Innovating with AI: How Innovative Attitude, Peer Influence, and Task-Technology Fit Shape AI Appropriation in Project Management

Abstract

The rapid diffusion of generative artificial intelligence (AI) tools is reshaping project management practices, yet significant variation remains in how professionals creatively appropriate these technologies. This study investigates the drivers of AI appropriation in project management by integrating Adaptive Structuration Theory (AST) with Task–Technology Fit (TTF) theory. The research examines how innovation attitude, peer influence, and task–technology fit influence AI-enabled creative behaviour, while also assessing the moderating role of organizational culture. A quantitative cross-sectional survey was conducted among 234 project management professionals working in Pakistan’s information technology and logistics sectors. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that task–technology fit is the strongest predictor of creative AI appropriation, followed by innovation attitude and peer influence. Furthermore, organizational culture significantly strengthens the relationships between these antecedents and creative behaviour, highlighting its role as a contextual amplifier of AI-enabled innovation. The model explains 71.5% of the variance in creative behaviour, demonstrating substantial explanatory power. The study contributes to the literature by extending AST to generative AI contexts, empirically integrating AST and TTF in a unified framework, and providing evidence from an emerging economy with collectivist cultural characteristics. Practically, the findings suggest that organizations seeking to leverage AI for innovative project outcomes should prioritize task-aligned AI tools, cultivate innovation-oriented mindsets among professionals, and develop supportive organizational cultures that encourage experimentation and collaborative learning.

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