The global debate on artificial intelligence (AI) governance often focuses on regulation. Governments discuss legal frameworks, compliance mechanisms, ethical principles, and risk management. Yet experience increasingly shows that governing AI involves far more than drafting legislation. It requires building institutions, developing public-sector expertise, creating coordination mechanisms, and establishing the operational capacity needed to oversee a technology that evolves faster than traditional policymaking processes.
Spain’s recent experience offers a valuable case study in this regard. Over the past five years, the country has undertaken one of Europe’s most ambitious efforts to build a comprehensive AI governance ecosystem, combining strategic planning, institutional development, regulatory innovation, and public investment. For Latin America and the Caribbean (LAC), where many countries are currently defining their own AI strategies and regulatory approaches, the Spanish experience provides important lessons on how states can prepare themselves not only to regulate AI, but also to govern it effectively over the long term.
The Growing Importance of Institutional Capacity
Across Latin America and the Caribbean, governments are increasingly recognising the strategic importance of artificial intelligence. Countries such as El Salvador and Peru have already adopted legislation related to AI and digital innovation. Brazil, Chile, Colombia, Uruguay, and several others are actively discussing regulatory frameworks, national strategies, and governance mechanisms. At the regional level, organisations such as the Inter-American Development Bank (IDB) have promoted enabling regulatory approaches designed to balance innovation, economic competitiveness, and the protection of fundamental rights.
However, regardless of where each country currently stands in the regulatory process, all face a common challenge: developing the institutional capacity necessary to implement AI policies in practice.
Passing legislation is often the most visible step in the governance process, but it is rarely the most difficult one. The deeper challenge lies in creating public institutions capable of understanding rapidly evolving technologies, supervising AI systems, coordinating with technical experts, engaging with academia and industry, and adapting policy frameworks as technological developments unfold.
AI governance is not a static exercise. New models, applications, risks, and opportunities emerge continuously. Public institutions therefore need the ability not only to regulate, but also to learn, adapt, and evolve. This requires capabilities that go well beyond traditional legislative functions.
For this reason, the experiences of countries that have already begun building such capabilities deserve close attention. Spain represents one of the most developed examples of how a government can move from strategic ambition to operational implementation.
Spain’s Journey Towards AI Governance
Spain’s approach to AI governance emerged within a broader national effort to modernise the economy and accelerate digital transformation. Rather than treating AI as an isolated technological issue, Spanish policymakers framed it as a strategic component of economic competitiveness, public-sector modernisation, innovation policy, and national resilience.
A major milestone came in 2020 with the creation of the Secretary of State for Digitalisation and Artificial Intelligence (SEDIA), housed within the Office of the Vice-President for Economic Affairs. During the same period, Spain launched its National Artificial Intelligence Strategy (Estrategia Nacional de Inteligencia Artificial – ENIA), supported by approximately €600 million in public investment through the Recovery, Transformation and Resilience Plan established in response to the COVID-19 crisis.
The strategy aimed not only to stimulate AI innovation but also to strengthen the country’s ability to govern and deploy AI responsibly across both the public and private sectors.
As the importance of AI continued to grow, Spain progressively expanded its institutional architecture. In 2023, responsibility for digital transformation and AI governance was elevated to a dedicated Ministry for Digital Transformation and Public Service. This institutional upgrade reflected the recognition that digital governance had become a central policy domain requiring specialised leadership, dedicated resources, and long-term strategic oversight.
Subsequent reforms further refined responsibilities across government. New structures were created to address AI policy, data governance, digital services, connectivity, cybersecurity, and digital economy initiatives as distinct but interconnected policy areas. Rather than relying on a single institution, Spain gradually developed a networked governance model capable of addressing the multidimensional nature of AI.
Building More Than Ministries
Perhaps the most important lesson for Latin America and the Caribbean is that Spain’s governance model extends far beyond ministerial structures.
Alongside its formal governmental bodies, Spain has developed an ecosystem of public agencies, state-owned entities, innovation programmes, investment mechanisms, and technical institutions designed to translate policy objectives into operational action.
These organisations perform a variety of critical functions. They finance AI research and innovation projects, manage grant programmes, support technology adoption, coordinate public-private partnerships, provide technical expertise to government agencies, and facilitate knowledge transfer between academia, industry, and the public sector.
Equally important is the development of advisory and anticipatory capabilities. Spain has invested in foresight mechanisms, expert councils, and multi-stakeholder forums that help policymakers anticipate future technological developments and emerging governance challenges.
This combination of regulatory, operational, and strategic foresight functions creates a governance ecosystem capable not only of responding to present challenges but also of preparing for future ones.
In many respects, this broader institutional ecosystem may be the most transferable aspect of the Spanish experience. While organisational structures differ between countries, the underlying principle remains universal: effective AI governance requires institutions that can act, coordinate, learn, and adapt.
Acting Before Regulation Is Complete
One of the most distinctive characteristics of Spain’s approach has been its willingness to build governance capacity before regulatory frameworks were fully finalised.
In 2023, Spain became the first European Union member state to establish a dedicated AI supervisory authority: the Spanish Agency for the Supervision of Artificial Intelligence (AESIA). The agency became operational in 2024 and is responsible for overseeing aspects of AI governance while supporting compliance with European regulations.
AESIA also manages Europe’s first AI regulatory sandbox, an experimental environment where companies, regulators, researchers, and public authorities can collaborate to test how emerging AI regulations may apply to real-world systems before broader implementation.
The significance of this initiative extends beyond regulatory experimentation. Regulatory sandboxes create opportunities for institutional learning. They allow governments to better understand technological developments, identify practical implementation challenges, engage directly with innovators, and refine regulatory approaches based on evidence rather than assumptions.
Importantly, Spain established AESIA before the European AI Act was fully implemented. This reflects a broader philosophy: governance capacity should not wait for perfect regulatory certainty.
The same principle is visible in Spain’s evolving AI strategy. The original National AI Strategy, launched in 2020, was designed before the emergence of large language models and generative AI technologies such as ChatGPT. By 2024, however, technological developments had fundamentally altered the AI landscape.
In response, Spain updated its strategic approach, incorporating new initiatives such as ALIA, a sovereign Spanish-language large language model initiative, alongside an additional €1.5 billion investment package focused on AI development and deployment.
This experience highlights a critical reality of AI governance: strategies cannot be static documents. They must be living frameworks capable of evolving as technologies evolve. In rapidly changing technological environments, the capacity for continuous adaptation becomes one of the most valuable institutional capabilities of all.
Key Lessons for Latin America and the Caribbean
While Spain’s political, economic, and institutional context differs from that of many countries in Latin America and the Caribbean, several lessons have broad relevance.
Establish Leadership Early
Governments do not need perfect institutional designs before taking action. Establishing a lead authority with a clear mandate, sufficient resources, and coordination responsibilities can create momentum and provide direction for future governance efforts.
Waiting for complete regulatory certainty may delay the development of the very capacities needed to implement future legislation effectively.
Invest in Execution, Not Just Regulation
Many countries focus heavily on drafting laws and strategies while investing less attention in the institutions responsible for implementation.
Successful AI governance requires agencies capable of administering programmes, managing projects, supporting adoption, monitoring compliance, and generating technical expertise. Regulatory frameworks alone cannot perform these functions.
Develop and Retain Public-Sector Talent
Across the world, governments face growing competition with the private sector for AI expertise.
Without specialised professionals inside public institutions, governments struggle to evaluate AI systems, oversee implementation, assess risks, or engage effectively with technical stakeholders. Building attractive public-sector career pathways for AI specialists is therefore becoming a strategic necessity.
Create Mechanisms for Continuous Learning
AI governance cannot be based solely on static rules.
Regulatory sandboxes, pilot projects, periodic strategy reviews, stakeholder consultations, and foresight exercises provide governments with opportunities to learn continuously and adapt their approaches as technology evolves.
These mechanisms help reduce uncertainty while strengthening trust and collaboration between government, industry, academia, and civil society.
Looking Towards the Future
For Latin America and the Caribbean, where institutional capacity and digital maturity vary significantly between countries, the central lesson emerging from Spain’s experience is that governance is ultimately an institutional challenge rather than a purely regulatory one.
Effective AI governance depends on the ability of public institutions to coordinate actors, develop expertise, anticipate technological change, implement policies, and adapt continuously over time. Legislation remains important, but laws alone cannot create these capabilities.
As artificial intelligence becomes increasingly integrated into public administration, economic development, healthcare, education, infrastructure, and public services, governments will need institutions capable of managing both the opportunities and the risks that accompany technological transformation.
The countries that invest early in building these institutional foundations are likely to be better positioned to harness AI for economic growth, social development, and public-sector innovation. The experience of Spain demonstrates that this process is neither immediate nor linear. It requires experimentation, adaptation, and sustained political commitment.
Ultimately, governing artificial intelligence is not a single legislative event. It is a long-term process of institutional development. For Latin America and the Caribbean, the challenge is not simply how to regulate AI, but how to build the state capacity necessary to govern it effectively in the decades ahead.