Why This May Be the Biggest M&A Year in History

A recent a16z article made the case that 2026 could be the biggest year for mergers and acquisitions (M&A) on record. That's a bold claim, but the reasoning behind it is worth taking seriously, because the forces driving this cycle are structurally different from what we've seen before.

The underlying dynamics of how companies grow, how capital gets allocated, and how public and private markets interact have all shifted in ways that make acquisition more urgent and more rational than it's been in years. This isn't just pent-up deal flow finally breaking loose. Speed, AI, and institutional design are converging to reshape why deals happen and who wins when they do.

Why this cycle looks different

For most of the last decade, corporate M&A felt discretionary. Capital was cheap, but growth was available organically, and many companies convinced themselves they could build whatever they needed to internally. That assumption held for a while. It's getting harder to defend now, particularly as AI shifts from experimentation to core infrastructure.

When the cost of being late becomes existential, acquisition stops being a balance sheet decision and starts being an operating one. You're no longer buying a company primarily for its revenue or market share. You're buying time, teams, and systems that would take years to assemble from scratch.

That's why this cycle may look different from the ones that came before it. There's less financial engineering and more strategic urgency. Fewer roll-ups designed to juice returns. More deals designed to close real capability gaps.

In private equity, I watched firms spend months building conviction around a deal, stress-testing every assumption, debating entry multiples and downside scenarios. That discipline matters. But the firms that won weren't the ones who modeled the most cases; they were the ones who recognized when speed of action was the real edge.

The same logic applies to corporate M&A in 2026. If this does turn out to be a record year, it will be because speed became more valuable than optionality.

AI makes capital allocation legible again

There's a deeper shift underneath the M&A headline, and it has to do with how capital works inside companies.

For a long time, throwing more money at a problem didn't reliably accelerate outcomes. Progress was constrained by coordination costs, headcount bottlenecks, and diminishing returns on incremental spend. Capital was abundant, but its marginal impact was hard to see, let alone measure.

AI breaks that pattern. Compute, data, and spend now map much more directly to real capability. If you invest aggressively in AI infrastructure, you do more than grow faster. You often learn faster, iterate faster, and lock in advantages that are difficult to unwind. The relationship between input and output has become more legible than it's been in a long time.

This helps explain why we're seeing both larger private rounds and renewed interest in IPOs at the same time. Those aren't contradictory signals. They reflect a world where capital allocation has become an operational discipline, not just a financial one.

Executives are being forced to ask a harder question than they're used to: Where does additional capital actually compress timelines or change outcomes? That's fundamentally different from optimizing burn or protecting margins, and it's a question many organizations haven't yet internalized. The ones that answer it well will be the acquirers. The ones that don't will be the targets.

The public company pressure cooker

Private companies can invest ahead of returns. They can tolerate volatility, absorb inefficiency, and justify long build cycles without quarterly scrutiny.

Public companies, especially large ones, operate under a very different contract. Shareholders expect annual returns on massive equity bases, and patience for long-term experimentation is limited. Every dollar spent on something that doesn't show up in next quarter's numbers needs a compelling story attached to it.

That tension shows up clearly in AI adoption. Even when leadership understands the opportunity, internal investment competes with near-term performance, regulatory scrutiny, and organizational inertia. The result is a gap between what companies know they need and what their operating structure allows them to build on their own timeline.

In that context, acquisition becomes a release valve. Buying capability is often easier than defending years of uneven internal investment to the market. It's faster, more legible to analysts, and easier to explain on an earnings call.

If the a16z (Andreessen Horowitz) forecast proves right, a meaningful portion of the next M&A wave will be driven by this dynamic because the structure they operate in leaves them few alternatives. The public markets, in a sense, are pushing companies toward the deal table whether they planned to be there or not.

Institutions that grow vs. institutions that deploy

There's a layer underneath all of this that I find more interesting than any single M&A prediction: the question of institutional design.

The a16z piece draws a comparison to Goldman Sachs, and it's a useful one. Goldman's story is often told as the story of a financial institution. But if you zoom out, it's the story of a partnership that behaved entrepreneurially for generations. It wasn't built through a single grand plan or a wave of mergers. It was built incrementally, as partners raised their hands to expand into new geographies, new products, and entirely new businesses, often long before there was consensus that those moves would work.

What makes a16z distinctive is a similar structural bet. Instead of optimizing for a narrow definition of efficiency, the firm keeps investing in capabilities around founders, policy, research, and platform work that don't pay off immediately but widen the surface area of what it can do. That's not a strategy you can copy by reading about it. It's an operating model, and it compounds.

When capital allocation becomes a strategic weapon again, whether through AI investment, infrastructure spending, or M&A, the firms that win will be the ones that can repeatedly build new internal engines without losing their core identity.

Goldman did this over more than a century. a16z is attempting something similar in a very different era, but with the same underlying bet: that a firm designed to grow capabilities, not just funds, will outlast cycles and outperform peers who treat structure as an afterthought.

The operating model is the real story

As a founder who came out of private equity, what I find most compelling about this framing is that it shifts the conversation away from predicting markets and toward designing institutions. Markets come and go. Technology shifts. Cycles turn. But the operating model of a firm, how it makes decisions, how it invests internally, how much autonomy it gives its people, compounds over time.

I carried that lesson into building Meridian. The structural decisions were the ones that mattered most. These decisions were around how we organized information, how we built systems that would scale without breaking, and how we made sure the team could move with conviction instead of waiting for consensus.

That's the real lesson underneath the M&A forecast. The a16z piece is nominally about deal volume. But what it's actually about is how the next era of capital will favor firms that are built to grow, not just to deploy.

Whether you're investing or building, the question in 2026 is whether or not your organization is structured to act with conviction.

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Frequently asked questions

Why is 2026 expected to be a record year for M&A? 

Several structural forces are converging at once. AI is making capability gaps more urgent to close; public companies face pressure to acquire rather than build internally on slow timelines; and capital allocation has become more legible, meaning firms can see a clearer return on aggressive investment. This isn't just a backlog of delayed deals. The underlying reasons companies acquire have shifted toward strategic urgency and speed.

How is AI changing M&A strategy? 

AI changes the relationship between capital and capability. Compute and data investments now map more directly to measurable outcomes, which means acquirers can underwrite AI-driven targets with more confidence. At the same time, companies that fall behind on AI adoption face compounding disadvantages, making acquisition a faster path to closing the gap than building internally.

Why are public companies under more pressure to acquire than private ones? 

Public companies operate under quarterly earnings scrutiny, which limits their ability to invest in long-term, uneven internal builds. Private companies can tolerate years of experimentation without explaining it to shareholders. That structural difference means public companies often find it easier to buy capability than defend the cost of building it slowly, especially when the capability involves AI infrastructure.

What does institutional design have to do with M&A? 

The firms that perform best over multiple cycles tend to be the ones designed to grow capabilities internally, not just deploy capital externally. The article here draws a comparison between Goldman Sachs and a16z as examples of institutions that expanded into new areas repeatedly, often before consensus said those moves would work. M&A success depends on whether an acquirer's operating model can absorb and compound what it buys.

How should investment firms think about the 2026 M&A cycle? 

The core question is whether your organization is structured to act with conviction when the right opportunity appears. Firms that have clear processes for building internal conviction quickly, tracking deal context over time, and coordinating across teams will be better positioned than those still relying on fragmented workflows. Speed matters, but only when paired with the systems and institutional memory to support it.