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In nine emerging markets, good governance is the transmission belt through which generative-AI readiness boosts national financial performance; once dynamics and endogeneity are accounted for, governance quality fully mediates the AI–finance link.

Does generative artificial intelligence reinforce financial performance? The mediating role of governance quality
Bahaa Awwad, Mohammad A. A. Zaid, Adel Sarea · January 22, 2026 · Future Business Journal
openalex quasi_experimental medium evidence 7/10 relevance Full text usable extracted full text DOI Source PDF

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Using panel and dynamic GMM estimators on nine emerging markets (2021–2024), the paper finds governance quality fully mediates the effect of generative-AI readiness on macro-level financial performance once endogeneity and path dependence are controlled for.

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Abstract This research seeks to empirically explore the mediating role of governance quality on the nexus between generative artificial intelligence and macro-level financial performance. This empirical study employs cross-country panel data from 2021 to 2024, encompassing an analytical sample of nine emerging markets. Initially, various static panel data techniques were employed. Afterward, to alleviate potential endogeneity bias and support the reliability of the results, the one-step system GMM approach was implemented. The results reveal that while fixed-effects estimates indicate a partial mediating role of governance quality in the nexus between generative artificial intelligence and macro-level financial performance, the dynamic system GMM estimations support full mediation once endogeneity and path dependence are controlled for. Taken together, these findings underscore the central role of governance quality as the primary transmission channel through which AI readiness translates into macro-level financial performance. The novelty of this research is reflected in its application of mediation techniques to elucidate the relationship between generative AI and macro-level financial performance. Moreover, this study pays rigorous attention to offer multidimensional insights for regulators and policymakers to design solid regulatory frameworks that enhance the adoption of generative AI tools, uphold high governance standards, and ultimately strengthen macro-level financial performance.

Summary

Main Finding

When accounting for endogeneity and dynamic path dependence (one-step system GMM), governance quality fully mediates the positive effect of government AI readiness (measured as generative AI readiness) on macro-level financial performance across nine emerging markets (2021–2024). Static fixed-effects estimates showed only partial mediation, but the dynamic GMM results indicate that AI readiness translates into improved macro financial outcomes primarily via improvements in governance quality.

Key Points

  • Research question: Does generative AI (GAI) reinforce macro-level financial performance (MLFP), and is governance quality (GQ) the transmission channel?
  • Theoretical framing: Legitimacy theory and neo-institutional theory — governments adopt AI to meet stakeholder expectations and improve institutional effectiveness.
  • Hypotheses tested:
    • H1: GAI → MLFP (positive)
    • H2: GAI → GQ (positive)
    • H3: GQ → MLFP (positive)
    • H4: GQ mediates the GAI → MLFP link
  • Empirical result summary:
    • GAI readiness is positively associated with governance quality.
    • Governance quality is positively associated with macro financial performance.
    • Controlling for endogeneity and dynamics, governance quality fully mediates the effect of GAI readiness on MLFP.
  • Novelty: First cross-country mediation analysis linking AI readiness to macro financial performance via governance quality.

Data & Methods

  • Sample: Panel of 9 emerging markets (Saudi Arabia, UAE, India, Indonesia, Egypt, South Africa, Turkey, Brazil, Romania), 2021–2024 → 36 country-year observations.
  • Dependent variable (MLFP): A latent composite of four WDI indicators — GDP per capita, GDP growth rate, FDI inflows, and stock market capitalization (% of GDP).
  • Independent variable (GAI): Oxford Insights Government AI Readiness Index (0–100). Note: captures AI readiness/policy capacity, not direct deployment or intensity of GAI use.
  • Mediator (GQ): Composite World Bank Governance Indicators (six dimensions: control of corruption, government effectiveness, political stability/absence of violence, regulatory quality, rule of law, voice & accountability), percentile ranks.
  • Controls: Country size (population), government expenditure, time and country fixed effects.
  • Estimation strategy:
    • Static panel estimators including fixed effects.
    • Mediation tested via Baron & Kenny approach.
    • One-step system GMM (dynamic panel) to address endogeneity and path dependence; reported results indicate stronger inference from the GMM approach (full mediation).
  • Limitations noted by authors: small N and short T (36 observations), emerging-market-only sample, Oxford index measures readiness not realized usage.

Implications for AI Economics

  • Governance as the primary transmission channel: Policies that increase AI readiness alone may not yield macro financial gains unless governance quality is strengthened. AI-readiness investments should be paired with institutional reforms (transparency, rule of law, regulatory quality, anti-corruption, government effectiveness).
  • Policy prioritization: Regulators should design integrated strategies — build AI-capable infrastructure and policymaking capacity while upgrading governance mechanisms to capture economic returns.
  • Measurement caution: Researchers and policymakers should distinguish AI readiness (institutional preparedness) from realized GAI deployment; effects likely differ by actual use intensity and sectoral adoption.
  • Research agenda: The paper highlights needs for larger samples, longer time spans, causal identification strategies, and investigation of heterogeneity (by region, polity type, sectoral deployment) to generalize findings and unpack micro-to-macro mechanisms.
  • Practical takeaway for emerging markets: Investments in AI policy frameworks + governance improvements can be complementary and jointly necessary to convert AI capability into measurable macroeconomic and financial performance gains.

Assessment

Paper Typequasi_experimental Evidence Strengthmedium — The paper tries to recover causal effects using system GMM to address endogeneity and dynamics, which strengthens identification relative to simple correlations; however the sample is small (nine countries over 2021–2024), the time dimension is short, measurement of 'generative AI readiness' and aggregate financial performance may be noisy, and system GMM in small-N panels can suffer from weak/invalid instruments and finite-sample bias—limiting confidence in causal interpretation. Methods Rigormedium — The authors apply appropriate panel and dynamic panel techniques (FE and system GMM) and conduct mediation analysis, which indicates technical competence; but methodological concerns remain—small cross-sectional N, short T, potential overfitting of instruments, unspecified diagnostics (e.g., Hansen/AR tests not reported in the abstract), and limited robustness checks reduce overall rigor. SampleCountry-level panel data for nine emerging-market countries observed annually from 2021 to 2024 (up to four years per country), with measures for generative-AI readiness, governance quality indicators, and macro-level financial performance outcomes. Themesgovernance adoption innovation IdentificationUses country-level panel methods: static fixed-effects estimators and a dynamic one-step system GMM to control for endogeneity and path dependence; mediation analysis implemented to test whether governance quality transmits the effect of generative-AI readiness on macro-level financial performance. GeneralizabilityVery small number of countries (n=9) limits statistical power and representativeness, Sample restricted to emerging markets—results may not apply to advanced economies, Short post-AI-adoption time span (2021–2024) captures early adoption period and may miss long-run effects, Macro-level aggregation masks within-country, sectoral, and firm-level heterogeneity, Potential measurement error in AI-readiness and governance indices specific to country-level proxies, Possible unobserved confounders and country-specific shocks reduce external validity

Claims (7)

ClaimDirectionOutcomeConfidence & EvidenceDetails
This empirical study employs cross-country panel data from 2021 to 2024, encompassing an analytical sample of nine emerging markets. Other null_result None
Reading fidelity high
Study strength high
n=9
0.8
Initially, various static panel data techniques were employed; afterward, to alleviate potential endogeneity bias and support the reliability of the results, the one-step system GMM approach was implemented. Other null_result None
Reading fidelity high
Study strength high
n=9
0.8
Fixed-effects estimates indicate a partial mediating role of governance quality in the nexus between generative artificial intelligence and macro-level financial performance. Fiscal And Macroeconomic positive macro-level financial performance
Reading fidelity high
Study strength medium
n=9
0.48
Dynamic system GMM estimations support full mediation once endogeneity and path dependence are controlled for. Fiscal And Macroeconomic positive macro-level financial performance
Reading fidelity high
Study strength medium
n=9
0.48
Governance quality is the primary transmission channel through which AI readiness translates into macro-level financial performance. Fiscal And Macroeconomic positive macro-level financial performance
Reading fidelity high
Study strength medium
n=9
0.48
The novelty of this research is reflected in its application of mediation techniques to elucidate the relationship between generative AI and macro-level financial performance. Other null_result None
Reading fidelity high
Study strength speculative
n=9
0.08
The study offers multidimensional insights for regulators and policymakers to design regulatory frameworks that enhance adoption of generative AI tools, uphold high governance standards, and ultimately strengthen macro-level financial performance. Governance And Regulation positive macro-level financial performance
Reading fidelity high
Study strength low
n=9
0.24

Notes