# I- Introduction

global competitiveness (Brynjolfsson and Unger, 2023), making its adoption a critical priority for nations worldwide.<sup>2</sup> The most prominent accounting and consulting firms claim that AI is projected to contribute significantly to the global economy, with estimates ranging from US$2.6 trillion to US$4.4 trillion annually (Chui et al., 2023), to US$15.7 trillion by 2030, driven by productivity and consumption gains (PwC, 2017). Some recent NBER publications<sup>3</sup> highlight that AI has the potential to significantly boost productivity and economic growth by automating tasks and driving innovation. However, the realization of these gains depends on complementary policies, institutions, and societal adaptation to ensure equitable and sustainable outcomes (Aghion, Jones, and Jones, 2019; Trammell and Korinek, 2023; Acemoglu, 2024). To summarize, AI, and particularly generative AI, has the potential to boost economic growth and productivity but poses risks of labor market disruptions, including premature de-professionalization—where skilled jobs are replaced or diminished before workers can fully capitalize on their expertise—and challenges for developing economies, such as reduced opportunities for high-skill job creation, increased inequality, and difficulties in integrating AI technologies into less-developed industrial and educational systems (Liu, 2024).

Such substantial socio-economic impacts underscore the critical importance for countries to adopt and integrate AI technologies to remain competitive and keep a sovereign public policy.<sup>4</sup> However, the benefits of AI are not uniformly distributed. The 2023 Government AI Preparedness Index (AIPI) from the International Monetary Fund (IMF) reveals significant disparities in AI preparedness and readiness among nations, highlighting a growing divide between those equipped to leverage AI and those at risk of falling behind (Cazzaniga et al., 2024).<sup>5</sup> Related to this, Liu and Wang (2024) highlight that middle-income countries exhibit unexpectedly high engagement with generative AI tools relative to their economic scale, while low-income economies are notably underrepresented. In this context, it becomes imperative to identify effective strategies for enhancing a country's AI readiness. This paper aims to explore such strategies, providing a framework for nations to efficiently bolster their AI capabilities and ensure inclusive growth in the evolving digital landscape.

The methodology outlined in this paper is straightforward: it evaluates AI preparedness at the country level using the AIPI and compares it to each country's assessed level of economic complexity. This approach identifies countries that outperform in AI preparedness and readiness relative to their

> 2 The UN Secretary-General’s High-level Advisory Body on Artificial Intelligence (HLAB-AI) has published the final report “ _Governing AI for Humanity_ ,” advocating for the establishment of a globally inclusive and distributed AI institutional framework rooted in international cooperation. The report emphasizes the need for collaboration among governments and stakeholders to ensure AI promotes development while safeguarding human rights (UN HLAB-AI, 2024).

> 3 National Bureau of Economic Research (NBER) publications, including working papers, are highly regarded as they are produced by leading economists, often serve as precursors to top peer-reviewed journal articles, and are widely cited in academic and policy discussions.

> 4 “The late 2022 launch of GPT-3.5, OpenAI’s generative Artificial Intelligence (AI) chatbot, sparked a media frenzy about the onrushing evolution of AI and what it portends for the human race and the planet at large. During the recently concluded Global Digital Summit, World Bank President Ajay Banga observed that ‘even people who are relatively naive about AI are rushing toward AI, because of the fear of being left behind.’” [https://accountability.worldbank.org/en/news/2024/Developing-AI-for-development].

> 5 See https://www.imf.org/external/datamapper/datasets/AIPI.

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