Luisa Crawford
Jun 23, 2026 17:45
AI adoption in legal departments has surged, with 87% of general counsel now using AI to streamline workflows and expand capacity.
Generative AI has rapidly reshaped corporate legal departments, with 87% of general counsel incorporating AI tools into their workflows by mid-2026, according to the latest General Counsel Report by FTI Consulting and Relativity. This marks a dramatic rise from just 44% a year ago and only 20% in 2024. The surge reflects a growing reliance on AI to handle high-volume, repetitive tasks like contract drafting, legal research, and matter intake, freeing up in-house lawyers to focus on strategic work.
For general counsel, the promise of AI lies in efficiency and scale. The technology enables legal teams to process routine requests faster, enhance accuracy, and reduce dependence on costly outside counsel. AI tools such as Harvey, a platform purpose-built for legal work, are designed to ground outputs in citable sources, ensuring lawyers can verify results—a critical requirement in a profession where errors carry significant risks. Harvey has already been adopted by over 1,500 organizations, including 60% of AmLaw 100 firms and 500 enterprise in-house teams.
Why Legal Departments Are Turning to AI
With the scope of legal departments expanding faster than their budgets, AI offers an alternative to traditional scaling methods like hiring additional staff or outsourcing work. According to the General Counsel Report, legal teams are using AI to address challenges such as regulatory tracking, contract management, and knowledge retrieval. These tools allow teams to handle increasing workloads without adding headcount or significantly increasing costs.
One of the most common use cases is contract review and drafting. AI can perform a first-pass review of contracts, flagging non-standard clauses and generating redlines according to an organization’s playbook. Similarly, AI-driven legal research tools streamline the process of identifying relevant statutes and regulations, ensuring teams stay ahead of compliance requirements across multiple jurisdictions. These efficiencies mean that general counsel can redirect resources toward complex matters that require human judgment, such as risk management and negotiating key agreements.
Challenges in AI Adoption
Despite its potential, AI adoption in legal departments is not without hurdles. A June 2026 analysis highlighted that nearly 90% of general counsel still feel resource constraints limit their strategic impact, even with AI-driven productivity gains. A major issue is governance. Many legal departments are still developing policies to ensure responsible use of AI, including protections around data confidentiality, accuracy, and the separation of client matters.
Another concern is shadow AI—when non-legal teams within a company use consumer-grade AI tools to draft contracts or address policy questions without legal oversight. This can lead to exposure risks, such as reliance on incorrect or unverifiable outputs. To mitigate this risk, general counsel are increasingly offering enterprise-approved AI tools that meet security and compliance standards, paired with clear policies on their use.
The Road Ahead
The shift toward AI in legal departments is still in its early stages, with many teams focused on pilots and incremental gains. Measuring ROI remains a challenge, as the benefits often show up in efficiency improvements rather than direct cost savings. However, the long-term potential is clear: AI can transform legal departments from cost centers into strategic enablers by reducing reliance on outside counsel and scaling internal capabilities.
Industry leaders like Harvey are setting the benchmark with AI platforms designed specifically for legal work, offering features like citable sources, matter separation, and seamless integration with existing tools like document management systems. For general counsel, adopting AI is no longer a question of if, but how to roll it out effectively. Starting with high-volume workflows and scaling strategically could be the key to turning AI into a competitive advantage.
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