AI Comes for BigLaw Staff: What This Means for Your Firm
Talk about AI taking lawyers' jobs often gets waved off. It's harder to dismiss now that AI-linked cuts have hit business professionals at a top firm.
Sources indicate Baker McKenzie has rolled out a large staff reduction across global business services. The cuts reportedly touch IT, knowledge, admin, DEI, leadership & learning, secretarial, marketing, and design. The number circulating: roughly 700 roles, under 10% of staff.
What the firm said
The firm noted it reviewed business professional functions "to position the firm for continued growth and remain agile," including the use of AI, process efficiencies, and targeted investment. After that review, some roles will be phased out and others will evolve, subject to consultation. They emphasized support for impacted colleagues.
The signal to the market
- AI impact starts where repeatable tasks live. Back-office functions move first. Fee-earner workflows won't be far behind.
- This isn't a single-office tweak. It's a global reset of how work gets done and who does it.
- Under 10% sounds small. For operations, it's a major shift in structure, skills, and tooling.
What law firm leaders should do now
- Run a task inventory: Break work into units. Flag items fit for automation (scheduling, intake, invoice review, conflicts checks, pitch content, knowledge tagging). Keep humans on judgment, exception handling, and client touchpoints.
- Redesign roles, not just headcount: Convert legal assistants to client service coordinators. Shift KM to model librarianship, prompt standards, and quality review. Build "AI ops" into legal ops.
- Set AI governance: Data controls, privilege boundaries, vendor risk, human-in-the-loop, and accuracy thresholds by task type. Require audit trails for AI-assisted work.
- Fix pricing and WIP rules: Stop billing human hours for machine tasks. Use fixed fees or value pricing for AI-augmented workflows, with clear scope and acceptance criteria.
- Pick your stack with intent: Standardize on a small toolset. Integrate with DMS, timekeeping, intake, and CRM. Measure cycle time, error rates, and rework before and after.
- Train for new leverage: Prompting, workflow design, retrieval (RAG) basics, and verification. Create internal playbooks and sandboxes for safe practice.
For individual lawyers and staff
- Become the supervisor of AI, not its rival: Learn to spec tasks, craft prompts, build test sets, and review outputs with a checklist. Your value rises when you can direct systems and guarantee quality.
- Keep a portfolio: Track examples where you shipped faster, cheaper, or cleaner with AI assistance. Bring proof to reviews and clients.
- Protect client data: Use approved tools. Mask sensitive facts. Log what you submit and what comes back.
- Specialize where judgment rules: Courtroom advocacy, complex negotiations, regulatory strategy, and high-stakes counseling are less automatable. Pair that with AI fluency and you're hard to replace.
Practical next steps (start this quarter)
- Pick three workflows per practice and run controlled pilots. Time them. Score quality. Keep what beats baseline.
- Stand up a cross-functional AI council (IT, KM, legal ops, risk, finance, partners) with a 90-day roadmap and public metrics.
- Update engagement letters and client comms to explain AI use, review standards, and data protection.
- Offer opt-in transition plans for impacted roles: reskill pathways, certifications, and internal mobility.
This is a hard moment for the professionals affected. It's also a clear message: AI is now part of firm economics. The firms and lawyers who learn to pair judgment with automation will set the pace. The rest will follow it.
Resources to upskill
- AI courses by job role - curate learning paths for legal, ops, KM, and marketing.
- AI Automation Certification - build skills for scoping, prompting, and quality control.
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