Best AI Tools for Lawyers in 2025–2026

Artificial intelligence is reshaping how legal teams operate, delivering faster research, smarter document review, and scalable client engagement. In 2025 and 2026, leading firms combine AI capabilities with rigorous governance to improve outcomes while upholding professional standards. The ecosystem features contract-focused AI, advanced research assistants, and practice-management helpers, all designed to handle large datasets and complex workflows. Notable industry moves include Thomson Reuters’ acquisition of Casetext and the subsequent integration of Casetext’s Copilot-inspired capabilities into Thomson Reuters’ AI roadmap, the rapid maturation of contract-review platforms such as Luminance, and strategic partnerships that broaden access to authoritative legal content through Harvey and LexisNexis.

Contract review and due diligence: automating routine risk assessment

Automated contract review and due-diligence workflows help legal teams process thousands of pages with high consistency. In 2024–2025, providers advanced first-pass analysis, flagging risky clauses, redlines, and missing information so lawyers can focus on high-value negotiation and strategic decisions. Luminance, a pioneer in “legal-grade” AI, has seen adoption across multinational firms and industrial clients, supporting rapid first-pass reviews of standard agreements and complex supply contracts. Large firms and corporate legal departments have highlighted its ability to triage volumes while preserving key insights and audit trails.

Other established platforms focus on clause-by-clause comparison, risk flagging, and evidence-based redlining. Tools in this space aim to reduce manual drafting time and improve consistency across jurisdictions. The result is a more predictable review process, with clear traceability from AI observations to human conclusions. As with any automated analysis, integration with firm policy, document management practices, and security controls remains essential.

Industry reporting indicates continued momentum in this category, with large-scale deployments at global manufacturers and financial institutions. Firms report measurable gains in cycle times, while maintaining strong governance over output quality and data handling. These outcomes align with ongoing investments in AI-powered contracting and due-diligence tooling, supported by both vendor roadmaps and client case studies.

• Luminance: first-pass contract review, risk flagging, and multilingual capabilities for due diligence and negotiations.
• Kira Systems: targeted review and clause spotting with machine learning trained on contract data (common in practice-based deployments).
• LawGeex: contract analysis and policy-compliant redlining to accelerate standard-form reviews.

AI-enabled legal research and drafting: smarter drafting, verified citations

Research and drafting workflows have benefited from AI that can summarize authorities, extract key holdings, and draft initial briefs with inline citations. In 2023–2024, Casetext’s CoCounsel established a benchmark as one of the first AI assistants for lawyers, focusing on research, deposition preparation, and document review. Thomson Reuters’ subsequent acquisition of Casetext integrated its capabilities into a broader AI platform, signaling a trend toward comprehensive, enterprise-grade AI support for legal work. Industry observers noted the awards and recognition Casetext received for AI innovation, underscoring the push toward more capable, citation-aware AI assistants.

Another influential development is the collaboration between Harvey and LexisNexis, which gives Harvey users access to Lexis content and citations within drafting and review flows. This partnership reflects a broader move toward AI assistants that combine generative capabilities with trusted sources, offering lawyers a path to faster drafting without sacrificing verifiable authority. As firms explore these options, they are also building guardrails to address potential AI hallucinations and citation gaps.

In practice, many teams blend AI drafting with human review, ensuring accuracy through citator checks and final human oversight. The goal is to shorten drafting cycles while maintaining high standards for citation integrity and legal reasoning. Industry commentary also notes the evolving nature of product ecosystems, where AI drafting tools are often delivered as part of larger knowledge management or research platforms.

• Westlaw Precision and Lexis+ AI: AI-assisted search with authoritative citators, quick summaries, and drafting support.
• Casetext CoCounsel: AI-assisted legal research and document analysis integrated with Casetext’s databases (now part of Thomson Reuters roadmap).
• Harvey: drafting and review assistant with access to integrated content via LexisNexis collaboration.

Practice management and client communication: AI at the center of workflow

Beyond core legal tasks, practice-management tools with AI components help firms manage matters, track time, and respond to clients with contextual summaries. Clio Duo represents a practical example of AI-enabled practice management, offering automated task reminders, data-driven summaries, and client communications drawn from firm data. Such capabilities are particularly valuable for mid-sized firms seeking to scale operations while preserving personal client service.

Adoption in this space is often tied to secure data handling and interoperability with existing systems. Firms should evaluate how AI features align with their workflows, whether they need firm-wide automation or focused modules, and how data flows between practice-management platforms and contract or research tools.

• Clio Duo: AI-powered assistant within Clio Manage for task automation, summaries, and client-facing communications.
• General workflow automation: AI-enabled assistants can draft client replies, summarize matters, and populate standard forms using firm templates.

Security, privacy, and governance: building trust in AI-enabled practice

As AI tools permeate law firms, safeguarding client data and ensuring responsible use become paramount. Privacy-preserving frameworks are being explored to protect sensitive information when using external AI services. A recent privacy-centered framework outlines approaches to mask and reintroduce confidential data within prompts and responses, supporting safer use of AI across legal tasks. Firms adopting these methods should combine technical safeguards with robust policies, employee training, and ongoing monitoring.

Beyond data handling, professionals should establish governance around model selection, prompt design, data retention, and vendor risk management. Industry observers emphasize the need for clear protocols to handle AI outputs, verify citations, and prevent inadvertent disclosure of client material. As AI adoption grows, these controls help maintain client confidence and regulatory compliance.

• Privacy-preserving AI frameworks: methods to mask PII and control data flow when using external AI services.
• Governance and training: policies detailing how AI outputs are reviewed and stored within the firm.

Adoption strategies for 2025–2026: governance, skills, and risk management

Successful AI adoption hinges on a thoughtful governance model, targeted training, and alignment with client expectations. Firms often begin with a small set of high-impact use cases—contract review, due diligence, or drafting assistance—then scale to broader workflows as confidence grows. Selecting tools that offer strong integration with existing content, citation controls, and secure data handling reduces friction and increases return on investment. Industry coverage notes that large firms are aligning AI investments with AI-ready platforms, enabling a more cohesive tech stack and better knowledge sharing across departments.

Adoption also benefits from practical change-management steps: pilot programs with measurable goals, clear success metrics, and documented best practices for prompt design and output evaluation. Firms that publish internal guardrails and run periodic audits on AI-generated materials tend to maintain higher quality and lower risk. The evolving market provides a variety of options, from specialized contract-review engines to versatile research and drafting assistants, allowing firms to tailor a suite that fits their practice areas and risk appetite.

• Start with high-impact use cases: contract analysis, due diligence, and client communications.
• Establish governance: data handling, prompts, output verification, and retention policies.
• Invest in training: prompt engineering, review workflows, and citation checks to maintain quality.

Representative AI tools for lawyers in 2025–2026: a quick reference

These tools illustrate a broad spectrum: research-centric platforms that emphasize citations and defensible outputs, contract and due-diligence engines, and practice-management assistants that augment everyday workflows. The right mix depends on practice areas, data-handling requirements, and the firm’s governance maturity.

Implementation tips: getting value while managing risk

To maximize benefits, firms should approach deployment with a phased plan. Start with one or two use cases that deliver quick wins, such as first-pass contract review or drafting assistance for routine documents. Establish clear success metrics, including speed gains, error rate reductions, and client satisfaction indicators. Build a lightweight governance framework to govern prompts, source checks, and output storage. As confidence grows, expand to deeper workflows like comprehensive due diligence, complex research tasks, and client communications. This staged approach helps teams adjust to AI, refine processes, and reduce disruption.

Industry commentary emphasizes the importance of verification and human oversight. Even leading AI tools can produce hallucinations or inaccurate citations if not guided by disciplined prompts and governance. Lawyers should treat AI outputs as inputs to expert analysis, validating results against primary sources and maintaining professional responsibility standards. This approach preserves trust with clients while enabling teams to scale operations.

Conclusion: AI as a force multiplier for modern law practice

In 2025–2026, AI tools offer meaningful benefits across contract work, research, drafting, and firm operations. The most successful deployments combine strong tool selection with disciplined governance, targeted training, and ongoing quality checks. As the market evolves, expect continued integrations that blend AI assistants with authoritative content and enterprise workflows, while firms remain vigilant about data privacy and ethical use. The result is a more efficient practice that upholds professional standards and delivers greater value to clients.

Note on industry dynamics: major moves include Thomson Reuters’ acquisition of Casetext, the recognition of CoCounsel as an AI milestone, and partnerships that broaden access to trusted content. These developments signal a trend toward integrated AI platforms that support end-to-end legal workflows. Firms should monitor product roadmaps, security updates, and regulatory guidance to ensure alignment with client expectations and legal obligations.

• Lexis+ AI Lexis+ AI combines advanced natural language processing with trusted primary and secondary sources from LexisNexis. It speeds up research by interpreting queries, suggesting relevant statutes, regulations, and case law, and presenting clear syntheses. The tool uses citation-aware results to help attorneys verify precedents and prepare briefs. It offers document drafting support, with automated outlines, slip sheets, and issue spotting that align with firm procedures. Workflow integrations connect to practice management systems, enabling quicker reference checks, note capture, and collaborative review. Security features protect client information while audit trails support compliance requirements in complex matters. User controls and role protections maintain confidentiality everywhere.
  

• Westlaw Edge Westlaw Edge delivers AI-powered research and analysis for modern legal practice. It combines seamless search across dockets, statutes, regulations, and secondary materials with predictive insights and practitioner-focused dashboards. Features include citation checking, key passages highlighting, and relevance scoring that help lawyers identify persuasive authorities quickly. Automated brief templates, issue outlines, and document assembly tools streamline drafting. The platform supports collaboration with shared folders and real-time annotations, while security controls protect sensitive data and provide clear audit logs. Regular updates reflect evolving law, enabling teams to respond promptly to new developments and evolving standards. Customizable workflows align with processes and billing.
  

• Casetext CoCounsel Casetext CoCounsel uses advanced language models to assist lawyers with research, drafting, and analysis. It can summarize long briefs, locate relevant authorities, and generate concise issue-focused outlines. The tool integrates with Casetext's database to fetch up-to-date case law, statutes, and regulatory materials, while offering citation formatting and flagging potential gaps. In drafting mode, it proposes language for petitions and memos and flags ambiguous terms for clarity. Collaboration features enable team members to leave notes and assign tasks. Privacy controls and access logs help firms maintain client confidentiality and comply with professional standards during matters. The tool emphasizes accuracy and accountability.
  

• Luminance Luminance powers document review with adaptive machine vision and human-in-the-loop validation. It scans contracts, briefs, and filings to identify deviations, ambiguities, and high‑risk terms. The system groups documents by relevance, highlights key passages, and creates exception lists that support risk assessment. Quality controls allow reviewers to annotate, challenge outputs, and route items to specialists. Integrations with matter management platforms streamline intake and version control. Comprehensive audit trails capture decisions and edits. Security measures guard client data, while automated reporting supports compliance, due diligence, and fast, informed decision making. The interface stays intuitive for attorneys reviewing hundreds of pages daily online.
  

• Evisort Evisort automates contract management with AI-powered classification, extraction, and tracking. It reads agreements to pull clause data, dates, and obligations, then stores terms in a searchable library. The system supports lifecycle workflows, renewal alerts, and risk flags that help teams manage volumes efficiently. Advanced search across contracts helps locate precedent clauses, supplier terms, or liability provisions quickly. Collaboration features enable redlines, comments, and task assignments. Extensive audit trails, access controls, and encryption protect sensitive information, while reporting dashboards provide metrics on cycle times, bottlenecks, and compliance readiness. Users tailor roles and templates to match firm standards and approval processes globally.
  

• Harvey AI Harvey AI provides assistant capabilities for legal writers and researchers with an emphasis on drafting support, memo generation, and question answering. It interprets client questions, locates relevant authorities, and suggests language appropriate for filings and briefs. The tool integrates with cloud storage and collaboration suites to enable secure sharing and review. It offers task lists, reminders, and version control to keep teams aligned. It also includes risk indicators and confidence scores for results. Strong data governance and privacy features help firms protect client information and meet professional standards in dynamic practice settings. Users can customize templates to reflect firm policy.