Proceedings of the 7th International Conference on Advanced Research in Management, Business and Finance, 2024
Year: 2024
DOI:
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Leveraging Artificial Intelligence for Effective Strategic Alliances: A Practical Guide
Prof. Dr. Pooya Tabesh
ABSTRACT:
Purpose: As businesses recognize the immense value of collaborative partnerships, integrating artificial intelligence (AI) into alliance strategies opens new opportunities for enhanced decision-making and performance. This article aims to explore the impact of AI on the key alliance success factors (i.e., the effectiveness of partner selection, contractual provisions, and coordination/communication of efforts) by explaining the significant role that AI-enabled tools could play in addressing alliance challenges. Design/methodology/approach: In this conceptual work, we combine existing knowledge about using AI in decision making with the findings of strategic alliances literature to contribute to theoretical and practical understanding of how AI can improve alliance management capability and performance. Findings: This article explains the ways AI can improve decision-making throughout the three main phases of the strategic alliance lifecycle. After discussing the classic challenges in alliance formation, design, and post-formation phases, we explain how some AI-enabled tools can address the alliance challenges in partner selection, contractual provisions, coordination, and communication. Originality: Our work is among the first to explore and discuss the application of AI technologies to enhance alliance performance in various phases of alliance formation and management. In doing so, we explain how AI can augment managerial decision making regarding strategic alliances. Research Implications: Our work contributes to both strategic alliance and human-AI augmentation literatures. First, we contribute to the scholarly conversations about strategic alliances in the strategic management literature by introducing AI as a technology that can enhance alliance management capability. In addition, we contribute to human-AI augmentation literature by clarifying and explaining the division of alliance formation and implementation tasks between AI tools and organizational decision-makers and identifying opportunities for AI-human collaboration. Practical Implications: Our work contributes to the practice of alliance management by explaining the ways AI can assist firms with limited alliance experience to enhance alliance management capability and increase the odds of alliance success.
keywords: Artificial intelligence (AI); strategic alliance; augmentation; alliance management capability