Will AI Replace Legal Jobs in Peru? Here’s What to Do in 2025

Will AI replace legal jobs in Peru in 2025? Not entirely, but the landscape is changing fast: Peru's risk-based AI framework (Law 31814) and recent criminal-code amendments that penalize AI-enabled harms - including deepfakes and fraud under Law No.

32314 - mean regulators are reshaping what's legal and what's off-limits, so lawyers who only do routine drafting face real disruption. At the same time scholars warn Peru's “regulatory boom” risks being performative unless enforcement and depth follow, and global legal practice is shifting from hype to practical AI implementation that boosts efficiency and client value.

That mix of tougher rules and practical AI tools creates an opening for Peruvian lawyers to upskill in prompt design, risk assessments, and vendor due diligence - practical skills taught in Nucamp's AI Essentials for Work program to help legal teams move from defensiveness to advantage.

Peru AI risk-based regulatory framework (Law 31814), Peru criminal-code AI amendments (Law No. 32314), and practical training like the Nucamp AI Essentials for Work syllabus are starting points for action.

"If you create value, you win. Focus on your clients. Focus on value." - Danielle Benecke, Baker McKenzie (Legalweek 2025)

In 2025 the reality in Peru is pragmatic: AI is not a futuristic threat but a day-to-day force reshaping legal workflows, pressured from both the regulator's “boom” of AI bills and the fast uptake of tools that cut routine hours; Peru's regulatory surge is critiqued as “quantity without depth” (Harvard Kennedy School analysis of Peru's AI regulatory boom), even as firms and in-house teams push AI into research, drafting and contract work to meet client demand.

2025 data show heavy practical use - legal research and clause drafting lead adoption - so Peruvian lawyers who treat AI as an always-on assistant (not a replacement) can reclaim time for strategy and client counsel; think of it as swapping repetitive file-sorting for a tireless junior that surfaces key precedents and flags risk.

The winners will pair clear AI policies with vendor due diligence and concrete training, turning compliance pressure into a competitive edge rather than a compliance burden (Juro State of In‑House 2025 legal research and drafting adoption statistics).

“This transformation is happening now.”

Peru's immediate AI collision course is with the high-volume, repetitive work that machines already do faster and cheaper: first‑pass document review and e‑discovery, early data assessment that surfaces key threads in litigation, clause extraction and contract triage, and routine legal research and summarization - tasks that can be processed “by the hour” at scale (think thousands of documents per hour) rather than by billable human time.

Platforms that automate initial review are reclaiming work once farmed out to managed‑review teams, while contract‑review tools now extract clauses, flag deviations and triage risk so lawyers spend less time hunting and more time advising; see Syllo analysis of GenAI-driven document review and the Juro guide to AI contract review for how these use cases are maturing.

That said, Peru's risk‑based AI rules and tight privacy regime mean anything involving sensitive profiling, biometric or neurodata, or high‑stakes automated decisions will face strict oversight or pre‑market checks, so firms should prioritize automating low‑risk, high‑volume tasks and keep humans in the loop for anything touching regulated data or strategic judgment (use DPIAs and vendor due diligence to stay compliant; the Future of Privacy Forum regional AI risk overview explains the emerging risk framework).

“Rather than outsource review to managed review providers, law firms are using platforms that enable automated first-level review, like Syllo, to take large reviews (and the revenues) back in house.”

Even as Peruvian firms adopt AI for speed and scale, several core legal strengths remain stubbornly human: judgment that weighs competing equities, courtroom advocacy that reads tone and subtext, and the ethical accountability clients expect when lives or livelihoods are on the line.

Peru's rapid regulatory push may be “quantity without depth,” which actually creates space for lawyers to provide the deep, contextual analysis machines lack (Harvard Kennedy School analysis of Peru's AI regulatory boom); likewise, scholarship on AI in the courtroom stresses that speed and pattern matching cannot replace real-time strategy, empathy, and the visible responsibility a human advocate brings (Analysis: AI in the courtroom - why human advocates remain necessary).

In practice this means Peruvian lawyers should treat AI as a tireless research assistant while preserving human-led tasks - ethical judgments, narrative framing, cross-border nuance and client reassurance - like a lighthouse that guides a ship through fog: indispensable, local, and hard to automate.

Risks for Peruvian legal teams in 2025 center on a global pattern that has already produced real courtroom pain: generative AI can “hallucinate” plausible but false authorities, and leading studies and reporting show this isn't rare - general-purpose chatbots hallucinate far more than legal tools, bespoke systems still err (Stanford's RegLab/HAI benchmarking), and July 2025 saw “over 50” reported fake‑citation incidents across jurisdictions - examples that turned into fines, disqualification and referrals to bar investigators in multiple U.S. courts.

Those headlines matter in Lima because the same failure modes - fabricated cases, misquoted authority, and misplaced trust in RAG claims - trigger sanctions, wasted adversary time, and reputational collapse.

Practical regulatory concerns for Peru therefore include mandatory verification of every AI‑sourced citation, mandatory training and logging of AI use, vendor transparency and DPIAs, and documented human review workflows that courts can audit.

Treat AI output as an unverified draft, not authority: the vivid risk is simple and concrete - a brief that looks airtight but cites a case that does not exist can cost a client the case and a lawyer their license (World Lawyers Forum report on AI hallucinations in court, Stanford HAI RegLab benchmarking of legal AI hallucinations, VinciWorks report on over 50 fake cases cited in July 2025).

“Keeping humans in the loop to review, refine, and verify AI output - and allowing AI to analyze human drafts - ensures that efficiency is maximized without compromising ethical standards.”

A concrete 10‑step action plan for Peruvian lawyers and firms in 2025: 1) classify existing and proposed AI uses under Peru's risk‑based Law 31814 and run DPIAs for high‑risk systems (Peru AI regulation (Law 31814)); 2) map low‑risk, high‑volume tasks (document triage, clause extraction) to automate first‑pass work; 3) prioritize pilots that align with firm strategy and measurable ROI, not novelty (AI pilots that drive profits at tech firms); 4) invest in data hygiene and KM so Copilot‑style tools draw from trustworthy sources; 5) build vendor due diligence and contract clauses that enforce transparency and incident reporting; 6) mandate human oversight, citation verification and logging - remember a single hallucinated citation can cost a client the case and a lawyer their license; 7) keep automated decisions away from prohibited or high‑risk categories and factor in the criminal‑code changes that raise penalties for AI‑enabled harms (Peru Law No. 32314 (AI criminal code changes)); 8) document workflows and train every team member on verification and ethics; 9) run sandboxed pilots with clear success metrics and a rollback plan; 10) establish a governance committee that reports incidents to national authorities and re‑assesses risk periodically - small, measurable steps protect clients while unlocking AI's efficiency gains.

"If you create value, you win. Focus on your clients. Focus on value." - Danielle Benecke, Baker McKenzie (Legalweek 2025)

Running pilots in Peru should begin inside the regulatory guardrails: use the National AI Sandbox and phased timelines to test real use cases - for example, trial a citizen‑service chatbot or a contract‑triage Copilot in a locked sandbox rather than in front of clients - to surface data, safety and explainability issues before scaling.

Align each pilot with Peru's risk‑based Law 31814 and the SGTD/PCM governance model so pilots feed into the national Digital Transformation System and obey human‑oversight, transparency and DPIA requirements (Peru Law 31814 AI regulation and national governance overview).

Structure governance as a small, cross‑functional committee (legal, data, ops, security) that reviews pilot metrics, rollback triggers and vendor transparency, and invite civil‑society or academic reviewers where possible - this multistakeholder approach mirrors regional trends and sandboxes across LatAm (AI regulation and sandbox trends in Latin America - FPF overview).

Finally, treat pilots as a legal-proof exercise: document impact assessments, logging and human verification so a successful sandbox becomes the evidence base for safe, auditable deployment under the recently approved regulations (Peru Supreme Decree approving Law 31814 AI regulations), not a compliance afterthought; the vivid payoff is a single safe pilot that prevents a costly public failure.

Peruvian firms must retool hiring and career paths to reward AI fluency and strategic judgment: recruit flexible talent (including vetted remote associates to scale workload quickly), pair that sourcing with targeted, role-specific training in AI literacy and prompt‑crafting, and create explicit career ladders that value KM, governance and client‑facing strategy over rote drafting.

Data from the 2025 sector studies show firms that tie AI to strategy and invest in people see faster ROI and productivity gains (roughly five hours saved per person per week), so stand up interdisciplinary training, add governance roles or a Chief Transformation sponsor, and convert knowledge management into a revenue skill rather than a filing task.

That means formal onboarding for AI tools, measurable upskilling paths, and performance plans that reward verified, high‑value legal work - not just billable minutes.

For practical guidance, see the Thomson Reuters Future of Professionals Report (2025) and analysis of AI-driven contract automation and legal tech trends for 2025 to shape hiring and training priorities in Peru.

"This transformation is happening now."

Positioning AI to Peruvian clients requires a clear, trust-first message: sell augmentation, not replacement - explain that tools automate routine research, contract triage and admin so lawyers spend more time on strategy and human judgment, while mandatory human oversight and risk controls (per Peru's risk‑based Law 31814) keep responsibility squarely with counsel (Peru AI regulation Law 31814 - full regulatory text and overview).

Reassure clients with governance evidence, not promises: show DPIAs, vendor due diligence and logging so transparency replaces fear, especially where critics warn Peru's regulatory boom can be performative without enforcement (Harvard Kennedy School analysis of Peru's AI regulatory boom).

Emphasize practical client benefits - faster, consistent responses and 24/7 handling of routine queries (think a Copilot that answers a status question at 2 AM so the lawyer can craft persuasion by daylight) - and cite secure, auditable workflows from communications platforms that automate outreach while preserving final human sign‑off (AI-driven client communication tools for law firms with secure, auditable workflows).

Local signals show Peru is already in the mix: vLex's Winter '25 upgrades explicitly added country‑specific Vincent AI workflows for Peru, bringing multimodal transcription for hearings and depositions plus an improved Build an Argument feature that ties facts to citation‑backed authorities - concrete tools Peruvian litigators can pilot to turn hours of testimony into searchable timelines in minutes (vLex Winter 2025 Vincent AI release for Peru).

That expansion makes a practical local playbook obvious: run a small, sandboxed pilot (depositions, contract collections or judicial‑proceedings transcripts), fold your archived files into a verified KM collection, and use the results to test governance, DPIAs and vendor clauses before scaling.

Real-world case studies - where Vincent helped a litigator finish trial prep overnight and reclaim family time - underscore the payoff for wellbeing and efficiency, while the Studio beta offers a low‑code path to build firm‑specific workflows that surface lost institutional “gold.” For Peruvian teams wanting structured upskilling, consider formal training such as the Nucamp AI Essentials for Work syllabus (AI Essentials for Work, 15 Weeks) to build prompt, verification and governance skills that turn pilots into repeatable advantage.

“They can pull their data, use our data and tools, and build something that really works for their firm or corporate legal department.”