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<p>Artificial Intelligence (AI) represents a knowledge-intensive technology with the potential to transform production processes, enhance intellectual capital, and accelerate the transition toward knowledge-based economic systems. In developing economies, however, the adoption of AI remains uneven and constrained by organizational, institutional, and policy-related factors. This study examines the readiness of industries in Kathmandu Valley, Nepal, to adopt AI, positioning AI adoption as a key mechanism of knowledge-based industrial upgrading in an emerging economy. Using survey data from 287 industries and employing Structural Equation Modeling (SEM), the study analyzes how technological, organizational, and environmental contexts influence AI adoption, with government intervention examined as a mediating factor. Descriptive results indicate limited readiness for AI adoption among Nepalese industries, with a majority expressing reluctance to adopt AI-based systems. The SEM results reveal that technological, organizational, and environmental contexts exert significant positive effects on AI adoption, while mediation analysis highlights the critical role of government intervention in shaping the environmental conditions that support knowledge-intensive technology uptake. AI adoption in Nepal reflects systemic knowledge economy constraints rather than technological scarcity, as evidenced by the SEM results, highlighting the pivotal role of intellectual capital, innovation infrastructure, and institutional support in knowledge-driven industrial transformation.</p>

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AI Adoption and Knowledge-based Industrial Readiness in an Emerging Economy: Evidence from Nepal

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Ghanashyam Khanal,
  • Rabin Paudel,
  • Niranjan Devkota,
  • Udaya Raj Paudel,
  • Surendra Mahato,
  • Yatish Acharya,
  • Chandra Kanta Khanal

摘要

Artificial Intelligence (AI) represents a knowledge-intensive technology with the potential to transform production processes, enhance intellectual capital, and accelerate the transition toward knowledge-based economic systems. In developing economies, however, the adoption of AI remains uneven and constrained by organizational, institutional, and policy-related factors. This study examines the readiness of industries in Kathmandu Valley, Nepal, to adopt AI, positioning AI adoption as a key mechanism of knowledge-based industrial upgrading in an emerging economy. Using survey data from 287 industries and employing Structural Equation Modeling (SEM), the study analyzes how technological, organizational, and environmental contexts influence AI adoption, with government intervention examined as a mediating factor. Descriptive results indicate limited readiness for AI adoption among Nepalese industries, with a majority expressing reluctance to adopt AI-based systems. The SEM results reveal that technological, organizational, and environmental contexts exert significant positive effects on AI adoption, while mediation analysis highlights the critical role of government intervention in shaping the environmental conditions that support knowledge-intensive technology uptake. AI adoption in Nepal reflects systemic knowledge economy constraints rather than technological scarcity, as evidenced by the SEM results, highlighting the pivotal role of intellectual capital, innovation infrastructure, and institutional support in knowledge-driven industrial transformation.