Artificial Intelligence & Robotics: New lawyers are expected to be AI savvy
AI is no longer a bonus skill. It's baseline. An annual survey of more than 1,800 law students, faculty, and practicing lawyers found clear expectations for AI competence from day one.
According to Bloomberg Law's 2026 Path to Practice Survey: Bridging the Gap, firms want new hires who can work with AI without creating risk-or rework.
What firms expect on day one
- 76% of attorneys expect graduates to cite-check AI-generated materials.
- 63% expect a working grasp of AI-related legal ethics.
- 14% expect basic prompt engineering skills.
Legal education hasn't caught up
Only 11% of faculty say their law school requires professors to take AI training. About two-thirds offer optional workshops, and 20% offer none.
On the student side, just 20% of 3Ls report any proficiency with generative AI as legal tech. That gap turns into lost time, higher supervision costs, and preventable errors in practice.
Why this matters for your practice
Unchecked AI output can introduce bad cites, fabricated facts, and confidentiality leaks. That's a direct hit to client trust, ethics, and the bottom line.
Competence now includes technology. See ABA Model Rule 1.1 (Comment 8) on keeping up with relevant tech-AI falls squarely in that bucket.
What law schools and employers can do now
- Set a clear AI policy: disclosure requirements, approved tools, and no-go zones for confidential data.
- Make cite-checking nonnegotiable: every AI-assisted output gets source verification and a log of checks performed.
- Teach prompt hygiene: precise instructions, staged prompts, and reproducible workflows to reduce hallucinations.
- Protect confidentiality: redaction protocols, private/enterprise AI where possible, and audit trails.
- Integrate into coursework and training: research memos, contract clauses, and deposition outlines with AI + human review.
- Assess performance: rubrics that score accuracy, sources, reasoning, and ethical compliance-not just speed.
What 3Ls and new associates should focus on
- Core use cases: first-draft research, case summaries, issue spotting, clause comparisons, and style edits-always verified.
- Prompts that work: role + task + constraints + sources + format. Save your best prompts as templates.
- Verification checklist: citations traced to primary sources, date checks, jurisdiction fit, and known-false "hallucination" sweeps.
- Ethics guardrails: no client data in public models, clear disclosure where required, and supervising attorney sign-off.
- Build proof of skill: a small portfolio of AI-assisted briefs, research memos, or contract redlines with your verification notes.
Training options if your institution doesn't offer them
If you need a fast track on prompts, verification, and policy, consider structured courses. Useful starting points:
- AI courses by job function for role-specific learning paths.
- Prompt engineering modules to build repeatable workflows.
Bottom line
AI literacy is now a hiring filter. Firms expect new lawyers who can use AI effectively, verify rigorously, and uphold ethics without hand-holding.
The gap is clear-and fixable. Build the skill, prove it with your work, and you'll stand out fast.
Your membership also unlocks:
