Citigroup sees record M&A in 2026 driven by AI

Citigroup forecasts a record year for M&A activity in 2026, driven by AI despite recent volatility in tech stocks and broader markets.

Senior bankers noted that recent sell-offs across tech, commodities, and cryptocurrencies may create winners and losers, but overall valuations remain healthy.

The bank highlighted a pipeline of AI-related deals, including Singapore’s S$13.8 billion (US$10.8 billion) acquisition of ST Telemedia Global Data Centres by KKR and Singtel, as the largest M&A deal in four years.

Experts expect 2026 to be the strongest year ever, supported by economic growth, low inflation, and abundant private equity capital.

🔗 Source: South China Morning Post

🧠 Food for thought

Implications, context, and why it matters.

The M&A boom is hiding a capital gap for AI infrastructure

Private equity cash can look plentiful, yet the spending needed for data centers and other compute gear for AI remains far larger.
Bain estimates that meeting AI compute demand by 2030 needs about $500 billion in capital investment each year, which then needs $2 trillion in annual revenue to support it 1.
Even under optimistic assumptions, Bain still calculates an $800 billion annual revenue shortfall, and says the gap is far beyond any expected government subsidies 1.
Dealmaking picked up in 2025, yet M&A funding hit a 10-year low, only 7% of cash spending across almost 700 S&P World Index companies, as budgets shifted to tech stacks, robots and AI, factories, and energy farms 2.

Power and land are turning into deciding factors in the AI economy

The S$13.8 billion ST Telemedia Global Data Centres deal focuses on locking up sites for physical infrastructure with reliable access to power.
The purchase gives KKR and Singtel control of a platform with more than 100 data centers and 2.3 gigawatts of total design capacity, as AI compute demand grows more than twice the rate of Moore’s law (a long-running observation that chip performance tends to improve rapidly over time) 3, 1.
Constraints are already tight, and US demand alone could reach 100 gigawatts by 2030, adding pressure to a power grid that has seen relatively flat load growth for the past 20 years 1.
Companies that secure grid connections, land, and permits can gain leverage, and access to AI may depend on electricity supply as much as software 4.