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Metodologia para identificar lecciones aprendidas
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Metodologia para identificar lecciones aprendidas
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Peru’s National Artificial Intelligence Strategy 2026–2030, approved by the Presidency of the Council of Ministers through Ministerial Resolution No. 152-2026-PCM, is a national strategic instrument designed to organise and coordinate State interventions for the development, governance and management of artificial intelligence. It establishes a long-term vision and provides a framework for strengthening AI capabilities, deployment, oversight and public-sector coordination across the country.
ANALIA automates the extraction, processing, and structuring of data from handwritten and digital PDF documents submitted to OSITRAN as part of the road infrastructure maintenance supervision process. The initiative enables automatic data capture, integrates it into a predefined structure, applies technical criteria automatically, and generates information for regulatory decision-making, reducing manual tasks and improving operational efficiency in the supervision process.
The JULIO AI Platform is Peru's leading public sector digital transformation project. It uses AI to optimise registry services across three pillars: Specialised Consultation (natural language processing and large language models for legal precedents), a Learning Centre (manuals, prompt libraries, and automated "esquela" generators), and Integrated AI Access (specialised tools for registry contexts). Rather than replacing human judgment, it empowers staff to improve legal precision and efficiency
This initiative uses advanced AI (embeddings, FAISS and OpenAI) to align SINAPLAN instruments with the National Development Strategic Plan (PEDN). By analysing 27 national objectives against 43 public policies, it detects gaps and misalignments within the results chain. This ensures State actions respond to strategic priorities, strengthening evidence-based decision-making and public value generation through coherent national planning.
The initiative consists of a web application developed in R Shiny that integrates AI (via API) to assist specialists in creating and improving indicator names. This ensures their alignment with the results chain and the Guide for the Development of Indicators for National Policies and Strategic Plans.
The AI Assistant, combining a custom GPT with Python, automates the creation of 16-field indicator fact sheets, scaling from a 2025 pilot with 65 local documents to a national-level tool for 2025-2026. The updated system covers the Multi-sectoral Strategic Plan, the Coordinated Development Plan and the Institutional Strategic Plan (PEI), incorporating semantic validation against 2024 guidelines, intelligent navigation and batch processing to enhance efficiency across all levels of government
The project covers: improving the integration between the different modes of transport (administrative, regulatory, or value-added), providing a benefit to citizens who use these services (quality, availability, cost reduction, or safety), increasing the effectiveness and efficiency of operators, or advance in aspects linked to sustainability, social inclusion or emissions reduction.
SOFIA (Automated Information Guidance and Facilitation Service) is a virtual assistant developed by Peru's tax and customs authority, SUNAT. It provides guidance on tax and customs matters through graphic content, direct links, personalised consultations, and video tutorials. Available 24 hours a day, seven days a week via the SUNAT portal, SOFIA supports taxpayers, both individuals and legal persons, with topics including tax obligation compliance, electronic audits, customs import procedures.
Peru's Adetop algorithm is an AI-powered tool developed for forest supervision, used by Osinfor (the Peruvian forest oversight body) to detect illegal logging across Peruvian territory. Using multispectral satellite imagery from the European Space Agency's Sentinel-2 and NASA's Landsat constellation, the algorithm identifies concentrated tree extraction. Between 2024 and June 2025, the system detected 42 cases of illegal logging, totalling 23,351 cubic metres of unauthorised timber extraction.