Global M&A industry trends

In the world of AI, it seems, bigger is better. M&A is being pulled into the same scale dynamic.

The supersize theme is already visible in public markets, where SpaceX’s public debut has become the largest public offering ever, and Anthropic and OpenAI have both confidentially filed for IPOs. Capital expenditure numbers are equally supersized, with just four companies, Alphabet, Amazon, Meta, and Microsoft, expected to spend more than $700bn in 2026 building the infrastructure they need to meet soaring demand for AI services. 

Capital commitments are breaking precedent too, with major investors and technology groups providing tens of billions of dollars in equity for data centres and other projects.

Sovereign debt is also rising to record levels, adding another pressure point as AI, infrastructure, and M&A compete for capital. 

M&A has joined this supersize party. This year, we’ve seen the largest ever deals in sectors from utilities to streaming to real estate investment trusts. Global deal value is on track to hit $4tn in 2026, up by about 13% year-on-year, even though deal volumes are declining. M&A transactions above $5bn have made up almost half of total global deal value so far this year. That’s double their share just two years ago. Strip out these megadeals, and deal value is down by 4%. 

The data show that the K-shaped M&A market we noted back in January is intensifying. Deal values from megadeals are on track to increase year-on-year by 40% in 2026 if the current pace continues. At the top, well-capitalised buyers are pursuing scale, resilience, and strategic transformation. NextEra Energy’s proposed $67bn combination with Dominion Energy is a clear example—it’s a deal designed to create the world’s largest regulated utility business and a platform for rising power demand. 

Below that, many mid-market dealmakers remain constrained by geopolitical uncertainty, valuation gaps, slowing growth, higher inflation and interest rates, and a private equity exit backlog that remains stubbornly high. AI is redirecting capital towards data centres, power, grid infrastructure, and frontier platforms while forcing buyers to reassess which sectors and business models are most exposed to disruption. 

For dealmakers, AI is not just changing where capital goes. It’s beginning to reshape how deals get done. The technological capability to substantially streamline and accelerate the deals process is already in place, touching areas from target screening and due diligence to valuation and value creation. What will the deal of the future look like? How far off is it? And what can dealmakers do to prepare?

The deal of the future will look very different, and it’s closer than you think. Dealmakers are already using AI tools to speed up transactions, improve transparency, and analyse far more data with much less friction. The question is no longer whether AI will reconfigure the M&A process, but how quickly and what it will ultimately look like.

The biggest shift has come in the past 12 to 18 months, as AI models have moved beyond pattern recognition into reasoning. Early models could help identify potential targets. Newer models are beginning to support more complex M&A problem-solving, from commercial analysis and data room review to valuation modelling and value creation planning.

The tipping point will come when AI agents are trusted to exercise judgement at key stages of the deal process. Don’t be surprised when dealmakers start sending AI agents into the market to identify acquisition targets, test strategic fit, run the first commercial assessment, scan the data room for risks, build the investment committee case, draft the value creation plan, and prepare first-cut transaction documents. Because some of this is already happening.

In the market, AI-enabled data rooms and deal platforms have begun to analyse and summarise large volumes of documents, surface potential risks, and help deal teams answer diligence questions faster. Best-in-class private equity and corporate development teams are starting to use AI to synthesise commercial, operational, and financial information on potential targets. At PwC, we are reimagining our own due diligence approach by embedding purpose-built AI, using coding agents to accelerate analysis, and examining each stage of the deal life cycle for opportunities to improve speed, insight, and execution. We are working alongside clients to co-create and build their own deal agents and AI-enabled solutions for their own transaction processes, from workflow redesign and data readiness to governance, controls, and practical tools that support better, faster deal decisions.

Important hurdles remain. Regulatory questions, investor concerns, trust, and unresolved issues around liability continue to slow AI adoption in M&A. AI also doesn’t always have access to all the context that shapes deal judgement, such as internal discussions and the nuance that builds through diligence and years of experience. A transcript can capture the words—it may not capture whether a speaker was enthusiastic, cautious, or sarcastic.

That’s why human judgement will remain central. The deal of the future may be faster, more transparent, and less fragmented, but high-stakes M&A decisions still depend on trust, challenge, and accountability. AI can surface insights, test assumptions, and accelerate analysis. Humans will still need to interpret the context, build confidence with stakeholders, and make the decisions that matter most.

The same is true after the deal closes. AI can help sharpen the value creation plan, identify operational levers, and track execution continuously. But turning a deal thesis into results still requires people to roll up their sleeves, align leadership teams, untangle complex systems and processes, and drive transformation through the business.

Over time, AI could make private markets more liquid by making assets easier to evaluate and trade. But the deal process will not simply be anchored around machines. It will be built around the combination of AI-enabled insight and human judgement. That is where trust will sit.

Global M&A value is on track to reach approximately $4tn in 2026, up 13% from 2025 and the second-highest level outside the pandemic-driven spike of 2021. But the headline number masks a narrower recovery. Deal volume is moving in the opposite direction, with approximately 42,000 deals projected for the full year, down 13% from 2025.

Megadeals are the dominant force. Transactions above $5bn now account for 48% of global deal value, compared with 39% in 2025 and 26% in 2024. Strip out those largest deals, and the market looks more subdued, with deal value down by 4% year-on-year.

Regional trends reinforce the uneven shape of the market. The Americas accounted for 61% of global deal value in early 2026, despite representing only 28% of global deal volume. That value concentration was led by US megadeals, which accounted for 64% of total US deal value, up from 54% in 2025, even as volumes fell. Europe, the Middle East, and Africa’s (EMEA) share of global value also increased, supported by several large transactions, while its share of volume remained stable. Asia Pacific tells a different story: its share of global deal volume rose to 37%, largely due to stronger activity in China, Japan, and some parts of Southeast Asia, but its share of deal value fell to 16%, reflecting fewer megadeals and smaller average transaction sizes across the region compared to the Americas and EMEA.

The scale of AI investment is now changing the shape of dealmaking. Capital is flowing into frontier models, data centres, digital infrastructure, energy, and strategic partnerships at a pace traditional M&A alone does not capture. Increasingly, that capital is moving through minority investments, joint ventures, partnerships, and other structures rather than control-based acquisitions. 

The AI buildout is also creating new investment and services models. Anthropic, Blackstone, Hellman & Friedman, and Goldman Sachs announced a new enterprise AI services company in May 2026 to help companies deploy Claude into core operations. The model points to a broader shift: AI is not only changing which assets attract capital, but also how investors seek to create value across portfolios.

The implications for M&A are twofold. First, AI is creating deal appetite for data centres, power generation, grid infrastructure, cooling, connectivity, engineering and construction, and industrial supply chains. Second, it is competing with traditional M&A for capital, management attention, and risk appetite.

That competition is part of a much larger infrastructure story. PwC’s Global Infrastructure Outlook 2025-50 projects approximately $150tn for cumulative infrastructure spending over the next 25 years, an almost 60% increase in annual spending from 2025 levels. AI is now becoming one of the forces determining where that capital goes, including towards digital infrastructure, energy security, electrification, grid capacity, and the critical inputs needed to support them.

Our analysis of the 100 largest corporate M&A transactions finds that while AI remains an important theme, its role is becoming more selective. In 2025, approximately one-third of the deals analysed cited AI as part of the strategic rationale. In the first half of 2026, this fell to 17%, with references concentrated in sectors closest to the AI buildout, led by technology, manufacturing, and power and utilities. 

Interest in AI has not faded. Buyers, however, are becoming more disciplined about where AI creates durable demand, where it compresses value, and where a partnership or minority investment may be a better route than full ownership. 

Sector implications: AI remains central, but the story is broadening 

A sector pattern is becoming apparent. Dealmaking activity remains strong for assets that enable the AI economy, such as compute capacity and energy supply to electrification, cooling, connectivity, and specialised components. Related end markets, including engineering, construction, and industrials, are also attracting investor attention.

Buyers are more cautious in sectors where AI is seen as potentially disrupting revenue models or service delivery. Software M&A aimed at acquiring AI capabilities has cooled from 2025 levels, with sector valuations re-rated lower. The same scrutiny is spreading to IT services, professional services, insurance brokerage, and asset and wealth management, among other sectors. Across these sectors, deal volumes declined in early 2026 compared with the prior year, suggesting buyer decision-making is reacting to AI-related uncertainty.

This uncertainty may be redirecting capital towards assets with lower perceived disruption risk or clearer demand drivers. We are seeing signs of this happening in healthcare, pharmaceuticals, consumer goods, and industrials, industries in which certain assets are attracting renewed attention, particularly where companies see opportunities to build scale and resilience. Valuation multiples have risen in some subsectors perceived to be more insulated from AI disruption. That shift is notable: AI is not only creating new winners and losers, but it is also challenging historical assumptions about which assets deserve a premium.

Technology continues to generate the largest number of megadeals, including Amazon’s 2026 investments in Anthropic and Globalstar, as well as several other large investments and capital commitments into OpenAI and Anthropic from major investors and technology groups. But the megadeal market is no longer just a technology story, with large transactions in energy, consumer markets, industrials, and pharmaceuticals pointing to a broader shift in strategic M&A. Among these megadeals are the NextEra Energy and Dominion Energy combination, McCormick’s proposed combination with Unilever’s food business, Sysco’s acquisition of Jetro Restaurant Depot, and KONE’s combination with TK Elevator. These transactions all suggest that scale and resilience are becoming more important strategic priorities.

The geopolitical environment is reinforcing that shift. Companies are using M&A to strengthen supply chains, secure access to critical capabilities, build market position, and improve long-term competitiveness.

Dealmakers need to act, but selectively. Successful buyers will be those that can see a clear strategic need, test the value case rigorously, and move decisively when the right asset becomes available. Conviction matters. But it will be tested. Softer growth, inflation pressure, higher-for-longer interest rates, and geopolitical volatility could all make the next phase of dealmaking more difficult.

More capital is needed just as capital could become more expensive. The market has absorbed the first wave of shocks, but its resilience remains unproven. Higher energy and raw materials prices, slowing growth, and rising government debt could all increase costs. Outstanding sovereign bond debt in OECD countries reached an all-time high of $61tn in 2025, up from $55tn in 2024.

M&A traditionally struggles when interest rates rise and growth slows. That risk matters now because the funding demands are multiplying. Higher defence spending, AI infrastructure, and the broader infrastructure buildout are all competing for funding.

The International Monetary Fund’s April 2026 outlook shows how quickly the downside could build. Even its more benign scenario points to global growth falling to 3.1% from 3.4% in 2024–25, with headline inflation at 4.4%. In a more severe scenario, growth falls to 2% in both 2026 and 2027 while inflation exceeds 6%.

Geopolitical risks could add to that pressure. Fragile energy markets could keep inflation higher for longer, weigh on growth and make financing conditions more difficult. That would be an extra challenge for M&A, particularly in regions where growth is already muted and the AI capital-expenditure supercycle is providing less of an offset than in the US. 

So far, financial markets have largely absorbed these risks. But the combination of softer growth, sticky inflation, and higher-for-longer interest rates would make dealmaking harder, particularly if trade disruption persists or capital costs rise.

Other pressure points also bear watching, starting with the private equity exit backlog. As of March 2026, according to PitchBook data, private equity funds globally held 32,979 portfolio companies—little changed from 32,776 at the end of 2025. The bigger issue is aging: 34% of those companies had been held for more than five years, up from 25% in 2025. If liquidity tightens, those hold periods could become harder to extend.

Private credit is another important test. It has become an important source of flexibility for dealmakers, but recent borrower defaults, and credit losses and concerns about exposure to sectors such as software have prompted more redemption requests and closer regulatory scrutiny in the UK, the US, and Europe. Even so, PwC’s Global Private Credit Survey 2026 found that 80% of portfolio managers still expect allocations to private credit to continue to grow. The next phase may test private credit’s resilience through its first cycle as a major asset class.

The key takeaway for dealmakers? Prepare before markets force the issue. Scenario planning should be more rigorous, financing assumptions more conservative, and downside cases more explicit. In a supersized market, discipline matters more than ever.

The only thing that seems truly certain for dealmakers is that they will need to manage their way through uncertainty. Again. Events in early 2026 have reinforced that point: geopolitical volatility and the massive capital needs of AI are weighing on traditional M&A activity, even as a select set of megadeals has kept headline value elevated.

For dealmakers, resilience now has two dimensions. First, the ability to withstand macroeconomic, geopolitical, and technological disruption. Second, the foresight to prepare for a deal process that is becoming faster, more data-led, and more AI-enabled.

Six questions should be top of mind for dealmakers:

• Are we on the right side of AI disruption? If not, what capabilities, partnerships or acquisitions would change that?
• How will AI impact the target? A comprehensive diligence lens spanning commercial, market, technology, operational, and financial factors can help dealmakers answer this must-know question.
• Where do we need to supersize? In a market dominated by scale, leaders need to know where bigger creates advantage and where it adds only complexity or risk.
• Is our capital allocation keeping pace with the AI buildout? The next wave of opportunity may sit across data centres, power, grid infrastructure, digital connectivity, and the supply chains that support them. Importantly, are we allocating enough capital to our own innovation and disruption?
• How resilient is our financing plan? Dealmakers should test what happens if rates stay higher, growth slows, or liquidity tightens.
• Are we ready for the deal of the future? AI is already changing target screening, diligence, valuation, and integration. The question is whether governance, controls, and decision-making are keeping up.

The next phase of M&A will reward preparedness. In a market being reshaped by AI, scale, and tougher capital decisions, the winners will be those who move with speed, conviction, and discipline.