From Digital Transformation to Intelligent Transformation: How Artificial Intelligence Reconfigures Organizational Capabilities

Abstract

Purpose: This study examines how artificial intelligence (AI) enables organizations to progress from digital transformation toward intelligent transformation through the reconfiguration of organizational capabilities.

Theoretical foundation: Drawing primarily on Dynamic Capabilities Theory (DCT), and integrating insights from the Resource-Based View (RBV) and organizational learning theory, the study conceptualizes AI capability as an organizationally embedded capacity that supports sensing, seizing, learning, and transforming.

Methodology: A simulation-based illustrative cross-sectional survey dataset representing 487 senior managers, executives, IT managers, AI managers, digital transformation leaders, and department heads was analyzed. The sample represents manufacturing, services, finance, telecommunications, information technology, and retail organizations that had implemented AI-based technologies. Partial least squares structural equation modeling (PLS-SEM) was used to test direct, mediating, and moderating relationships.

Major findings: The illustrative results indicate that AI capability positively influences organizational capability reconfiguration (β = .58, p < .001) and intelligent transformation (β = .31, p < .001). Organizational capability reconfiguration positively predicts intelligent transformation (β = .49, p < .001), which subsequently enhances organizational performance (β = .46, p < .001). Capability reconfiguration mediates the AI capability–intelligent transformation relationship, while intelligent transformation mediates the capability reconfiguration–performance relationship. Organizational learning capability strengthens the positive effect of AI capability on capability reconfiguration (β = .14, p = .001).

Theoretical contributions: The study conceptualizes intelligent transformation as an advanced organizational stage beyond conventional digital transformation and explains the capability-reconfiguration mechanism through which AI creates organizational value.

Practical implications: Organizations should complement investments in AI infrastructure with data governance, AI talent, organizational learning, cross-functional integration, and dynamic capability development.