Artificial intelligence in entrepreneurial project management: a review, framework and research agenda

Purpose This paper delves into the transformative impact of artificial intelligence (AI) across diverse sectors, notably project management. It examines the potential of AI to revolutionize project management processes within entrepreneurial ventures, where agility, efficiency and innovation reign supreme. Design/methodology/approach Through a comprehensive analysis, this study navigates the intersection of AI and entrepreneurial project management. It meticulously dissects the opportunities AI presents, the hurdles it introduces and the optimal strategies for harnessing its capabilities effectively. Drawing insights from complexity theory, a framework is crafted to delineate AI’s capacity to substitute human involvement, elucidating key considerations for transitioning to a digitally-driven paradigm in entrepreneurial project management. Findings The study underscores AI’s potential to augment project management processes significantly, particularly in fostering agility and innovation. However, challenges persist, necessitating adept navigation to maximize AI’s benefits. The framework delineates the extent to which AI can supplant human roles, offering crucial insights into the digital transformation of entrepreneurial project management. Practical implications Practitioners are equipped with valuable guidance on leveraging AI effectively, enhancing organizational agility and performance. Understanding the implications of AI adoption fosters informed decision-making in the realm of project management. Social implications The integration of AI in entrepreneurial project management signifies broader societal shifts toward digitalization and automation. Insights from this study contribute to navigating these transformations, fostering greater resilience and adaptability in entrepreneurial endeavors. Originality/value This study offers a novel perspective on the intersection of AI and entrepreneurial project management, shedding light on unexplored terrain. By drawing on complexity theory, it advances a nuanced understanding of AI’s implications, paving the way for future research avenues in this dynamic field.