Government priority · 28.05.2026.
PPPA working document. The document is structured in two levels — Strategic Goals (what AI deployment delivers for society) and Action Plan (how it is implemented). All core principles of the EU AI Act are observed.
Time remaining until the strategy approval deadline (05.09.2026.) · Government Declaration ↗
Part A — Strategic Goals
The goals serve society — not bureaucracy. AI is a tool, not a goal in itself.
State and municipal institutions provide public services to citizens and businesses on their own initiative, without waiting for an application to be submitted. Benefits, permits and notifications are provided automatically — citizens and businesses no longer need to request or prove facts that public administration already holds.
State and municipal institutions use AI in preparing decisions so that decisions are prepared faster, are data-driven, and carry a full audit trail. Decision-makers work with AI-prepared analysis. The administrative burden on citizens and businesses is reduced.
New capacity in education, healthcare, safety and entrepreneurship. The purpose of using AI is not better bureaucracy, but a freer and more capable society with new horizons of opportunity. People add value — AI provides support.
Part B — Action Plan
Every public administration institution acts on its own, without waiting for a centralised platform or a single vendor's all-encompassing solution. AI deployment carries challenges and risks that must be minimised wherever possible.
What "AI-ready" means under this strategy
An institution whose processes are algorithmised, whose documents are standardised, and whose contracts are machine-readable. AI supports decision-making with real facts, meaningful analysis and a fully auditable record. AI does not merely automate — it genuinely supports the decision-maker. Responsibility always remains with a person — an official, in accordance with applicable law.
Each institution implements at least one pilot project comprising a working, algorithmised, auditable operational process that uses AI to support decision-making.
Related to: Process-as-Code · Annex III of the EU AI Act
Each institution implements unified digital identifiers and metadata standards for its documents, making them machine-readable — AI can find, trace, classify, link and analyse them at the level of a single institution, sector, or the entire state.
Related to: Records-as-Code · Cabinet Regulation No. 282
All public procurement contracts exceeding the thresholds set in Directive 2014/24/EU are prepared using a machine-readable standard. Contracts become structured data that can be used for AI-supported monitoring of contract conclusion and performance.
Related to: Agreement-as-Code · IUB · Directive 2014/24/EU
All public sector decision-makers — not only IT specialists — complete structured AI governance training. The focus is on understanding the principles of AI operation in their respective field, validating AI-generated analysis, and overseeing semi-automated decisions that are fully auditable.
Example: Estonia's AI Leap 2025 ↗
Latvia builds its own AI capabilities to ensure independence from foreign suppliers.
Related to: AIFA-LAT ↗ · EC Tech Sovereignty Initiative
Public-private cooperation is used to rapidly build AI capability in the public sector. Private partners provide technology and expertise; the public sector provides the necessary data and regulatory environment. Not procurement, but partnership with shared accountability for results.
Related to: PPPA research (2026) ↗
Expand the special regulatory environment, the "AI Sandbox" — more projects under evaluation, a faster selection cycle, and active involvement of institutions and state-owned enterprises, contributing their own data and infrastructure.
Public sector data is built as a national asset — structured and made available for AI development under DVI (Data State Inspectorate) oversight. A national catalogue enables reusable Latvian AI components across institutions.
Example: Estonia's "kratijupid" · AIFA-LAT project ↗
PPPA Working Position · June 2026
Latvia needs AI compute it cannot build alone. PPPA proposes 7 vendor-neutral conditions that make foreign infrastructure partnerships trustworthy and sovereign — extending the principles of action points 5 and 6.
Read the position →Submit a proposal
Do you have an idea for what Latvia's National AI Strategy should include? Send it to [email protected]. The best proposals will be published on this page and included in PPPA's compiled summary, which will be submitted to the responsible authorities.
Please structure your proposal as follows:
Proposals received
PPPA collects and publishes selected proposals. The summary is updated regularly.
The Data State Inspectorate (DVI) is the principal competent authority for personal data protection and oversight of high-risk AI systems under the EU AI Act. At present, DVI dedicates only one staff member at ⅓ of full-time capacity to AI matters — disproportionate to the scope of its oversight mandate and the requirements of the EU AI Act. Without adequate funding and capacity, DVI cannot effectively carry out the oversight functions entrusted to it.
Using real personal data for AI development creates privacy risks and legal obstacles. A national synthetic data programme would allow private sector organisations to generate and use synthetic data for the development, testing and validation of AI solutions — reducing personal data protection risks, accelerating innovation, and strengthening the international export capability of Latvia's AI ecosystem.
There is a risk that, without clear limits, AI systems could produce outcomes harmful to society. The strategy must establish strict competence boundaries for AI operation, and compliance must be verified through testing against extreme scenarios. The goal is to eliminate any possibility of harm.
Europe depends on non-EU suppliers for more than 80% of critical digital technologies. Latvia's AI strategy must set a clear open-source priority for public sector AI solutions — so the state retains control over the systems that make decisions on its behalf.
Each supplier with its own proprietary format means dependency, not control. Latvia's AI strategy must introduce mandatory interoperability requirements for every AI solution in the public sector — open APIs, standardised data structures, and migration capability.
A state-funded software solution is a public asset. AI systems developed with public funding should be published in an open repository and made adaptable by other institutions. This builds a layer of state AI infrastructure rather than duplicating costs at every institution.
Digital sovereignty requires the ability to understand and control the processes, decision logic and infrastructure underlying public services. Process algorithmisation must be included in the strategy as a mandatory element — not merely a recommendation.
Summary
The PPPA working document comprises 3 strategic goals and 8 action plan items with measurable success indicators. An additional 7 industry proposals have been compiled.
Proposal submissions opened on 30.05.2026. The summary will be submitted to the responsible authorities ahead of the 05.09.2026. deadline.
Last updated: 20.06.2026.
International experience
Best practice from countries that have already implemented AI strategies in the public sector.
Estonia
In 2019, Estonia became the first EU country to introduce a national AI strategy, focusing on reusable AI components in the public sector.
KrattAI (OECD.AI) ↗Estonia
Estonia's framework for experimentation by state institutions — a structured approach to rapid testing and deployment of AI in the public sector.
accelerate.ee ↗Estonia
Estonia's national programme for integrating AI into education and public administration. Mandatory AI training with a practical focus.
e-estonia.com ↗EU
The European Commission's June 2026 package of initiatives — an EU Open Source strategy, interoperability requirements, and a plan to reduce dependency.
EC document ↗Latvia
An EU- and nationally-funded project (€8.4m, 2026–2028) — a national AI competence centre in cooperation with RTU, the University of Latvia, and the LUMI consortium.
VDAA announcement ↗Latvia
The special regulatory environment ("sandbox") — Process-as-Code is one of the first 3 projects selected (May 2026).
AI Centre Sandbox ↗