliance, encryption in transit and at rest, BYOK support, and matter-level access controls. Customer data is not used to train Harvey's models.
See Harvey AI in Action for Your Team's Use Cases
The use cases in this guide represent a sampling of how Harvey is used today, across law firms, in-house legal teams, and professional services. The shape of the work, whether drafting, diligence, research, document review, regulatory analysis, or contract management, stays consistent across teams. What varies is the precedent, the playbook, and the practice-specific standards each team brings to it. The Harvey AI legal platform stays consistent across every team; the codified expertise is what changes.
The best way to see how Harvey fits a specific team's use cases is to walk through a sample workflow on the matter types the team handles. Request a demo, and the Harvey team will work through your use cases with your playbooks and your document types, so you can see what the platform does on your real workload. For teams running a formal RFP or platform review, download the seven key criteria for evaluating AI solutions for law.
Ready to see Harvey on your team's real workload?
