Project-based organizations across industries increasingly rely on collaborative structures to manage complexity, uncertainty, and rapid technological change. The effectiveness of these organizations depends not only on technical competence but also on the quality of collaboration, team diversity, leadership, and the integration of emerging digital and generative technologies. Drawing strictly on established academic and practitioner literature, this study develops a comprehensive and integrative analysis of how team performance, cross-functional collaboration, organizational structure, leadership, and machine learning–enabled tools jointly influence project success. The article synthesizes insights from project management, organizational behavior, digital transformation, and artificial intelligence–enabled management frameworks to construct a holistic conceptual understanding of collaborative intelligence in modern project environments. Using a qualitative, theory-driven research methodology, the study examines how structural diversity, leadership practices, and generative AI frameworks reshape collaboration dynamics, decision-making processes, and resource allocation across global and cross-functional teams. The findings suggest that collaboration acts as a critical mediating mechanism between organizational design and project outcomes, while leadership and technology function as key enablers that amplify or constrain collaborative effectiveness. The discussion highlights significant implications for theory and practice, including the redefinition of team boundaries, evolving leadership roles, and the ethical and operational considerations of AI-supported collaboration. The article concludes by outlining future research directions that emphasize longitudinal studies, cross-industry comparisons, and deeper investigation into human–AI collaboration within project-based organizations.

Project success, team performance, cross-functional collaboration, leadership

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