Global mergers and acquisitions activity accelerated in the first quarter of 2026, pushing aggregate transaction value past $1.2 trillion even as the number of deals fell. The apparently contradictory trends reflect larger, higher-value transactions closing amid an otherwise quieter deal landscape, with AI considerations playing a central role in acquirer decision-making.
According to LSEG data cited in reporting, total transaction volumes exceeded $1.2 trillion for the quarter. While deal count dropped 17% year-over-year, the transactions that completed tended to involve larger companies, lifting total deal value by 26%. Four of the six largest transactions were tied to companies commonly viewed as beneficiaries of the AI boom.
Executives and bankers said a sizable pipeline of additional deals remains active despite geopolitical friction, energy price swings and the uneven economic consequences of AI adoption. Historically, firms have leaned on strategic acquisitions to navigate periods of disruption, and AI is increasingly a decisive factor in how buyers assess targets.
The technology is reshaping the way buyers value potential acquisitions. Firms perceived as AI winners are attracting higher interest, while those judged vulnerable to AI-driven competition face valuation pressure. That split is most pronounced in the software sector.
For example, the iShares Expanded Tech-Software Sector ETF (NYSE:IGV), which tracks the largest U.S. software companies, has declined as much as 25% this year, markedly underperforming the broader market. That valuation reset has chilled appetite among acquirers for software companies investors view as exposed to AI disruption.
To probe how these dynamics are reshaping M&A in software, Investing.com spoke with Zach Haarer, Co-Founder and Managing Partner at Kaizen Equity Partners. Haarer framed the difference between software that AI threatens and software that AI amplifies in functional terms rather than by company size.
"If your software is a thin layer sitting on top of a generic workflow, like task management or basic CRM, AI agents can replicate that functionality for a fraction of the cost. Those businesses are exposed. But if your software is a vertical system of record embedded in a mission-critical industry workflow, AI is a tailwind. It makes your product more valuable, not less."
Haarer emphasized that many vertical software businesses possess deep moats. Their customers do not rapidly switch because the domain expertise, regulatory compliance and workflow integration that underpin those products required years to develop. "You can’t "vibe code" a replacement for software that manages medical device compliance data or runs payroll for a niche industry," he said.
He pointed to a concrete outcome from one portfolio example: "One of our clients increased their EBITDA margins from 30% to 80% because AI reduced their development costs while simultaneously enabling them to build new features on top of their proprietary dataset. The software got stickier and more profitable at the same time."
Haarer described the market as bifurcating. Horizontal SaaS names face heightened buyer scrutiny over AI disruption risk, while capital is concentrating in vertical, high-retention SaaS with defensible moats. He said this segmentation is evident in competitive tension during sale processes: "We’re seeing upwards of 30 bids on a single process and averaging over 20 bids per deal this quarter. Buyers are competing aggressively for quality vertical assets."
When it comes to proving AI readiness to prospective acquirers, Haarer said foundational business metrics still matter most. "AI readiness is certainly a bonus, but not a requirement. The foundation is still the same. Strong retention, strong margins, embedded workflows, defensible market position. AI capability is the cherry on top that can add competitive tension to a process, but it’s not what makes or breaks a deal."
The discussion also touched on geographic valuation questions. Some market participants argue there is a valuation gap between fast-growing European software firms and their U.S. peers. Haarer pushed back on that framing, saying strong fundamentals drive outcomes regardless of geography. In his view, companies with solid metrics still command strong returns and increasingly draw U.S. investors looking globally for high-quality vertical software businesses.
For buyers and sellers alike, the takeaway is that AI is not a uniform force across software. In some subsegments it depresses value and cools deal activity; in others it accentuates product differentiation and intensifies bidding. As transaction activity continues, acquirers appear willing to pay premiums for vertical systems of record and other assets where AI acts as a multiplier rather than a substitute.
Looking ahead, bankers say a large pipeline remains in motion. How many of those processes will close and at what valuations will depend on where targets sit in the AI-disruption versus AI-acceleration spectrum and whether buyers prize long-standing customer retention, embedded workflows and defensible market positions over headline AI features.