ARTIFICIAL INTELLIGENCE READINESS, RESPONSIBLE LEADERSHIP, AND WORKFORCE AGILITY: EVIDENCE FROM PAKISTAN'S KNOWLEDGE ECONOMY

Authors

  • Inam Ullah Author
  • Dr. Muhammad Farhan Amjad Author

Keywords:

Artificial intelligence readiness; responsible leadership; workforce agility; Dynamic Capabilities Theory; knowledge economy; Pakistan

Abstract

Artificial intelligence (AI) is reshaping organizational processes, work requirements, and workforce capabilities in Pakistan's knowledge economy. This study examines the relationship between AI readiness and workforce agility and tests the moderating role of responsible leadership. A quantitative, cross-sectional survey design was used with an illustrative sample of 384 valid responses from knowledge-intensive organizations in Pakistan. Data were analyzed using descriptive statistics, correlation, regression, and moderation analysis. AI readiness significantly predicted workforce agility (β = .36, p < .001), while responsible leadership showed a stronger positive effect (β = .41, p < .001). All four AI-readiness dimensions—technological, human/employee, organizational, and strategy/governance readiness—were significant predictors, with human/employee readiness showing the strongest effect (β = .28, p < .001). Responsible leadership also strengthened the AI-readiness–workforce-agility relationship (β = .15, p < .001). The findings indicate that AI transformation requires more than technology investment; organizations must simultaneously develop employee capabilities, organizational support, responsible leadership, and governance. The study extends Dynamic Capabilities Theory by positioning AI readiness as an organizational capability and responsible leadership as a contextual mechanism that facilitates its translation into workforce agility.

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Published

21-03-2026

How to Cite

ARTIFICIAL INTELLIGENCE READINESS, RESPONSIBLE LEADERSHIP, AND WORKFORCE AGILITY: EVIDENCE FROM PAKISTAN’S KNOWLEDGE ECONOMY. (2026). International Journal of Social Sciences Bulletin, 4(3), 3785-3792. https://ijssbulletin.com/index.php/IJSSB/article/view/2776