The Asymmetric Impact of AI Readiness on Total Factor Productivity in Emerging Economies: Threshold Regression Analysis

Document Type : Research Paper

Authors

1 Administration and Economics, Humanities and Sport Science, University of Gonbad e Kavous, Gonbad e Kavous, GOlestan, Iran

2 Department of Economics & Administration, Faculty of Humanities, Gonbad e Kavous University, Gonbad e Kavous, Iran

10.22111/innoeco.2026.54002.1225

Abstract

Abstract:
Artificial intelligence (AI), as a transformative technology, has the potential to increase total factor productivity (TFP) in emerging economies; however, the realization of this potential depends on contextual conditions. This research examines whether the impact of AI readiness on TFP is nonlinear and conditional upon crossing specific thresholds in complementary capacities، particularly institutional quality and human capital. Using a panel threshold regression model (PTR) for 25 emerging economies over the period from 2020 to 2024, the results indicate that the relationship between AI readiness and productivity is asymmetric. Findings suggest that in countries where institutional quality and human capital levels fall below the estimated thresholds, the impact of AI readiness on TFP is negligible and statistically insignificant. In contrast, once these critical thresholds are surpassed, this impact becomes significantly positive and meaningful. These results underscore the importance of absorptive capacity as a prerequisite for realizing the economic benefits of AI, indicating that mere investment in technology without attention to institutional reforms and human capital development will not lead to productivity increases. A case study of Iran also reveals that despite the high potential of human capital, institutional weaknesses serve as a primary bottleneck. This research provides important policy implications for developing countries and emphasizes the necessity of adopting a comprehensive and sequenced approach to policymaking in the age of AI. Accordingly, policy implications and sugestions for policy makers and regulators to how directing sustainable dynamic prosperity have done.
Keywords: Artificial Intelligence, Total Factor Productivity, Panel Threshold Regression, Institutional Quality, Human Capital, Emerging Economies.

Keywords

Innovation EconomicEcosystem Studies
Volume 5, Issue 3
July 2026
Pages 25-52

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