Title: Artificial Intelligence and Mergers and Acquisitions

Authors: Yue Fang (Zhejiang University), Yingxuan He (Zhejiang University), Zilong Zhang (Zhejiang University)

Abstract: Using detailed data on employees’ job skills, this study examines the relationship between firms’ artificial intelligence (AI) capabilities and mergers and acquisitions (M&As). Our findings indicate that firms with higher concentrations of AI talent (high-AI firms) achieve superior acquisition performance during announcement periods. Further analysis shows that this superior performance is more pronounced among acquisitions of data-intensive targets. We then test whether firms leverage the strategic complementarity between AI expertise and data resources, and find that high-AI firms are significantly more likely to merge with data-intensive firms and actively hire data analytics specialists. Moreover, mergers with high-AI acquirers and data-intensive targets experience increased filings and citations of AI-related patents, suggesting better innovation capabilities in the post-merger period. Our results are robust to an instrumental variable approach and are not explained by higher post-merger mobility of AI-skilled employees or better pre-merger fundamentals of acquirers. By identifying AI-data synergy as a key driver of value creation in M&As, this research sheds light on how technological advancements are reshaping firm boundaries.