The long-term ramifications are alarming, and further work on their AI Preparedness Index could help improve and synchronize global AI regulation.
When IMF Managing Director Kristalina Georgieva sounded the alarm about the uneven AI landscape and weak AI ethics this week, she underscored that most countries lack the necessary ethical and regulatory structures to manage AI safely.
However, this strong statement was not made lightly. It was based on comprehensive research aiming to go beyond anecdotal evidence or isolated expert opinions. The IMF recognizes that, to guide governments and international organizations effectively, it needs a rigorous, measurable way to assess AI readiness globally.
The result is an analytical framework, the AI Preparedness Index, that could capture this complexity and yield clear, actionable findings. AI impacts multiple areas: economic growth, labor markets, innovation ecosystems, digital infrastructure, and critically — governance and ethics. These dimensions vary widely between advanced economies and developing countries. (Note: the IMF uses the term “ethics” as an umbrella term for both responsible AI (operational ethics) and the moral values (aspirational ethics such as fairness, transparency, privacy, non-discrimination, etc.)
Creating the AI Preparedness Index
- Digital infrastructure: Assesses internet access, broadband coverage, and technology penetration
- Human capital and labor policies: Evaluates STEM education levels, workforce skills, and labor market flexibility
- Innovation and economic integration: Measures R&D activity, technology diffusion, and participation in global value chains
- Regulation and ethics: Considers the existence and quality of legal frameworks, regulatory adaptability, and ethical AI governance
Rather than focusing solely on countries leading AI innovation or production, the index gauges the readiness to harness AI’s potential across diverse economies. This focus distinguishes the IMF’s approach, emphasizing equitable adoption and the avoidance of deepening inequality.
Combining diverse data sources
The AIPI aggregates multiple objective and perception-based data points from reputable sources such as the World Bank, United Nations, International Telecommunication Union, and various global surveys, such as the World Bank’s Beyond the AI Divide, 2025. These include statistics on internet penetration and educational attainment, as well as expert assessments of policy frameworks and ethical oversight.
Each pillar receives equal weight to provide a balanced picture. Scores are normalized between 0 and 1, enabling direct comparisons. This composite structure helps highlight specific strengths and weaknesses within nations and regional groups.
Uncovering weakest AI ethics and regulation
Once compiled and analyzed, the data revealed a consistent pattern: while most countries showed progress in infrastructure, skills, and innovation, nearly all — including many advanced economies — lagged significantly in the regulation and ethics pillar. This dimension was the index’s weakest globally.
This finding reflects the realities on the ground: many governments have yet to enact comprehensive AI-specific regulations. Ethical frameworks, such as principles for fairness, transparency, accountability, and privacy protection, remain underdeveloped or inconsistently enforced in most nations. The rapidly evolving AI landscape challenges policymakers who often lack the expertise or institutional capacity to keep pace, as reported widely in various media
Interpreting the findings beyond numbers
The IMF researchers caution that the regulation and ethics pillar relies heavily on perception-based measures because hard data on AI governance enforcement are scarce. Still, the pattern has been clear enough to raise red flags. The ethical foundation for AI adoption — the rules, norms, and oversight mechanisms — is the most fragile element of global AI readiness.
Moreover, this weakness threatens to exacerbate inequalities between advanced countries possessing resources to develop and regulate AI, and emerging or low-income countries struggling to establish even basic digital infrastructures, according to a June 2024 blog post.
From data to policy warnings
Armed with insights from the AIPI, Georgieva has communicated a twofold message at international forums:
- First, she urges governments and civil society groups to prioritize strengthening digital foundations, including ethical governance, to ensure AI benefits are broadly shared. Neglecting ethical regulation could deepen divides and expose markets to destabilizing risks.
- Second, she warns of “AI-driven exuberance” in financial markets, echoing the late-1990s tech bubble. Overvaluation in AI sectors, fueled by unchecked optimism and inadequate oversight, might trigger corrections with global economic repercussions.
Together, these messages underscored the urgency of building an ethical and regulatory base while advancing AI innovation and deployment responsibly.
Guiding governments with a research-based roadmap
The AIPI serves as a tool for policymakers, allowing them to benchmark their national AI readiness against peers and identify priority areas. The IMF recommends starting with digital infrastructure and skills development — a prerequisite to meaningful AI adoption — while concurrently developing robust legal frameworks and ethical guidelines.
International bodies and private sector leaders are also encouraged to participate in shaping AI governance. Georgieva emphasized shared responsibility, recognizing that no single actor can ensure AI’s potential without collective oversight.
Limitations and future improvements
The IMF dutifully acknowledges the AIPI’s limitations. The regulation and ethics pillar’s reliance on perception data and the difficulty of quantifying rapidly changing AI governance mean it provides a directional rather than definitive assessment. Updating the index with more granular enforcement data and broader ethical metrics is a future goal.
Nonetheless, the index’s transparency, coverage, and integration of diverse data types make it a valuable starting point. It transforms complex AI readiness factors into understandable metrics, facilitating evidence-based policy dialog.
Through this example, the IMF is demonstrating how research-based frameworks can illuminate challenges and guide international efforts toward more equitable and responsible AI adoption.
The four pillars of AI preparedness in the global landscape 2024
