Abstract
Digitalization is fundamentally reshaping project work by transforming how teams coordinate, communicate, and deliver outcomes. As Artificial Intelligence (AI) becomes embedded in project environments, organizations increasingly rely on it to enhance agility, streamline workflows, and advance digital transformation initiatives. Digital transformation projects are characterized by high complexity, rapid change, and environmental uncertainty, making AI’s capabilities such as real-time data analytics, task automation, and predictive insights particularly valuable. Despite its potential, many organizations struggle to realize tangible performance gains from AI implementation, highlighting the importance of human readiness alongside technological capability.
Digital leadership has emerged as a critical enabler of AI-driven transformation. Unlike traditional leadership models emphasizing control and stability, digital leadership fosters experimentation, collaboration, and openness to technological innovation. By providing strategic direction and psychological support, digital leaders help project teams navigate uncertainty associated with AI adoption. However, limited research has examined how digital leadership, AI adoption, and human motivational factors interact to influence digital transformation project performance.
Addressing this gap, this study develops and empirically tests a sociotechnical model grounded in Diffusion of Innovations (DOI) theory and Self-Determination Theory (SDT). DOI explains AI adoption through perceptions of relative advantage, compatibility, complexity, trialability, and observability. SDT complements this perspective by emphasizing the role of basic psychological needs (autonomy, competence, and relatedness) in shaping motivation to engage with new technologies. Integrating these perspectives, the model proposes that digital leadership promotes AI adoption, which in turn enhances digital transformation project performance, while psychological needs strengthen the leadership–adoption relationship.
Using a cross-sectional survey of employees working on IT projects, the study employs quantitative analysis to test theory-driven hypotheses. The findings demonstrate that digital leadership significantly predicts AI adoption, which subsequently improves digital transformation project performance. Moreover, satisfaction of basic psychological needs strengthens the relationship between digital leadership and AI adoption, underscoring the importance of human-centered mechanisms in technology integration.
This research contributes to project management literature by advancing a sociotechnical explanation of AI adoption in digital transformation projects, extending DOI and SDT into the project context, and linking leadership, motivation, and technology use to project-level outcomes. Practically, the study provides guidance for project leaders seeking to enhance AI readiness, reduce resistance, and improve digital transformation performance.