After the collapse in software stock valuations, is the era of major AI mergers and acquisitions here?

After the collapse in software stock valuations, is the era of major AI mergers and acquisitions here?

Deutsche Bank believes that most companies' AI implementation is currently far behind market expectations, and the volatility in AI-related market capitalization is pushing companies to accelerate mergers and acquisitions.

According to "Chasing Wind Trading Desk," on February 26, Deutsche Bank's research team released a report stating that recent market fluctuations and the sell-off of AI concept stocks are forcing CEOs to quickly formulate AI strategies and clearly communicate these strategies to investors.

However, by 2025, only 11% of companies may have fully implemented at least one AI-related business function. This means that most CEOs are under tremendous pressure to accelerate AI adoption. Facing the pressure to implement AI, mergers and acquisitions are becoming the main method for many CEOs to catch up with their peers.

Data shows that the global external corporate transaction volume involving private AI companies (including acquisitions, minority equity investments, private placements, and public offerings) has surged from negligible levels around 2013 to nearly $40 billion annually between 2021 and 2024.

(Global external corporate transaction volume for private AI companies)

The report believes that the revaluation of software sector valuations at historic levels, continued heating up of private AI company M&A activity, and intensified global M&A pace differentiation are three trends that will deeply impact asset allocation decisions in the next year or two. Regional differences in regulatory uncertainty and the macro interest rate environment are the biggest variables affecting the pace and pricing of M&A.

Most Companies' AI Implementation Seriously Lagging, CEOs Under Heavy Pressure

Deutsche Bank pointed out that current AI adoption is uneven, with startups and large enterprises as pioneers. According to survey data cited in the report, in the second quarter of 2025:

Only 8% of companies said they would fully implement at least one AI business function before mid-year;Only 3% expect to complete implementation by year-end;11% of companies clearly stated that they have no plans to implement AI agents.

The International Monetary Fund (IMF) estimates that about 40% of jobs globally will be affected by AI, especially "cognitive" work. According to frequency analysis of keywords in S&P 500 earnings calls:

AI and machine learning consistently top the list of hot topics, with layoffs, chip shortages, and R&D investment also being the fastest growing topics;M&A discussions have clearly rebounded after the 2025 spring tariff shock, and its frequency growth has surpassed dividends and buybacks;The fastest-growing capital allocation theme over the past six months is capital expenditure and R&D.

(Increase in mentions of specific topics in S&P 500 earnings calls)

From an individual company perspective, industry leaders such as Marriott International, Amgen, and S&P Global have clearly expressed positive strategic attitudes towards AI in their earnings reports, viewing it as a net benefit rather than a threat to business.

It is worth noting that medium-sized enterprises with 50 to 249 employees have significantly lower AI usage rates.

They lack the flexibility and focus of startups, as well as the resources and data scale of giants, and are most likely to fall behind in the race. Acquiring ready-made AI capabilities through M&A is a realistic shortcut for them.

Software Valuation Slumps, M&A Window Opens Quietly

Fortunately, the market provides a window for acquisitions.

Since the market peak in mid-January this year, the software and services sector has been the worst performing group in the Russell 1000 Index, with a median decline of 25%. Its valuation ranking has dropped from third to ninth place.

(The software sector has ranked last in the Russell 1000 Index since January 12)

More importantly, after adjustment for growth expectations, software company valuations have become relatively average. In the U.S. market, its PEG ratio ranking has dropped sharply from 7th to 17th, while Europe fell from 3rd to 15th place. The valuation bubble has been significantly squeezed, giving corporate buyers more bargaining power at the negotiating table.

(PEG ratio adjusted for growth expectations: ranking drops from 7th to 17th)

As for M&A prospects: The U.S. will remain cautious, while Europe will show a "mixed picture." Deutsche Bank's M&A leading indicators show:

United States: The Q1 M&A recovery momentum may slow in Q2, due to rising policy uncertainty and mixed capital issuance signals;

(M&A momentum in Q2 2026 may slow)

Eurozone: Rising sovereign bond yields drag M&A prospects, under pressure in the short term;

United Kingdom: Benefiting from lower bond yields and strong stock market performance, M&A recovery may be faster than current market expectations.

(Forecast for M&A transaction numbers in the eurozone and UK in the next 3 months)

So, what kind of AI companies are most likely to be acquired? Deutsche Bank believes that the more specialized an AI company is, the more attractive it is to industry giants. They need tools that delve into specific verticals and solve concrete problems.

Private Equity Dominates Transactions, but Must Eventually Exit

A key structural change in the market is that financial buyers such as private equity now dominate global software M&A transaction share.

Data shows financial buyers such as private equity have jumped from 28% share in the 2000s to 72% in the 2020s, while non-tech companies' share of software M&A has shrunk from 17% to 5%.

(Global software M&A by amount and buyer type)

These large private equity transactions will eventually need to exit. Selling assets to enterprises seeking AI capabilities will be a key exit path.

The report cites data showing that between 2022 and 2024, M&A transactions averaged 42% of total external corporate transactions for private AI companies, while IPOs only accounted for 3%.

Many AI challenger companies are small in scale and continually loss-making, while large incumbents possess proprietary data, trust endorsements, and scale advantages—especially in highly regulated industries, which startups can hardly replicate.

Risks and Historical Lessons

M&A is not a panacea. Risks include failed integrations, cultural clashes, loss of core talent, and high ongoing investment.

Deutsche Bank points out that the number of AI-related bills proposed in the US Congress has surged from about 80 in 2022 to over 200 in 2024, increasing regulatory uncertainty.

(Growth in AI-related bills proposed in US Congress)

History offers a long-term perspective. During the tech boom of the 1990s, the Nasdaq experienced multiple corrections over 10%, but still averaged 32% annual growth.

The regulatory evolution at the time eventually strengthened scale effects and led to market concentration. This time, the giants with capital, data, and scale advantages may also occupy a better position in the long AI race.

The report notes that this time is unique in that as the AI boom kicks off, large tech companies have unusually strong free cash flow. They are among the few entities able to afford massive AI capital expenditures and withstand potential losses. The threshold for this competition has been high from the start.

Ultimately, for investors, the AI M&A cycle is moving from the conceptual phase to substantive implementation, with valuation resets presenting potential strategic buying opportunities, but regulatory risk, lack of transparency in pricing for unlisted targets, and macro uncertainty remain the main constraints. In the medium term, companies able to proactively steer AI M&A strategies will gain an edge as competitive landscapes are reshaped.

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The above content is from Chasing Wind Trading Desk.

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