TLDR
- Gartner found that general counsel are increasingly prioritizing AI adoption, skills development, and contract analytics to manage risk and cut costs, reflecting growing top-down pressure from CEOs to integrate AI into legal workflows.
- Legal leaders are urged to strengthen AI risk management, build AI literacy, and learn from peers’ use of generative AI to balance innovation with oversight and avoid misuse.
- Contract analytics is emerging as a key efficiency driver, offering digital insight into contracts and potential savings opportunities – but success depends on careful planning and team readiness.
AI and contract analytics are becoming urgent priorities for general counsel (GC), according to a new survey from Gartner.
The July 2025 survey of GC found that 36% are prioritizing AI adoption, building of AI skills, or improving AI risk management in their departments or organizations, while another 9% are focused on using contract analytics to manage risks and reduce costs − outpacing other operational concerns such as defending departmental budgets or initiatives.
“AI adoption, skill-building and risk management are really getting to be a priority,” said Laura Cohn, director of research in Gartner’s Legal and Compliance Practice, in an interview with The AI Innovator. Since ChatGPT launched in 2022, “it’s been a slow boil, but it really now seems to be a strategic imperative.”
The other trend Gartner found was that contract analytics is gaining ground, Cohn added. Advanced contract analytics systems refer to a set of new tools that enable legal departments to analyze their contracts, review risk, and extract data. It gives legal departments a digital view of contracts instead of having to go through them manually, according to Dian Zhang, senior research principal, also at Gartner’s Legal and Compliance practice.
Cohn and Zhang attribute the new urgency partly to top-down expectations. “Building AI into the business is an imperative for CEOs,” Cohn explained. “General counsel are getting pressure from the top to weave AI into workflows, make sure they understand the risks, and know how to use it.”
Zhang added that a slowing economy amplifies the business case: Legal departments can drive measurable value by finding ways to save money within contracts or through renegotiation. “Those are all real money,” she said. “Legal departments can help contribute to that business value.”
For GC adopting AI, Gartner recommends the following best practices:
- Sharpen AI risk management.
Legal chiefs are urged to identify and mitigate the most significant risks associated with their organization’s AI use, establishing clear policy foundations for risk tolerance, decision rights, and disclosure obligations. Cohn emphasized that peer governance models − how other companies organize AI oversight − can help GC determine the best fit for their own structures. To be sure, the type of risk would depend on the organization itself. “If, for example, you’re an organization that uses a lot of personal data or has a lot of personal data, privacy would be a key risk for you,” Cohn explained.
- Learn how other legal teams use generative AI.
Legal leaders should learn from peers and outside counsel who are experimenting with generative AI to streamline work such as enforcement-trend analysis or hotline case intake. According to Cohn, some departments share cross-functional insights internally, while others lean on their law firms to get some insights. While sharing generative-AI integration wins is important, so too is sharing losses. Cohn recalled a legal team’s review of an AI-generated summary of a new regulation and discovered that “the generative AI actually missed a couple of key points that were important for the organization.”
- Upskill the legal team on AI.
Building AI literacy across legal functions is essential, according to the Gartner report. Zhang said that understanding AI’s limitations is the first step. “Know what it can do and what it cannot do for you is really important, because we still see a few stories about lawyers misusing AI, submitting cases without doing reviews, which is horrifying to hear. When you have AI that can spit out information that seems so legitimate, it actually makes that human review more important.” Cohn added that such training is not only prudent but increasingly mandated − AI literacy provisions are included in the EU AI Act.
- Prioritize contract analytics use cases.
Vendor selection, readiness of people, processes and data are important considerations before implementation. Done right, contract analytics can help speed up contract processes, reveal risks, and identify renegotiation opportunities. But this effort will take time and careful preparation. “It really is a very comprehensive journey,” Zhang said. “It’s not going to be achieved overnight.”
Lessons for smaller practices
Although Gartner’s research primarily targets in-house legal departments, Zhang said that the principles extend to smaller firms and solo practitioners. “One thing you want to avoid is a big catch-up game. Of course, you’ll have different complexity or risk exposure but it’s the same concept − paying attention to tools you could use and learning lessons from others to help you get up to speed faster.”
Both Cohn and Zhang cautioned that AI’s ultimate return on investment is still uncertain. “The jury’s out,” Cohn said when asked whether AI is primarily a driver of ROI or risk mitigation. Zhang agreed: “This is early days. … Technology is evolving, it’s moving very fast, and we’re still constantly monitoring that.”
Nevertheless, the research points to clear momentum. With CEOs pressing for transformation and legal leaders seeking efficiency, Gartner expects continued progress through 2026. “Time will tell whether they’ll have success in getting their teams to use it,” Cohn said, “but they’re going to keep pushing forward given the push from above.”
I believe that AI ican be a valuable tool, but must be heavily monitored in order to reduce risk to a person’s usage of it, including their personal usage.