EdTech #395 – Innovative voluntary financing options for artificial intelligence capacity-building

Five Tiers of AI Maturity

Tier 0: “AI nascent”

At this stage, countries face deep structural and capacity constraints, which limit meaningful AI engagement. Most lack a national AI strategy, or where it exists, there is no clear implementation plan. Expertise is minimal across government and the private sector. Infrastructure is weak, with unreliable connectivity, limited compute power and unstable energy. Structured data sets are scarce and data governance frameworks are largely absent. Education and training in AI are very limited, and both domestic investment and access to international financing are low. Engagement and support from existing private sector actors towards AI capacity development in these countries is extremely low to non-existent.

Strategic Pathway to Tier 1

A key step towards tier 1 is developing a minimum irreducible capacity across Four Domains: computing, data, skills and the ability to reuse pre-trained models. This step requires a national AI or digital strategy with a phased road map, backed by institutional coordination. Another essential step is establishing a national AI centre to support collaboration, oversee the management of shared resources, assess sectoral needs and lead training efforts, as well as engage effectively on international AI norms and standards, including international human rights law. Broad-based digital literacy and workforce skills development programmes, along with international support, are essential to building this foundation.

Tier 1: “AI experimenters”

These countries have begun integrating development. A national AI strategy is often in place, with basic compute infrastructure located in universities or government institutions. Early AI applications are being piloted in such sectors as health, education and agriculture. A small but growing pool of AI professionals are supported by academic or international partnerships. Regulatory frameworks are emerging, though are often fragmented. Countries are able to participate in international dialogues on AI governance. Engagement and support from existing private sector actors towards AI capacity development in these countries is low.

Strategic Pathway to Tier 2

To reach tier 2, countries need to expand compute capacity and improve the implementation of AI strategies. This step includes identifying priority sectors and developing high-impact use cases to demonstrate value and build confidence. AI centres may grow into hubs focused on such critical sectors as mining, manufacturing, agriculture and health, and are formalized within universities or public institutions to lead applied research and accelerate private sector collaboration. Governance frameworks progressively incorporate ethical and human rights foundations. Broader skills development in the sectoral application of AI and stronger data governance are also key components of this transition.

Tier 2: “AI ready”

AI is being adopted more systematically. These countries have mid-scale are in compute resources, such as national data centres or high-performance clusters, and growing private sector activity. Multilevel national AI strategies are being actively implemented, with better central government policy coordination. Universities offer stronger programmes and start-ups are emerging. Structured national data sets and governance frameworks are being developed, though consistency varies across sectors.

Strategic Pathway to Tier 3

To advance to tier 3, countries need to scale up compute and data infrastructure and integrate AI into broader economic planning. National strategies are regularly updated. Governments develop scalable, sectoral AI use cases and ensure that AI hubs support public-private research and international collaboration. Legal and governance frameworks address challenges to human rights, such as discrimination, privacy, information and communications technology security, and accountability and access to effective remedies. A crucial aspect is start-up and scale up funding for entrepreneurs, as well as growing integration across AI innovation and the broader digital economy. Specific attention is given to sectoral AI development.

Tier 3: “AI-enabled”

Countries at this tier have built a strong foundation and deploy AI widely across public and private sectors. AI supports productivity, innovation and service delivery. Compute infrastructure includes national platforms and access to advanced cloud systems. The energy and connectivity environment are stable. A skilled workforce, strong universities and private sector engagement support the ecosystem. AI is used specific sectors such as agriculture, transportation, health, manufacturing and public services. Data governance systems are operational and interoperable and support cross- sectoral integration.

Strategic Pathway to Tier 4

To reach the frontier (tier 4), countries need to build capacity to train large models and invest in local infrastructure, advanced hardware and frontier research. Specific skills development for foundational models and frontier AI applications is needed. Strategies anticipate and address emerging technology issues. Legal frameworks evolve to manage existing and emerging risks and promote responsible innovation, respecting human rights. Countries are active in developing international AI standards and have broad collaborations with international partners to secure opportunities and participate in global value chains.

Tier 4: “AI developers”

These countries are global leaders in AI. They develop foundation models, contribute to cutting-edge research and maintain significant domestic compute capacity. AI is embedded in all major sectors and national policy. Talent is supported by world-class institutions and global partnerships. Data ecosystems are advanced, with real-time, interoperable systems and adaptive governance.

While they may not need foundational support, global cooperation remains critical to their success. Access to diverse data sets, interoperable use cases and international markets is essential for continued innovation. These countries can drive further progress through open research and cross-border partnerships.