Paper Number

ICIS2025-2224

Paper Type

Complete

Abstract

Artificial Intelligence (AI) is becoming integral to efficient project management. To understand its potential, this study conducts a structured literature review on the role of AI in project management teams and their contribution to ambidextrous organizational learning. Drawing on intellectual capital theory, we identify ten core team characteristics, categorized under exploration and exploitation. Findings emphasize the need not only to balance these two dimensions but also to distribute intellectual capital evenly across its various forms. Building on this, we propose the concept of ambidextrous AI-driven project management, which underscores how AI can be systematically integrated into project teams. This approach highlights the dual importance of leveraging existing knowledge while fostering innovation through AI support. The study also outlines potential pathways for implementing ambidextrous AI-driven project management and provides directions for future research in this emerging field, offering both theoretical and practical implications for organizations.

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Dec 14th, 12:00 AM

To Exploit or to Explore: Achieving Ambidextrous AI-Driven Project Management through Intellectual Capital

Artificial Intelligence (AI) is becoming integral to efficient project management. To understand its potential, this study conducts a structured literature review on the role of AI in project management teams and their contribution to ambidextrous organizational learning. Drawing on intellectual capital theory, we identify ten core team characteristics, categorized under exploration and exploitation. Findings emphasize the need not only to balance these two dimensions but also to distribute intellectual capital evenly across its various forms. Building on this, we propose the concept of ambidextrous AI-driven project management, which underscores how AI can be systematically integrated into project teams. This approach highlights the dual importance of leveraging existing knowledge while fostering innovation through AI support. The study also outlines potential pathways for implementing ambidextrous AI-driven project management and provides directions for future research in this emerging field, offering both theoretical and practical implications for organizations.

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