The Complete Guide to Using AI as a Legal Professional in Peru in 2025

For legal professionals in Peru, AI is no longer a distant policy debate but a practical, regulated reality: Peru's Law 31814 establishes a risk-based AI regime with prohibited categories (like manipulative social scoring and certain real-time biometric uses), mandatory human oversight, transparency duties, and centralized oversight within the national digital transformation system - essential context for any counsel advising clients or deploying tools in-country (Peru's Law 31814 risk-based AI framework).

That regulatory clarity, coupled with regional trends toward sandboxes and innovation support, makes AI both an efficiency lever and a compliance challenge - one that can recapture lost time and revenue if governed properly (see industry findings on AI-driven legal efficiency).

Practical upskilling matters: consider targeted training such as Nucamp's AI Essentials for Work bootcamp - practical AI skills for legal teams to learn prompt design, tool selection, and workflows that preserve client confidentiality while boosting productivity.

Peru's AI regime in 2025 centers on Law No. 31814 and a risk‑based approach that tries to thread the needle between promoting innovation and protecting rights: it sets out prohibited uses (think subliminal manipulation, certain social‑scoring and much real‑time biometric surveillance), a mandatory human‑oversight regime, transparency and data‑governance duties, and centralized implementation through the Presidency of the Council of Ministers' Secretariat of Government and Digital Transformation (PCM‑SGTD) - an overview of these core elements is available in the official Law 31814 summary (Official summary of Peru Law No. 31814 risk-based AI framework (Nemko Digital)).

The implementing Regulations (published in the Official Gazette on 9 September 2025) layer in practical obligations - labelling and explainability for high‑risk systems, stronger consent and cross‑border rules, and even registration/traceability and recommended impact assessments - while the approved Supreme Decree (No.

115‑2025‑PCM) and guidance spell out institutional roles, sandboxes and phased sector timelines so firms can plan compliance (Peru AI Regulations published in the Official Gazette - 9 Sept 2025 (DataGuidance), Supreme Decree No. 115‑2025‑PCM implementing AI Regulations (Lexology)).

For legal teams the so what is concrete: high‑risk deployments require documented governance and trained personnel authorised to halt or correct AI decisions, and some impact assessments and traceability records must be retained for at least three years, turning abstract compliance talk into actionable project milestones for counsel advising clients.

Peruvian AI rules take a clear, risk‑graded approach that legal teams must read as a roadmap, not a suggestion: some systems are outright prohibited - the “unacceptable” category bans subliminal manipulation, social‑scoring schemes and many forms of real‑time biometric surveillance (and even predictive policing or autonomous lethal capabilities are flagged) - while a broad set of high‑risk uses (think biometric identification, credit scoring, hiring and workforce management, health and education systems, critical infrastructure and social‑program decisions) trigger mandatory human oversight, labelling, explainability and traceability duties; lower‑impact tools such as customer‑service chatbots or entertainment AIs remain allowed but still fall under general transparency and data‑protection rules (see the detailed framework in the Lexology: Summary of Peru AI Regulations and the practical overview at Nemko Digital: AI regulation overview in Peru).

The so‑what is immediate: a Peruvian firm using AI for client screening or automated case triage needs documented impact assessments, trained personnel empowered to stop an AI decision, and retained records (impact analyses and traceability logs) for regulatory review - in short, one misplaced facial‑recognition database or an unexplained automated denial could turn a time‑saving tool into a regulatory headache, so counsel should map each system to the prohibited/high‑risk/allowed categories before deployment.

Everyday AI workflows that Peruvian lawyers are already testing combine contract review and drafting, legal research, due diligence and e‑discovery into a practical toolkit - think clause extraction and deviation detection to triage incoming NDAs, playbook‑driven redlines for repeatable commercial terms, NLP/OCR to unlock legacy contracts for portfolio analytics, and targeted e‑discovery for large litigation where chain‑of‑custody and data‑residency rules must be confirmed before cross‑border collection.

These are not theoretical gains: AI acts like a 5‑star concierge for documents - surfacing critical clauses, renewal dates and obligation owners in seconds - freeing lawyers from the 40–60% of their time many spend on drafting and review (so teams can focus on strategy and client counselling).

Peruvian firms must, however, pair these tools with the governance Law 31814 requires - documented impact assessments, human‑in‑the‑loop supervision, labeling and traceability - especially for high‑risk processing or cross‑border transfers; practical vendor choices range from contract CLMs and intelligent agents (see the Juro guide to AI contract review) to enterprise e‑discovery platforms like Relativity, each chosen with privacy and compliance front of mind and integrated into firm workflows.

With AI Extract, I've been able to get twice as many documents processed in the same amount of time while still maintaining a balance of AI and human review. This AI functionality feels like the next step for intuitive CLM platforms. - Kyle Piper, Contract Manager, ANC

Client confidentiality and privilege in Peru sit at the crossroads of Law No. 29733 (the PDPL), the New Regulation (Supreme Decree No. 016‑2024‑JUS, in force March 30, 2025) and the new AI rules, so firms cannot treat data risk as an afterthought: processing personal and sensitive data (including biometrics and neural or health data) generally requires prior, informed consent, databases must be registered and technical/organisational security measures documented, and cross‑border transfers demand adequacy or binding contractual safeguards before any cloud‑based review, e‑discovery or model training is authorised (see the DLA Piper Peru data protection framework for a detailed summary).

The New Regulation phases in mandatory Personal Data Officer appointments by revenue bands and tightens breach reporting - large‑scale incidents must be notified to the authority quickly (the texts introduce strict notification duties and, for some incidents, a 48‑hour window) - while the AI Regulations explicitly tie mandatory human oversight and explainability to high‑risk systems that touch client data (see the Lexology overview of Peru AI regulations).

Practically, counsel should map each AI workflow (training data, prompt logs, vendor processors, retention and traceability) to PDPL duties, adopt privacy‑by‑design controls and documented incident response playbooks: non‑compliance can trigger significant sanctions (very severe infringements reach up to S/535,000, roughly USD 144,000) and reputational risks that undermine privilege claims.

For a hands‑on compliance checklist and operational steps - database registration, consent mechanisms, DPO timelines and ISO‑aligned security controls - consult the 2025 Peru business data protection compliance guide.

Ethics and bias mitigation are core pillars of Peru's AI regime, not optional extras: Law No. 31814 and the implementing Regulations embed non‑discrimination, transparency, accountability and mandatory human oversight across public and private use, requiring firms to prevent algorithmic bias, label high‑risk systems, and make outcomes explainable to affected people (see the MoFo overview of Peru AI laws and regulations).

Practical compliance means more than paperwork - organisations must implement internal ethical policies, adopt recognised standards (the Regulations even encourage international ISO guidance), maintain traceability and impact records for at least three years, and train designated personnel with the explicit authority to halt or correct automated decisions as set out in Supreme Decree No.

115‑2025‑PCM and its guidance on human‑in‑the‑loop controls (details in the Lexology summary of the Regulations).

a governance “big red stop button” in practice

The SGTD will issue ethical and technical guidelines within the short statutory window, and multisectoral oversight makes bias mitigation an ongoing operational responsibility: rigorous data‑quality checks, fairness testing, documentation of model limits, and visible human review points are the concrete steps that turn ethical principles into defensible practice in Peruvian legal workflows.

Intellectual property for AI in Peru now sits on two linked fronts lawyers must navigate: copyright and patents. On copyright, INDECOPI's September 2024 rulings make clear that registration still hinges on a natural‑person author and on the classic Andean originality test, and the authority cautioned that simple prompts can let different users obtain near‑identical images from the same generative tool - so AI outputs alone won't automatically carry authorship or a clean chain of title (INDECOPI generative AI and copyright decisions - Union Andina).

That means Peruvian counsel should insist on written assignments, vendor licences and clear consent for any training or TDM that uses third‑party works, since regional guidance has signalled that unauthorised use of copyrighted material to train models raises contagion risk for infringement claims.

On patents, practitioners should plan around the prevailing international posture that only natural persons can be named inventors while recognising AI‑assisted inventions remain patentable when a human makes a “significant contribution” to each claim - so careful documentation of prompts, design choices and human refinements is central to preserving prosecutability and enforcement in Peru (Peru patent law and AI inventorship primer - Lexology, Global AI inventorship trends and patent rights - Sterne Kessler).

In short: secure licences, record human creative and inventive inputs, and treat model training and prompt engineering as evidence‑grade steps in any IP strategy so clients don't trade speed for avoidable ownership disputes.

Originality means that a work can be distinguished from other third-party works. In his work, the author has infused elements of his own spirit. Two works could be considered original if one is not a reproduction of the other, and if each contains elements that distinguish or individualize them. Originality requires the work to display a highly characteristic individuality, clearly and evidently reflecting the imprint of its author. Originality entails an individual and creative contribution, that is, the product of independent thought.

Healthcare AI in Peru promises real gains - faster triage, AI‑aided imaging that can flag early‑stage cancer hours before a specialist review, and smarter telemedicine for remote communities - but it also sits squarely in the “high‑risk” box of Peru's Law No.

31814, triggering human‑in‑the‑loop duties, labelling, explainability and traceability that legal teams must bake into any clinical deployment (see the Regulations overview on Lexology overview of Peru AI regulations and the country guide at Nemko Digital country guide to AI regulation in Peru).

Patient data is doubly sensitive under the PDPL and its New Regulation (Supreme Decree No. 016‑2024‑JUS), so prior written consent, strict minimization, secure cross‑border safeguards and DPO/incident‑reporting workflows are non‑negotiable - particularly where models are trained on clinical records or imaging that could identify individuals (detailed compliance points are set out in DLA Piper's Peru data protection summary).

Practical counsel should therefore insist on vendor contracts that lock down licences and provenance, documented impact and safety checks, clear clinician oversight roles to explain and override AI outputs, and a certification/validation path for tools used in diagnosis or treatment: done well, AI can extend care into underserved regions; done poorly, a single unexplained automated recommendation could become both a patient‑safety and regulatory crisis in a nation that treats health AI as high‑stakes by design.

Start small, stay systematic: treat AI governance like client intake - create an AI inventory, map each model to a clearly documented use case, and immediately classify risk under Law 31814 so you know which systems are prohibited, high‑risk, or lower‑impact (Peru AI regulation overview - Nemko Digital).

For high‑risk systems, run and retain written impact assessments, build traceability and versioned audit trails, and bake mandatory human oversight into workflows so an authorised reviewer can pause or override outputs; technical controls should include secure deployment (VPC/on‑prem where needed), access controls and continuous monitoring to detect drift (TDWI AI governance checklist for regulated environments).

Vendor risk management is non‑negotiable: require plain‑language model documentation, data provenance, rights for audits, and ethical‑AI clauses in contracts so third parties meet the same standards your firm enforces (ISACA guidance: embedding ethical AI in third‑party compliance assessments).

Finally, assign clear roles (AI lead, compliance steward, DPO), train staff on explainability and bias testing, pilot in a regulatory sandbox where available, and schedule recurring audits - doing these steps in sequence turns abstract obligations into a defensible, operational program that protects clients while unlocking real productivity gains.

The pragmatic next steps for Peruvian legal professionals are clear: treat Law 31814 and its implementing Supreme Decree as project deadlines, not abstract policy - map every AI use to the risk categories in the national framework, document impact and traceability for high‑risk systems, and hardwire mandatory human oversight into workflows so an authorised reviewer can pause or correct outcomes (see the regulations summary: Supreme Decree No. 115‑2025‑PCM regulations (Lexology) and the Peru country guide to Law 31814 at Peru AI regulation country guide (Nemko Digital)).

Update engagement letters and vendor contracts to require model documentation, audit rights and data‑provenance guarantees, add DPIAs and retention of impact records (three years) to your compliance folder, and remember recent criminal‑law reforms now treat AI‑enabled offences as aggravating factors - so compliance lapses carry operational, administrative and even criminal risk.

Finally, invest in people: train a named AI lead and DPO where required, pilot solutions in a sandboxed environment and build a repeatable playbook for classification, testing and explainability; practical upskilling such as Nucamp AI Essentials for Work bootcamp can speed that transition with hands‑on prompt and tool training for legal teams.

Think of compliance as the cost of speed - one unexplained automated denial or a misplaced biometric dataset can turn an efficiency win into a regulatory and reputational crisis, so act now and operationalise these steps before the January 2026 entry‑into‑force milestones.