Peru - AI License Plate Regulation (PL 07651/2023)
Project 7651/2023 — Bill to regulate use of AI algorithms for license-plate recognition
Proyecto 7651/2023 — Proyecto de ley para regular el uso de algoritmos de IA para el reconocimiento de placas vehiculares
Peru
RAI-PE-NA-P7RUAXX-2024Peru - AI License Plate Regulation (PL 07651/2023) is Under Review in Peru as of 9 Sep 2026, according to congreso.gob.pe.
BillConformity Assessment and RegistrationData Protection and PrivacyGovernance and OversightBill 07651/2023-CR regulates the deployment of AI algorithms for real-time license-plate recognition by Peruvian law enforcement and municipal authorities. Presented to the Congress of Peru on April 22, 2024, the bill is currently Under Review. Data protection standards would be supervised by the National Personal Data Protection Authority.
Summary
Project 7651/2023 (registered as Bill 07651/2023-CR) is currently under review in the Congress of the Republic of Peru. The draft legislation was formally presented to Congress on April 22, 2024, by Congresswoman Cruz Maria Zeta Chunga of the Fuerza Popular parliamentary group and referred to relevant congressional commissions for study and review, where it remains pending legislative deliberation.
The proposed bill aims to establish a specific legal framework governing the use of artificial intelligence algorithms and techniques for real-time license-plate recognition across land transportation systems in Peru. Its primary public-safety objective is to prevent and investigate vehicle-related offenses by enabling automated, real-time identification of vehicles reported stolen or operating with altered license plates.
Under the proposed framework, the exclusive management and operation of license-plate recognition data for crime prevention is assigned to the National Police of Peru (Policía Nacional del Perú) and municipal Serenazgo services, as well as the Judiciary and Public Prosecutor's Office within their respective legal competencies. The Ministry of Transport and Communications (MTC), the National Superintendent of Public Registries (SUNARP), and provincial and district municipal administration services serve as primary information sources to populate the central database of vehicles authorized to circulate within national territory.
The draft mandates the deployment of AI-enabled video surveillance cameras at strategic municipal locations in coordination with the National Police. Oversight and enforcement authority resides with the relevant administrative and law enforcement entities alongside data protection supervision by the National Personal Data Protection Authority (Autoridad Nacional de Protección de Datos Personales). Overseeing authorities are empowered to audit system operators, inspect technical architecture, enforce strict data retention limits, require human-in-the-loop verification prior to any enforcement outcome, issue administrative warnings and fines, and suspend or revoke authorizations for noncompliant surveillance deployments.
The bill provides that its provisions will enter into force thirty business days following the publication of its implementing regulations in the official gazette El Peruano. The Executive Branch is tasked with promulgating the implementing regulations and necessary technical mechanisms within sixty calendar days of enactment.
Full article
Read full text ↗Overview
Project 7651/2023 (registered as PL 07651/2023-CR) is a draft law presented to the Peruvian Congress on 22 April 2024 that aims to regulate the deployment and use of algorithms and artificial intelligence techniques for the recognition of vehicle license plates ("reconocimiento de placas de rodaje"). The draft frames the intervention as a public-safety measure to prevent and investigate crimes involving stolen vehicles and altered plates by enabling real-time detection using video surveillance systems with AI modules. The bill text and parliamentary dossier can be consulted on the official legislative portal of the Congress (Expediente PL 07651) and downloaded from the congressional archive (Bill PDF).
Definitions
The bill defines core terms to delimit scope: "algorithm and AI techniques" refers to software and models used to detect, read and match license-plate characters (including optical character recognition and computer-vision models); "recognition in real time" denotes automated processing of live video streams or near-real-time processing of recently captured images; "authorized registry" describes a national or inter-agency register containing plates authorized to circulate and plates reported as stolen or altered; "operator" includes any public agency, municipal body, or private entity that deploys or operates plate-recognition systems; "match event" refers to an automated positive identification requiring follow-up. These definitions delimit obligations such as registration, logging, and human verification requirements to avoid purely automated enforcement outcomes.
Governance and Institutional Framework
The draft assigns regulatory, oversight and coordination roles to a set of public bodies. It contemplates technical rules and operational coordination by the Ministry of Transport and Communications (MTC) for deployments related to transport infrastructure, while data protection obligations and supervisory authority fall under the Autoridad Nacional de Protección de Datos Personales (ANPD). Operational access and law-enforcement follow-up are expected to involve the Policía Nacional del Perú (PNP) and the Ministry of the Interior. The Congress remains the legislative and oversight authority and the bill contemplates inter-institutional memoranda of understanding for data sharing. The draft requires that any public or private operator obtain prior registration/authorization and submit technical documentation, privacy impact assessments, and security plans to the designated authorities for approval.
Key Focus Areas
The bill concentrates on several intersecting policy pillars: (1) Risk management and necessity: deployments must demonstrate a specific public-safety purpose, documented risk assessment, and proportionality analysis; (2) Data protection and privacy: mandatory data protection impact assessments (DPIAs), minimum retention periods, anonymization/pseudonymization where feasible, and strict access controls; (3) Transparency and accountability: public disclosure of authorized deployments, registries of systems and operators, mandatory logging and tamper-evident audit trails; (4) Human oversight: requirement that automated matches be subject to human review before administrative or criminal measures are taken; (5) Cybersecurity and model security: technical standards for encryption, secure model update procedures, and vulnerability management; (6) Conformity and registration: compulsory system registration and periodic conformity assessments by accredited evaluators; and (7) Remedies and redress: complaint mechanisms and obligations to rectify incorrect matches and delete improperly retained images. The draft therefore intersects privacy, fundamental rights, and surveillance regulation.
Implementation Framework
Implementation is organized into pre-deployment, operational and post-deployment phases. Pre-deployment requires operators to: register systems; provide system architecture, datasets descriptions, model provenance, training/validation metrics, and DPIAs; obtain authorization from the designated regulator(s); and run third-party audits or conformity assessments. Operational requirements include secure logging, role-based access controls, encryption of stored media and model artifacts, predefined retention schedules, and procedures for human verification and escalation. Post-deployment mandates periodic reporting to regulators, incident notification procedures for breaches or misuse, and scheduled audits. The bill contemplates technical regulations and secondary norms to be issued by the MTC in coordination with the ANPD and relevant security bodies to define technical standards for cameras, model accuracy, false-positive thresholds, and interoperability with vehicle registries.
Monitoring and Evaluation
Monitoring mechanisms include mandatory operational reports to the ANPD and the coordinating ministry, independent audits by accredited entities, and public transparency reports summarizing deployments, incidents, and enforcement actions. The draft requires impact evaluations at specified intervals (for example, 12 and 36 months after authorization) to measure accuracy, social impact on rights (freedom of movement, privacy), and effectiveness in crime reduction. The bill also contemplates an independent oversight committee or ombudsperson function to review complaints and advise on policy adjustments. Metrics to be tracked include detection accuracy, false positive/false negative rates, number of matches leading to actions, complaints received, and incidents of data breaches.
Penalties, Liability, and Appeals
Proposed enforcement measures range from administrative sanctions (warnings, fines graduated by severity and repeat violations), suspension or revocation of system registrations, mandatory corrective measures, and referral to prosecutorial authorities for criminal misuse. The bill envisages civil liability for damages caused by negligent or unlawful operation, and allows affected individuals to seek correction, deletion, and compensation through administrative and judicial channels. Operators are required to maintain documentary evidence to defend decisions and are subject to inspection. Appeals procedures are to be defined in implementing regulations and require timely administrative review and access to evidentiary material for affected persons while balancing confidentiality of investigatory data.
Relationship to Other Instruments
The draft explicitly interfaces with existing Peruvian legal instruments: the Law on Personal Data Protection (Law No. 29733 and its regulatory framework) and rules governing vehicle registries and transport regulation. It calls for coordination with the Autoridad Nacional de Protección de Datos Personales for compliance with data-protection principles and with transport and interior ministries for operational rules. The proposal does not supersede general criminal or traffic laws but creates a specialized compliance layer for automated plate-recognition systems. Observers recommend alignment with administrative procedure laws to ensure due process in enforcement actions.
International Alignment
Project 7651/2023 draws on international debates about automated surveillance and AI governance, sharing policy elements present in other jurisdictions such as mandatory DPIAs, transparency registers, human-in-the-loop requirements, and conformity assessments. It references comparative practices and the need to align with international human-rights standards. The bill's measures can be compared to EU regulatory trends (e.g., rules in the AI Act proposals) and Latin American initiatives on algorithmic control and data protection. Observers urge that Peru consider international standards and best practices, and build interoperability and data-protection reciprocity where cross-border data flows are involved.
Implementation Timeline
| Phase | Milestone | Target Date |
|---|---|---|
| Introduction | Project presented to Congress (PL 07651/2023-CR) | 2024-04-22 |
| Committee review | Referral to Commission(s) for study, hearings | 2024 Q2 (ongoing) |
| Regulatory design | MTC & ANPD draft implementing regs after approval | Post-approval + 6-12 months |
| Registration & audits | Operators register systems; initial conformity assessments | Implementation year + 0-6 months |
| Monitoring | First mandatory impact evaluation | 12 months after major deployments |
Sources and References
Primary official sources for this instrument include: Congress of the Republic of Peru — parliamentary expediente (Expediente PL 07651); Congress of the Republic of Peru — official bill full text (Bill PDF); and Congress agenda listings (Agenda 2024-2025).
Requirements for a company
What an organisation has to do under Peru - AI License Plate Regulation (PL 07651/2023), at a glance. Not legal advice — the table below gives the provision and deadline for each item.
Not yet in force (Under Review). These requirements apply once the instrument takes effect and may change before then.
Must do
7- Obtain prior registration and authorization from designated authorities before deploying license-plate recognition systems.Public and private operators of license-plate recognition systems
- Perform and submit a data protection impact assessment prior to deploying license-plate recognition systems.Public and private operators of license-plate recognition systems
- Maintain secure logging and tamper-evident audit trails for all system operations and match events.Public and private operators of license-plate recognition systems
- Encrypt stored media and model artifacts and implement role-based access controls and secure update procedures.Public and private operators of license-plate recognition systems
- Establish complaint mechanisms to rectify incorrect matches and delete improperly retained images.Public and private operators of license-plate recognition systems
- Conduct impact evaluations and conformity assessments at 12 and 36 months following authorization.Public and private operators of license-plate recognition systems
- +1 more in the table below
Must not do
1- Do not enforce administrative or criminal measures based on automated matches without prior human review.Public and private operators of license-plate recognition systems
Should do
0Nothing in this category.
Should not do
0Nothing in this category.
Who must do what
The obligations under Peru - AI License Plate Regulation (PL 07651/2023), most serious first. Not legal advice — verify against the official text before relying on it.
| # | Who | Requirement | By when | Where | Severity |
|---|---|---|---|---|---|
| 1 | Public and private operators of license-plate recognition systems | Obtain prior registration and authorization from designated authorities before deploying license-plate recognition systems. “The draft requires that any public or private operator obtain prior registration/authorization and submit technical documentation” | Before deployment | — | Critical |
| 2 | Public and private operators of license-plate recognition systems | Do not enforce administrative or criminal measures based on automated matches without prior human review. “requirement that automated matches be subject to human review before administrative or criminal measures are taken” | — | — | Critical |
| 3 | Public and private operators of license-plate recognition systems | Perform and submit a data protection impact assessment prior to deploying license-plate recognition systems. “mandatory data protection impact assessments (DPIAs), minimum retention periods, anonymization/pseudonymization where feasible” | Before deployment | — | Important |
| 4 | Public and private operators of license-plate recognition systems | Maintain secure logging and tamper-evident audit trails for all system operations and match events. “mandatory logging and tamper-evident audit trails” | — | — | Important |
| 5 | Public and private operators of license-plate recognition systems | Encrypt stored media and model artifacts and implement role-based access controls and secure update procedures. “Operational requirements include secure logging, role-based access controls, encryption of stored media and model artifacts” | — | — | Important |
| 6 | Public and private operators of license-plate recognition systems | Establish complaint mechanisms to rectify incorrect matches and delete improperly retained images. “complaint mechanisms and obligations to rectify incorrect matches and delete improperly retained images.” | — | — | Important |
| 7 | Public and private operators of license-plate recognition systems | Conduct impact evaluations and conformity assessments at 12 and 36 months following authorization. “The draft requires impact evaluations at specified intervals (for example, 12 and 36 months after authorization)” | 12 months after authorization | — | Important |
| 8 | Public and private operators of license-plate recognition systems | Notify regulators promptly of any security breaches or system misuse incidents. “incident notification procedures for breaches or misuse, and scheduled audits.” | — | — | Important |
Related Regulations
More AI regulation in Peru
AI regulation in Peru: full overview
- Peru - AI Penal Code Amendments (8746/2024)
- Peru - AI Regulation Implementation (115-2025)
- Peru AI Regulation Overview
- Peru - Digital Government Framework (1412/2018)
- Peru - Digital Transformation Regulation (015-2025)
- Peru - AI Use as Aggravating Circumstance (32314/2025)
- Peru - Digital Transformation in Consulates (32082/2024)
- Peru - National AI Strategy
© Regulations.AI · updated on 20 Sep 2026 · reviewed against official sources on 9 Sep 2026 using Gemini 3.6 Flash