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National AI Strategies

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  • Pascal Muam Mah

Abstract

Purpose: This study investigates national AI strategies across sectors with a primary goal to construct an AI model that aspiring countries can utilize to formulate their own tailored AI strategies. Design/Methodology/Approach: We investigated 62 national AI strategies and policies across 12 sectors. Our investigations center on AI national interest, AI national priorities, AI national attention, AI national performance, AI national investments and AI national ranking. We use the python Google Colab programming library to build our model that tracks the number and amount of AI investments projects, investments priority for the 62 nations and predict the best nation with AI strategies. Findings: The study analysis and evaluation of investment patterns as identified from the data published by OECD and TortoiseMedia. Our model successfully tracked and compared AI investments priorities for the 62 nations with a correlation coefficient metrics score of 0.999, 100, and 0.999 for all the training models. Based on our model, we then conceded that AI strategies vary across nations with regards to priority, number, and amount of AI investments projects due to technology, cultural, economic, social and political differences, laws, population density, and knowledge flows. Practical implications: There exists global skepticism, fear, and discomfort on the application and use of AI due to limited knowledge of global AI strategic policies. Originality: Artificial intelligence (AI) is the number one technological innovation that is revolutionizing sectors of a nation’s economy. The scope and the significance of AI have attracted huge government investments. These huge investments seem like a nation’s strategy and policy towards AI, but it isn’t.

Suggested Citation

  • Pascal Muam Mah, 2024. "National AI Strategies," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1196-1215.
    • Handle: RePEc:ers:journl:v:xxvii:y:2024:i:4:p:1196-1215
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    References listed on IDEAS

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    1. Simon Kaggwa & Tobechukwu Francisa Eleogu & Franciscamary Okonkwo & Oluwatoyin Ajoke Farayola & Prisca Ugomma Uwaoma & Abiodun Akinoso, 2024. "AI in Decision Making: Transforming Business Strategies," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 10(12), pages 423-444, January.
    2. Ghio, Alessandro, 2024. "Democratizing academic research with Artificial Intelligence: The misleading case of language," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 98(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Artificial intelligence; Economic sectors; AI investments; national AI strategies; national AI priorities; correlation metrics.;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M16 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - International Business Administration
    • R49 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Other

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