Law Firms Add AI Leadership: A Practical Playbook for Senior Executives
Top law firms are moving fast to get an AI edge. The latest move: Ropes & Gray hired Gretchen Greene from Meta as its first chief of AI strategy. Greene previously worked at the firm and led AI adoption for Meta's policy and legal teams, bringing a rare mix of technical depth and legal experience.
She will partner with the firm's CIO to set AI direction and deliver measurable client value. The message is clear: AI leadership is now a C-suite-level priority, not an IT side project.
Who's hiring and why it matters
- Ropes & Gray: Hired Gretchen Greene as chief of AI strategy; launched a program allowing first-year associates to allocate up to 20% of annual required billable hours to AI training and simulations.
- Herbert Smith Freehills Kramer: Appointed Ilona Logvinova as global chief AI officer, coming from Cleary Gottlieb.
- Husch Blackwell: Brought in Michael Yang from Adobe.
- Fisher Phillips: Hired Pritesh Patel from Walmart.
- Linklaters: Created a 20-lawyer AI team to apply AI to client matters across the firm.
Since late 2022-accelerated by the release of ChatGPT-firms have moved from experiments to executive-level hires. The goal isn't novelty. It's speed, quality, and client impact.
Executive brief: What this means for your firm
- Client pressure: Corporate legal departments now ask for AI capability in RFPs. Expect scrutiny on security, privilege, and auditability.
- Margin protection: AI can trim research and drafting hours while maintaining quality. Firms that don't adapt will feel rate pressure first.
- Talent model: Work once done by junior lawyers is changing. Upskilling plus new roles (AI leads, data scientists, prompt engineers) is the path forward.
- Risk posture: Data privacy, model accuracy, and hallucinations are board-level risks. Policy and controls must be explicit.
Your AI org blueprint
- Accountability: Appoint a senior AI leader who partners with the CIO and GC. Give them budget and clear KPIs.
- Cross-functional team: Blend legal experts, knowledge management, data science, security, and L&D. Keep it small and outcome-focused.
- Priority use cases: Legal research, first-draft memos, clause comparison, due diligence checklists, deposition prep, client alerts.
- Buy vs. build: Start with vetted vendors integrated into your DMS and productivity stack; build only where your workflows are unique or high-value.
- Controls: Data residency, privilege safeguards, red-teaming, human-in-the-loop review, model selection standards, and logging.
What to measure
- Efficiency: Reduction in time-to-first-draft; research hours per matter; review cycle count.
- Quality: Error rates vs. baseline; peer-review scores; client feedback.
- Adoption: % of matters using approved AI tools; active users per week; training completion rates.
- Financials: Margin lift per practice; write-offs avoided; new revenue from AI-enabled products.
90-day pilot plan
- Weeks 1-2: Select 3 use cases in two practices; define guardrails; set baselines; choose vendors.
- Weeks 3-8: Run controlled pilots with 10-20 lawyers; capture time saved and quality deltas; log issues.
- Weeks 9-12: Publish results; refine playbooks; expand to adjacent workflows; align compensation to adoption where appropriate.
Talent and training strategy
Ropes & Gray's policy to allocate up to 20% of first-year billable targets to AI training sets a clear standard. It signals that skills matter as much as hours.
- Adopt a similar model: Create protected time for AI simulations and tool practice. Tie it to promotions and reviews.
- Role clarity: Define career paths for AI strategy leads, knowledge engineers, and data stewards inside practice groups.
- Certification: Use external programs to standardize proficiency across offices and practices.
Governance checklist for firm leaders
- Written policy on approved tools, data handling, and client consent.
- Model evaluation standards (accuracy, bias checks, hallucination rate).
- Privileged data safeguards, redaction defaults, and secure prompts.
- Incident response plan and audit trails for AI-assisted work.
What's next
- More firms will appoint chief AI officers and build dedicated AI teams.
- Clients will expect documented AI controls and measurable outcomes.
- Practice groups will compete on speed-to-draft and matter predictability.
If you're formalizing training, explore curated programs for business and legal teams: Latest AI courses and AI courses by job.
Context note: The surge began after public releases of generative AI tools like ChatGPT, and hires now increasingly come from tech companies such as Meta. Law firm leaders are turning that momentum into structured capability-backed by governance, incentives, and clear KPIs.
Your membership also unlocks:
