AI Meets Data: Unlocking a New Type of Synergy in the AI Era

In an era where Artificial Intelligence (AI) becomes an academic buzzword and dominates boardroom discussions, one question remains particularly intriguing: does AI truly enhance a firm's ability to create value through mergers and acquisitions (M&A)? Our research explores exactly this—and the findings are interesting.

Here's the quick overview: firms with strong AI capabilities don’t just outperform others by applying AI in daily operations. AI capabilities also help them thrive in M&As, but only when paired with data-rich companies. Why? Because AI, as revolutionary as it is, cannot produce magic on its own. To unleash its full potential, it desperately needs something to feed on: data, which is aptly called the "oil" of the AI era.

Measuring AI Capabilities: Skills Matter

As intuitive as our story may seem, as academic researchers, we must back every claim with rigorous quantitative evidence. Yet measuring a firm's AI capability is inherently challenging. Rather than relying on firms' potentially exaggerated claims about how AI-savvy they are (or are going to be), we focused on a crucial and quantifiable element: human talent. Companies are increasingly willing to invest millions in securing the brightest AI minds (Meta is offering up to $100 million to lure AI talent, says OpenAI's Sam Altman | TechSpot). Leveraging data from a major professional social network, we analyzed millions of employee profiles to objectively identify which companies genuinely possess the AI expertise necessary to succeed.

Big Gains for AI-Driven Deals

What did we discover? Companies rich in AI talent experience significantly better market reactions around their acquisition announcements. In fact, a mere one-standard-deviation increase in AI capabilities boosts announcement returns by a whopping 52%! This isn't just statistical noise—it's clear evidence that markets reward firms equipped to harness AI.

But wait—what’s driving this astonishing result? The real magic happens when high-AI acquirers merge with data-intensive targets. AI needs data to train models and innovate, while data assets desperately need AI to convert raw information into actionable insights. This is precisely the synergy that markets reward—and our research robustly confirms this pairing is both strategic and profitable.

Firms Know What They're Doing

In an efficient market, if deals of certain types create financial gains, they surely will be more likely to occur. Our research finds that not only does the pairing of high-AI firms and high-data firms create better financial returns, but such pairings are also more likely to happen: High-AI firms are more likely to acquire data-rich companies, underscoring the deliberate strategy behind their deal-making. Also, the strategic sense behind these AI-driven mergers isn’t lost on companies themselves. Our analysis shows that high-AI firms actively seek out data specialists even before mergers, clearly preparing themselves for integration and synergy. 

Innovation Takes Flight Post-Merger

Financial returns are just part of the story. We also care about real post-M&A outcomes. To validate whether real innovation emerges from this synergy, we dug deeper into patent filings and citations after mergers. Sure enough, mergers pairing high-AI acquirers with data-rich targets witnessed a surge in patents and citations—particularly those related to AI technologies. This indicates that not only do markets recognize the immediate financial value, but the integration of AI and data genuinely enhances firms’ innovation capabilities, setting the stage for long-term competitive advantages.

Policy and Market Implications

These findings carry profound implications for policymakers, business leaders, and investors. For policymakers, by highlighting the synergistic relationship between AI talent and data, our results also contribute to the ongoing academic and policy debate on the optimal balance between protecting data privacy and unleashing the full potential of economic efficiency, in Europe (Commission launches consultations on the future of EU data legislation | Shaping Europe’s digital future), the US (Data Privacy in the Digital Age: A Comparative Analysis of U.S. and EU Regulations – University of Cincinnati Law Review Blog), and other parts of the world. Firms and investors, meanwhile, gain a valuable playbook for leveraging AI: prioritize acquisitions that not only add scale or market share but, crucially, deliver complementary data assets. If you’re thinking about AI as just another buzzword—think again. In today's market, it's AI plus data, or bust.

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Yue Fang is an Assistant Professor of Finance and a 100 Talent Researcher at the School of Economics at Zhejiang University

Yingxuan He is a Researcher at Zhejiang University

Zilong Zhang is an Associate Professor at Zhejiang University

This blog is based on a paper presented at the 9th Annual Mergers & Acquisitions Research Centre (MARC) Conference. Visit the event page to explore more conference-related blogs.

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