Mega AI Deals Drive Global M&A Volume to Record First-Half High
Claire Weston
Global M&A volume surged 44% year-on-year to top $3 trillion in H1 2026, powered by six AI-linked deals each exceeding $50 billion — yet total deal count fell 3%, signaling a market where big money is concentrating while smaller players sit out.
How did $3 trillion stack up?
H1 saw six deals above $50 billion — the most ever recorded by Mergermarket.
The two largest: OpenAI's $122 billion funding round and NextEra Energy's proposed $67 billion acquisition of Dominion Energy.
This means → AI is not just driving tech M&A; its power-consumption demands have pulled the energy sector into the deal wave too.
Deal count fell — so who is actually buying?
Deals above $10 billion accounted for 42% of all M&A value, yet total deal count dropped 3% year-on-year.
In plain terms = the M&A market is not broadly booming — it is "giants shopping while everyone else watches."
Mergermarket executive editor Lucinda Guthrie put it this way: markets have "largely chosen to ignore" a string of would-be black-swan events "and press on."
Why is the U.S. surging hardest?
U.S. M&A value jumped 72% year-on-year in H1 — the fastest growth of any market globally.
Guthrie pointed to a widespread "front-running" mindset — locking in deals before the Trump administration's looser regulatory window closes.
"There is a feeling that if you don't get these landscape-changing deals done now, under a different administration you may not get the chance," she said.
Why are smaller companies sitting out?
Large corporates with strong balance sheets are driving deals; mid-sized and smaller firms remain on the sidelines due to high rates, macro volatility, and geopolitical risk.
This reflects a widening two-tier split: those with capital are accelerating, while those without are forced to wait.
Can this engine keep running in H2?
Mergermarket takes a cautious view on H2 AI-linked M&A: if rates stay high or rise further, activity could slow.
Guthrie also flagged rising doubts over whether the tech sector can turn massive AI infrastructure spending into actual profit.
In plain terms = if the money poured into AI doesn't earn its way back, the M&A boom it underpins cools with it.
Content is for reference only, not financial advice.