The Complete Guide to Using AI in the Government Industry in Uruguay in 2025

AI matters for Uruguay's public sector because the country already pairs a world-class digital foundation with deliberate, ethical stewardship: a national Uruguay Public Sector Artificial Intelligence Observatory now gathers cases and guidance to promote trustworthy AI across agencies (MIT collaboration on AI for social policy in Uruguay), while cross‑sector events and pilots - from IDB and industry forums to a hands-on MIT collaboration that prototyped models for MIDES - show how machine learning can speed decisions, reduce bias and free civil servants to focus on people.

Uruguay's long digital journey (ranked top in Latin America for digital government) makes it well placed to scale AI for citizen services, but success hinges on capacity building and practical training - skills that programs like the Nucamp AI Essentials for Work bootcamp syllabus can help deliver to public teams.

“Our program in Uruguay was designed to empower students to use new AI technologies to address local challenges,” says Eduardo Rivera.

Uruguay's digital government scene is built around the unified gub.uy portal and a compact institutional ecosystem - led by AGESIC and supported by agencies like UAIP - that stitches services, open data and observatories into one operational platform; the gub.uy modernization effort explicitly aimed to integrate 100% of central agencies and create permanent channels for citizen feedback and transparency (see the State Web Portal commitment).

Anchoring AI work within that platform, AGESIC lists an Observatorio de Inteligencia Artificial among its knowledge spaces and makes explicit objectives for responsible use of AI, signaling that policy and practice are advancing together.

The country's hard numbers are striking: about 90% of people and 91% of households are connected, formalities are reported as 100% online, and Uruguay ranks 1st in Latin America on the UN Digital Government Index - small but concrete wins like the nationwide, self‑managed tollbooth automation show how digital projects can move from pilot to production and free people from routine tasks, creating fertile ground for trustworthy AI services across government.

generating technical guides

promoting algorithm transparency

Uruguay's legal, policy and ethical framework for AI rests on a clear, government-led strategy that treats AI as a tool for digital transformation and responsible public‑sector use - laid out in the national Uruguay national AI Strategy (official government site, gub.uy) - reinforced by a revised 2024–30 plan that ties AI adoption to digital infrastructure and governance goals (BNamericas coverage of Uruguay's revised 2024–30 AI and digital infrastructure plan).

That domestic policy architecture now sits alongside international commitments: in September 2025 Uruguay became the first Latin American country to sign the Council of Europe's Framework Convention on AI, a legally binding treaty designed to ensure AI respects human rights, democracy and the rule of law - a symbolic move signed in Strasbourg that underscores the diplomatic and legal weight behind national reforms (CADE Project report on Uruguay signing the Council of Europe Framework Convention on AI).

Together these steps - strategy documents, observatories and treaty commitments - create a layered compliance environment for agencies, signaling that ethical guardrails, transparency and capacity‑building are now core parts of how AI is approved, procured and governed across Uruguay's public administration.

Data and observatories are the bedrock of Uruguay's practical AI ambitions: the national Catálogo Nacional de Datos Abiertos bundles datasets from ministries, the Presidency, departmental governments, academia and civil society so models can be trained on standardized, reusable records, while the Social Observatory has published more than 1,600 indicators on welfare and economic, social and cultural rights - integrating sources like INE, MIDES and administrative records - to power evidence-based algorithms and public monitoring; see the official Catálogo Nacional de Datos Abiertos and the OGP summary of the Social Observatory commitment for details on scope and reuse.

Local nodes matter too: Montevideo's CKAN-based portal exposes datasets and API endpoints for urban planning and services, making it trivial for technical teams to prototype models that respect provenance and transparency.

These linked platforms - backed by AGESIC, MIDES and DINEM - make open data, observatory metrics and civic participation a practical, auditable foundation for trustworthy AI in Uruguayan public services, where the tangible payoff is already clear in new analytical tools and civic‑facing dashboards built from the same open sources that power decision‑making.

Practical AI in Uruguay's public services is already concrete and varied: AGESIC's catalogue highlights conversational agents and a government chatbot prototype to help citizens begin multiple trámites, while the active

Comunidad de Inteligencia Artificial

inside the public administration has incubated pilots, IA‑CKATÓN ideas and regular cross‑agency teams that move concepts toward deployment (see the official cases page and the community convening).

Tasks that are repetitive or data‑heavy are the low‑hanging fruit - from chatbots that streamline front‑end intake to back‑office automation that speeds processing of records - and even transport and infrastructure have visible wins (the nationwide, self‑managed tollbooth automation freed staff from routine duties).

Technical use cases in IT operations also map directly to public clouds and services: proactive log analysis, capacity forecasting and automated patching cut downtime and cloud spend, making services more resilient and cost‑effective.

For small agencies and local governments, the same patterns that help PYMES - virtual agents, inventory and scheduling prediction, and straightforward automation pilots - offer fast, measurable returns and a memorable payoff: fewer queues and more time for human staff to handle complex, high‑value citizen needs (GUB.UY government AI use cases, Uruguay AI community of practice - Comunidad de Inteligencia Artificial, Practical AI use cases in IT management).

Procurement, governance and project approval for AI in Uruguay are being shaped around a small number of public institutions and practical, ethics‑first processes: AGESIC and the Unit for Access to Public Information (UAIP) anchored the Public Sector Artificial Intelligence Observatory to catalog cases, publish guidance and monitor progress, and the Observatory's first nationwide survey (December 2023–May 2024) asked organisations to report projects that already identify a problem and sit in their strategic plans - including detailed technical, team and decision‑making information - so approvals favor documented, strategic pilots (see the OECD's Observatory brief for the survey design and objectives).

At the same time, reporting and policy work emphasize capacity‑building and AI ethics as essential inputs to procurement pathways (summarised in Oxford Insights' review of Uruguay's readiness), and sector commentary notes a clear push to formalise standards for development, use and acquisition of AI in the public sector to make procurement predictable and auditable (BNamericas coverage).

Practical coordination between AGESIC and the gub.uy platform also helps streamline standards, tender specifications and adoption across agencies, turning the Observatory's case repository into a living reference that procurement officers can reuse when approving responsible AI projects.

Building capacity in Uruguay means pairing a clear national strategy with hands‑on, audience‑segmented training that moves civil servants from awareness to applied practice: AGESIC's AI Strategy and the fAIr LAC Uruguay hub emphasize targeted training plans - from introductory modules for managers to “IA in practice” and deep‑learning classes for ICT technicians - and promote self‑paced and face‑to‑face offerings to match different roles (fAIr LAC Uruguay training plans and pillars); academic partnerships have amplified that pipeline, notably the MIT MISTI/Global Teaching Labs collaboration with UTEC that ran intensive ML capstones and helped prototype models for MIDES using an anonymized dataset of over 15,000 cases, a vivid example of how classroom work can turn into decision‑support pilots (MIT MISTI collaboration helped Uruguay harness AI for social policy).

Independent reviews note the emphasis on boosting AI literacy across the public sector and embedding ethics and governance into curricula, while AGESIC's capacity development spaces and platform channels create repeatable, auditable learning paths so that training directly supports responsible procurement and deployment (AGESIC capacity development and AI strategy pillars).

“Our program in Uruguay was designed to empower students to use new AI technologies to address local challenges,” says Eduardo Rivera.

Turning Uruguay's strong digital foundation into real-world AI services starts with a short, practical checklist: begin by framing a citizen‑centred problem that aligns with AGESIC's national vision and the country's 25‑year digital strategy, then map available sources and provenance (observatories and open datasets) so models are trained on auditable inputs; next assemble a mixed team of policy, data and operations staff while investing in targeted training (local pipelines and international partners help - see the Public Sector Podcast on Uruguay's digital transformation); prototype quickly with rigorous privacy and fairness checks - a standout classroom‑to‑policy example used an anonymized dataset of over 15,000 cases to prototype decision‑support models via the MIT MISTI collaboration - then document technical specs, metrics and governance so procurement and approvals can reuse the same templates; pilot in a controlled production slice, measure accuracy, equity and operational cost, and only then scale through interoperable channels like gub.uy while keeping continuous monitoring, incident response and public reporting in place.

This staged, evidence‑first flow - problem → data → prototype → ethics review → pilot → scale - turns policy ambition into measurable citizen value and reduces risk at every step (Uruguay's status as an AI regional leader shows the payoff of that approach: infrastructure, talent and governance working in concert).

AI development in Uruguay offers useful benchmarks for each phase.

“Our program in Uruguay was designed to empower students to use new AI technologies to address local challenges,” says Eduardo Rivera.

Transparency, civic participation and risk management are woven into Uruguay's AI playbook so that technology serves the public interest rather than obscuring it: the national strategy explicitly demands that:

algorithms and data [be] openly available

alongside privacy‑by‑design, accountability and ethics principles, turning model outputs into auditable records rather than black boxes (see the Uruguay AI Strategy for Digital Government (official summary)).

Practical capacity‑building and trust‑building are part of the package - independent reviews highlight ongoing work on training, ethics and literacy to help officials and citizens understand when and how AI is used (Oxford Insights analysis of Uruguay's AI readiness) - and regulators are pushing concrete standards so procurement and deployment follow predictable, auditable rules (BNamericas report on Uruguay's AI regulation recommendations).

The result: open data, monitored algorithms and public awareness campaigns together form a risk‑management loop that makes misuse easier to spot and harder to hide.

The next practical steps for Uruguay are clear: keep turning strategy into skills, pilots and public trust by using the national AI Strategy as a roadmap, scaling targeted training, and making resources easy to find - the official Uruguay AI Strategy for Digital Government sets out governance, capacity and transparency pillars that agencies should map to every project, while the IDB‑backed fAIr LAC Uruguay hub is already running segmented courses and sector pilots to move teams from awareness to applied practice.

For public servants and local teams who need practical, work‑ready skills, short, focused programs can fill the gap quickly - Nucamp AI Essentials for Work (15-week syllabus) is an example of a 15‑week pathway that teaches tool use, prompt writing and job‑based AI tasks that agencies can deploy across functions.

Keep watching open repositories and observatories for re‑usable datasets and algorithmic guidance, prioritise transparent pilots with clear impact metrics, and invest in repeatable training so the country's regional leadership (Uruguay ranked among the top three in the Latin American AI Index) converts into tangible, accountable services citizens trust.

“In Uruguay, access to relevant public information must be guaranteed in compliance with Law 18.381.”