Spain - AI Research Strategy
Spanish Strategy for Artificial Intelligence in R&D&I
Estrategia Española para la Inteligencia Artificial en I+D+i
Spain
RAI-ES-NA-SSAIRXX-2019The Spanish Strategy for Artificial Intelligence in R&D&I (published March 2019) sets national priorities for research, development and innovation in AI, identifying strategic application areas, institutional arrangements and recommendations to promote talent, knowledge transfer and ethical use. It is an R&D&I-focused framework prepared by the Ministry of Science, Innovation and Universities to guide state plans, public funding and cross-ministerial coordination.
Summary
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Overview
The Spanish Strategy for Artificial Intelligence in R&D&I (presented 4 March 2019) is a national framework that defines priorities, organizational arrangements and policy recommendations to orient public and private R&D&I activities in AI. Prepared by the Ministry of Science, Innovation and Universities with a multidisciplinary working group, the document emphasizes research excellence, knowledge transfer, talent development and the ethical and socially responsible use of AI. The strategy situates AI within Spain's broader Science, Technology and Innovation architecture and state R&D&I plans and highlights the role of cross-ministerial coordination. The official PDF and presentation materials are published by the Ministry; see the primary strategy document (Estrategia española de I+D+I en Inteligencia Artificial (PDF)) and the ministry announcement (Ministry news release, 4 March 2019).
Definitions
For the strategy, "Artificial Intelligence" refers to a set of techniques and methods (including machine learning, deep learning, symbolic AI and natural language processing) that enable systems to perform tasks that would otherwise require human intelligence. "R&D&I" covers research, technological development and innovation activities across public research organisations, universities and the private sector. The strategy differentiates between foundational research (methods, algorithms, datasets), applied research (domain-specific prototypes and demonstrators) and innovation/transfer actions (commercialisation, public sector deployment). It also defines cross-cutting concepts such as 'ethical AI' (respect for human rights, fairness, transparency) and 'capacity map' (a national inventory of public and private AI actors and resources).
Governance and Institutional Framework
The strategy recommends a multi-level governance architecture centered on the Ministry of Science, Innovation and Universities as the lead coordinating authority and a cross-ministerial Group on AI to align sectoral policies. It proposes the creation and use of a national "Map of Capabilities" to identify research centres, universities, technology platforms and companies, supporting coordination and matchmaking. It also advocates closer ties between the ministry, public research organisations (CSIC and others), autonomous communities, funding agencies and relevant ministries (Health, Economy, Education, Digital Transformation) to align the State Plan and sectoral programmes. For administrative and communications details, see the ministry announcement (Ministry of Science news) and the government event summary (La Moncloa: presentation, 4 March 2019).
Key Focus Areas
The strategy identifies priority application areas and enabling technologies. Priority areas include: health (precision medicine, diagnostics), public administration (data-driven services, digital public services), industry and manufacturing (automation, predictive maintenance), education and training (digital skills), mobility and climate-related sectors, and language technologies. Enabling technologies highlighted are machine learning, deep learning, natural language processing and data infrastructures. Cross-cutting aspects include data sharing and reuse (with privacy safeguards), high-performance computing and access to datasets, creation of flagship demonstrators and 'lighthouse' projects, and measures to increase private R&D investment. The document stresses talent and training policies to build capacity (PhD and postdoc programmes, specialist masters, upskilling for industry), and the promotion of public-private collaborations and technology transfer mechanisms to take research results to market or to public-sector use. It also recommends research into societal impacts (bias, explainability, socio-economic effects) and embedding responsible research practices throughout the R&D lifecycle.
Implementation Framework
Implementation is envisaged through existing state instruments: the State Plan for Scientific and Technical Research and Innovation (PEICTI), multiannual strategy instruments (such as the EECTI 2021-2027), targeted competitive funding calls, and coordinated actions across ministries. The strategy advocates the use of the national capacity map to prioritise calls and fund networks of excellence, and recommends creating strategic public investment lines for flagship technologies and infrastructures (compute and data). It advises that funding criteria include open science, data management plans and ethics review components, and proposes collaboration mechanisms with regional governments and industry clusters to scale pilots and demonstrators. Suggested actions also include the development of evaluation indicators for R&D impact and mechanisms to facilitate SMEs' access to R&D resources.
Monitoring and Evaluation
The strategy proposes periodic monitoring through measurable indicators (research outputs, patents, participation in EU programmes, talent flows, technology transfer metrics and adoption in strategic sectors). It recommends establishing a monitoring body or strengthening the role of an existing coordination structure within the Ministry to track progress against the strategy and to report outcomes in the State Plan cycle. The document encourages integration of AI metrics into the national Science & Technology Information System and reuse of data analytics to inform policy decisions and to adapt priorities as technologies and societal needs evolve. The Map of Capacities is listed as a recurring tool to measure ecosystem evolution and gaps.
Penalties, Liability, and Appeals
As a strategic policy document (not primary regulation), the strategy itself does not establish formal legal sanctions. Instead, compliance is operationalised through funding conditions, evaluation criteria and programmatic requirements: entities that fail to meet funding conditions, ethical standards or data management obligations may face ineligibility for competitive calls or suspension of grants. The strategy explicitly refers to applicable legal frameworks (for example, data protection laws) and recommends alignment with those regimes; liability and appeal mechanisms therefore remain in the scope of sectoral and legal instruments (e.g., grant rules, administrative law and national/EU legislation such as the GDPR). For data protection issues, the strategy points to the role of the Spanish Data Protection Agency (AEPD).
Relationship to Other Instruments
The strategy is explicitly positioned as an R&D&I instrument aligned with the Spanish Strategy for Science, Technology and Innovation (EECTI 2021-2027) and the State Plans for R&D&I (PEICTI). It references the need to implement recommendations consistent with EU coordinated plans on AI and to comply with horizontal legislation (data protection, sectoral health and safety rules). The strategy complements other national AI-related initiatives (capacity maps, flagship plans and recovery/PRTR funds) and is intended to inform the programming of public R&D funding and the definition of national missions and large-scale projects in priority sectors.
International Alignment
The strategy recommends active alignment with European and international AI initiatives, including the EU Coordinated Plan on AI and Horizon Europe research priorities. It calls for participation in transnational projects, standard-setting bodies and international cooperation to leverage research funding, share datasets and participate in coordinated testbeds and cross-border demonstrators. The strategy highlights the need to harmonise ethical guidelines and technical standards with EU partners and to foster Spain's role in European AI research networks and programmes to increase competitiveness and ensure regulatory coherence.
Implementation Timeline
| Milestone | Date |
|---|---|
| Presentation of the strategy | 2019-03-04 |
| Publication in Transparency Portal | 2019-05-24 |
| Integration into the EECTI / alignment with State Plans | 2020-09 (EECTI approved September 2020) |
| Ongoing: Map of Capacities initial release | 2019-10-02 (map first announced) |
Compliance Checklist
| Requirement | Check |
|---|---|
| Register on national Map of Capabilities / notify participation | Yes / Recommended for institutions and research centres |
| Incorporate ethics and data management in project proposals | Mandatory for state-funded projects (as criteria) |
| Align project goals with identified strategic areas | Advised for higher scoring in calls |
| Provide staff training and talent development plans | Recommended |
| Comply with GDPR and sectoral legal frameworks | Mandatory |
Sources and References
| Source | Type |
|---|---|
| Estrategia española de I+D+I en Inteligencia Artificial (PDF) | Primary Source |
| Ministry news release: Presentation of the strategy (4 March 2019) | Primary Source |
| La Moncloa: Activity record (presentation event) | Primary Source |
The Spanish Strategy for Artificial Intelligence in Research, Development, and Innovation (R&D&I), effective March 4, 2019, guides Spain's national efforts in AI by setting priorities and promoting ethical use for public and private entities.
This framework, developed by the Ministry of Science, Innovation and Universities, applies to anyone involved in AI research, development, and innovation across public research organizations, universities, and the private sector in Spain. Its main goal is to foster research excellence, knowledge transfer, and talent development while ensuring AI is used ethically and responsibly.
While not a law with direct penalties, the strategy influences compliance through public funding. Key recommendations and requirements for those seeking state funding include: - Incorporating ethical considerations and data management plans into project proposals. - Aligning project goals with the strategy's identified priority areas, such as health, public administration, and manufacturing. - Participating in the national "Map of Capabilities," an inventory of AI actors and resources, to support coordination.
Failure to meet these funding conditions, ethical standards, or data management obligations can lead to ineligibility for competitive calls or suspension of grants. Legal liability for broader issues, like data protection, falls under existing national and EU laws like the General Data Protection Regulation (GDPR), not this strategy directly.
A practical point for product managers and founders is that while this strategy doesn't impose direct legal obligations, it heavily shapes the landscape for public funding and collaboration in Spain's AI sector. Ignoring its principles, particularly around ethics and data governance, could significantly hinder access to state support and partnerships. This means even private companies not directly seeking grants should be aware of the ethical and responsible AI principles it champions, as these are becoming standard expectations.
Plain-English rewrite by Regulations.ai — not legal advice. Verify against the official text.
What you must do — compliance checklist
0 / 8 marked completePlain-English obligations under Spain - AI Research Strategy. Not legal advice — verify against the official text before relying on it.
- #1CriticalPenalties, Liability, and Appeals
Applies to: All entities engaged in AI R&D&I activities.
“The strategy explicitly refers to applicable legal frameworks (for example, data protection laws) and recommends alignment with those regimes.”
- #2ImportantImplementation Framework⏰ Before submitting project proposals
Applies to: Entities applying for state funding for AI R&D&I projects.
“It advises that funding criteria include open science, data management plans and ethics review components.”
- #3ImportantKey Focus Areas
Applies to: Researchers and institutions conducting AI R&D&I.
“embedding responsible research practices throughout the R&D lifecycle.”
- #4RecommendedKey Focus Areas⏰ Before submitting project proposals
Applies to: Entities applying for state funding for AI R&D&I projects.
“The strategy identifies priority application areas and enabling technologies.”
- #5RecommendedGovernance and Institutional Framework
Applies to: Public research organisations, universities, technology platforms, and companies in AI R&D&I.
“It proposes the creation and use of a national 'Map of Capabilities' to identify research centres, universities, technology platforms and companies.”
- #6RecommendedKey Focus Areas
Applies to: Organisations engaged in AI R&D&I.
“The document stresses talent and training policies to build capacity (PhD and postdoc programmes, specialist masters, upskilling for industry).”
- #7RecommendedKey Focus Areas
Applies to: Public research organisations, universities, and private sector entities in AI R&D&I.
“promotion of public-private collaborations and technology transfer mechanisms to take research results to market or to public-sector use.”
- #8RecommendedKey Focus Areas
Applies to: Researchers and institutions conducting AI R&D&I.
“recommends research into societal impacts (bias, explainability, socio-economic effects)”
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