From Adoption to Transformation: Organizational Outcomes of Artificial Intelligence Integration Within Textile Smes in Pakistan

Purpose: The purpose of this study is to examine the organizational outcomes achieved by Small and Medium Enterprises (SMEs) in Pakistan's textile industry after adopting Artificial Intelligence (AI) technology. This study uses the Resource-Based View (RBV) and Dynamic Capabilities (DC) theories to understand how AI adoption will impact process efficiency, customer and market responsiveness, innovation, costs, and strategic growth. Design/Methodology/Approach: This study employed a qualitative multi-case design. Eleven SMEs from the textile industry in Punjab, Pakistan, were interviewed. The SMEs were then categorized by AI maturity level (Nascent, Intermediate, and Advanced). Thematic Analysis was conducted in NVivo 12 using the six steps outlined by Braun and Clarke (2006). Findings: Overall, 5 outcome categories were identified: Process Efficiency, Customer & Market Responsiveness, Innovation & Improvement, Cost Reduction & Improvements, and Strategic Growth. The range of outcomes seen differed across the AI maturity levels. Those with a higher maturity level experienced larger organizational change. Originality/Value: This study provides detailed qualitative insights into the outcomes of AI adoption in Pakistan's textile SMEs. Using RBV and Dynamic Capabilities theories, this study demonstrates how organizational AI maturity influences outcomes.