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<p>Artificial intelligence (AI) is increasingly central to how societies pursue sustainable development, as contemporary insights show that it reshapes production, public services, and citizen welfare. Yet, the conditions under which national AI readiness translates into measurable gains remain unclear. Drawing on competing perspectives: absorptive-capacity complementarity (ACC) and the Technology Enactment Framework (TEF), we test whether innovation capability conditions the AI readiness-SDG relationship across ASEAN using Oxford Insights’ AI Readiness Index (2020–2024). AI readiness is operationalised via three pillars: government, technology sector, and data &amp; infrastructure, while sustainable development is proxied by the country-level SDG Index score. We estimate country fixed-effects (FE) models (with and without year effects) with GDP per capita and trade openness as controls, and report Limited Information Maximum Likelihood (LIML) results as a robustness check to assess sensitivity to potential endogeneity in innovation capability. The results show that technology readiness is robustly and positively associated with SDG performance in the preferred FE specification, while government readiness is weaker (marginal in the year-FE model) and data &amp; infrastructure is not statistically different from zero once year effects are included. Crucially, innovation capability significantly and negatively moderates the association between technology readiness and SDG performance (β = − 0.491, <i>p</i> &lt; 0.01). This finding contrasts with ACC predictions, but aligns with the TEF, suggesting a “catch-up”/diminishing-returns pattern in which the technology-readiness association is stronger when innovation capability is below its country-specific mean and smaller (and potentially adverse) when it is above. Policy-wise, the findings support a differentiated sequencing approach: strengthening foundational digital capacity may be most salient for members where such capacity remains limited, while innovation-advanced contexts may benefit more from mission-oriented deep-tech (including green innovation) alongside continued governance safeguards.</p>

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Innovation capability moderates the association between AI readiness and sustainable development in ASEAN

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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  • Pureheart Ogheneogaga Irikefe,
  • Qi Yi Thong,
  • Mohammad Falahat,
  • Jason Samuel Lucas

摘要

Artificial intelligence (AI) is increasingly central to how societies pursue sustainable development, as contemporary insights show that it reshapes production, public services, and citizen welfare. Yet, the conditions under which national AI readiness translates into measurable gains remain unclear. Drawing on competing perspectives: absorptive-capacity complementarity (ACC) and the Technology Enactment Framework (TEF), we test whether innovation capability conditions the AI readiness-SDG relationship across ASEAN using Oxford Insights’ AI Readiness Index (2020–2024). AI readiness is operationalised via three pillars: government, technology sector, and data & infrastructure, while sustainable development is proxied by the country-level SDG Index score. We estimate country fixed-effects (FE) models (with and without year effects) with GDP per capita and trade openness as controls, and report Limited Information Maximum Likelihood (LIML) results as a robustness check to assess sensitivity to potential endogeneity in innovation capability. The results show that technology readiness is robustly and positively associated with SDG performance in the preferred FE specification, while government readiness is weaker (marginal in the year-FE model) and data & infrastructure is not statistically different from zero once year effects are included. Crucially, innovation capability significantly and negatively moderates the association between technology readiness and SDG performance (β = − 0.491, p < 0.01). This finding contrasts with ACC predictions, but aligns with the TEF, suggesting a “catch-up”/diminishing-returns pattern in which the technology-readiness association is stronger when innovation capability is below its country-specific mean and smaller (and potentially adverse) when it is above. Policy-wise, the findings support a differentiated sequencing approach: strengthening foundational digital capacity may be most salient for members where such capacity remains limited, while innovation-advanced contexts may benefit more from mission-oriented deep-tech (including green innovation) alongside continued governance safeguards.