Artificial Intelligence and Merger and Acquisitions
Authors:
Yue Fang, Zhejiang University
Yingxuan He, Zhejiang University
Zilong Zhang, Zhejiang University
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 postmerger 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.