Legal Is Already Ahead on AI—It’s Time to Track It with Legal AI KPIs

As organizations begin tracking AI usage across departments, many are surprised to learn that the general counsel is one of the most active AI users, often more than executives in marketing, IT, or product. As GCs, we sit at the crossroads of risk and strategy. We’re asked to respond faster, with fewer resources, to increasingly nuanced legal, regulatory, and operational demands. Some of us may be the only legal person at a company. AI is becoming essential to how we deliver value to the business, or just help us get home in time to have dinner with the family. 

Like many GCs, I use AI to review contracts, summarize new regulations and draft emails. But as our team’s AI adoption deepens, I am realizing something important: we need a better way to measure how, where, and why we’re using AI and the value it’s actually delivering. To demonstrate the value of this adoption, legal teams must begin incorporating AI usage into their KPIs to show how they’re driving efficiency, leveraging data, and aligning with broader business goals.

That’s why I am working with my team to implement formal goals and KPIs around AI adoption and its impact both for myself and our legal department. I recommend all general counsel begin this process now so they have enough feedback and data in preparation for their end-of-year reviews.

What do Legal AI KPIs look like?

We’re aligning our AI-related KPIs to reflect the different levels of responsibility and impact across our function.

For instance, as general counsel, my KPI’s are:

1. AI Adoption Rate in Legal Operations

• Percentage of legal workflows (e.g., contract review, summarizing regulations) using AI tools

2. AI-Driven Efficiency Gains

• Reduction in average contract review/turnaround time due to AI (i.e., reduce contract review cycle time by 30% through AI-assisted tools by year-end)
• Percentage decrease in manual legal research hours
• Percentage decrease in questions to outside counsel

3. Risk Mitigation and Compliance

• Number of AI-related legal/compliance incidents (e.g., hallucination) detected and resolved
• Percentage of AI models and vendors reviewed for legal, privacy, and ethical compliance (i.e., ensure 100% of new AI deployments undergo legal and privacy review before launch)

4. Training and Upskilling

• Percentage of legal team trained on AI tools and AI risk management
• Number of AI/tech-focused CLEs or internal workshops completed per quarter, including AI prompting classes (i.e., deliver quarterly AI risk and ethics training to the legal and compliance teams)

5. AI Governance and Policy Implementation

• Completion and regular review of AI governance policies (e.g., responsible AI use, model audit protocols)
• Percentage of business AI initiatives reviewed by legal for compliance and risk

6. Data Privacy and Security

• Percentage of AI projects with documented privacy impact assessments
• Number of privacy/security incidents involving AI systems

7. Stakeholder Engagement

• Number of cross-functional meetings with IT, compliance, and business on AI strategy and risk
• Legal and privacy team participation in AI steering committees or governance boards

I have different goals for my team, such as:

1. AI-Assisted Task Completion Speed

• Time reduction percentage on routine tasks like contract review, research, and drafting. (i.e.,reduce SAAS contract review time from 2 hours to 30 minutes using AI tools)

2. AI Tool Utilization Rate

• Percentage of eligible tasks where AI tools were used (i.e., drafted demand letter using an AI tool to create the first draft)
• • Present on 3 ways a team member used AI during weekly team meetings
  • Show consistent adoption rather than sporadic use

3. AI-Enhanced Output Quality

• Error reduction in documents created with AI assistance
• Error reduction in reviewing and summarizing agreements

4. AI Learning & Process Improvement

• Number of new AI workflows or prompts developed
• Process improvements identified through AI experimentation
• Training or knowledge sharing provided to colleagues on AI tools

5. AI ROI Contribution

• Hours saved per week through AI usage
• Cost avoidance (reduced need for outside counsel, overtime, etc.)
• Value of additional work capacity created through AI efficiency

For the legal department, my team and I created other KPIs like the adoption rate (percentage) of team members actively using our AI tool. 

Leading with Metrics, Not Just Mandates

By establishing these legal AI KPIs now, we’re positioning legal as a strategic partner that drives measurable business value through technology. The data we collect over the next six months will become the foundation for budget requests, headcount justifications, and demonstrating legal’s contribution to enterprise-wide efficiency gains.

The question isn’t whether AI will transform legal departments; it’s whether we’ll lead that transformation with clear metrics and accountability, or find ourselves explaining why we didn’t act when we had the chance. The general counsel who can walk into their year-end review with concrete AI performance data will have a very different conversation than the one who cannot.