If you look at 2025’s deal tape, it’s easy to see why people ask. The year began with genuine froth: a more business-friendly U.S. administration, falling-rate expectations, and early trophy prints such as T-Mobile’s double-swoop on Vistar Media (for approximately $600 million) and Blis ($175 million), plus strategic moves like Publicis buying Lotame and The Trade Desk picking up Sincera. 

But by Q3, dealmakers were talking about something closer to a controlled deflation than a mania. Global mergers and acquisition volumes across talent- and tech-enabled services are down about 8% year on year, with buyers citing macro volatility and a widening valuation gap as the main reasons processes stall, according to sources.  For many, this represents the much-touted 2025 rebound in M&A as arriving with “a whimper, not a bang,” as bankers lean into smaller, more surgical transactions instead of 2021-style land grabs.

Yet AI is in almost every pitch deck and virtually every process. The question is whether that AI story is real — or just lipstick on a pig.

One of the clearest signals from SI Global’s latest Global M&A Insights Report is that AI has shifted from “nice to have” to table stakes. Buyers say a well-developed AI strategy is now a baseline requirement, and 70% of respondents name data and analytics as a key interest for next year’s M&A; roughly half explicitly call out AI and machine learning.

Paul Silver, global president of corporate development at MiQ, describes a diet change rather than a loss of appetite. Private equity hasn’t gone off ad tech, he argues — it’s moved from “growth-at-all-costs” to “consolidation-and-integration.” The new playbook is to roll up “orphan assets” with solid tech but broken cap tables into larger platforms, strip out duplicate back-office costs, and use AI to lift margins rather than justify wild revenue multiples.

In practice, that’s showing up as smaller, highly targeted deals. Verve Group’s proposed acquisition of Captify is a neat example, costing the publicly-listed company roughly €25.6 million ($27 million) for an asset expected to contribute about €41 million ($47.7 million) of 2025 revenue and €5 million ($5.8 million) of EBITDA after synergies. It’s a classic data-plus-demand-side tuck-in: one of the largest onsite search datasets outside the walled gardens, bolted onto an existing DSP footprint rather than sold as a standalone AI “story.”

The same pattern runs through other 2025 transactions. WPP’s purchase of data-clean-room provider InfoSum, The Trade Desk’s acquisition of Sincera for a sub-$50 million sum, and DoubleVerify’s deal for Rockerbox all fall into the “defensibility buys” bucket — assets with proprietary data or infrastructure that supports AI-driven planning and measurement, rather than pure model IP. 

Meanwhile, AI is also driving capability grabs at the creative and SMB end of the market: Magnite’s acquisition of streamr.ai to simplify CTV creative and campaign setup for small advertisers, and Rembrand’s merger with Spaceback to fuse virtual product placement with social-to-programmatic creative automation. Both speak to a barbell that Silver and others see emerging: CTV scale on one end, AI-enabled margin expansion on the other.

Paul Knegten, an industry consultant with extensive experience working with ad tech companies, described a “huge force from AI” that’s forcing many investors to reevaluate any earlier theses — and could prompt M&A activity.

“On one hand, the pressure’s gotten even stronger to consolidate that’s just, there’s this massive, like existential pressure,” he said, describing this as “existential.” Knegten added, “You have pure-play AI companies that are innovating directly in that space. Then you have, like, the rest of the ad tech infrastructure that needs to kind of get consolidated quickly into some very durable companies.”

PE’s patience meets the AI overhang

The more uncomfortable dotcom parallel sits inside PE portfolios. SI Global’s research shows that 21% of PE-backed B2B assets are now classed as “overdue,” double last year’s level, while refinancings are down 57%. In plain English: a big chunk of the 2020–21 vintage is stuck, and fund-life clocks are ticking.

Joe Hine at SI Global frames it as the hangover from the 2021 peak, when high-growth digital assets traded 30 to 50% above historic norms. Many of those companies aren’t basket cases, he notes, but they need longer growth periods than their original five-year plans allow — and in the meantime, CEO churn and cap-table tension are rising as PE firms try to re-align incentives. “This is a risk endemic in investments made at a peak in the market,” he adds. “Exits become harder with the twin-pressure of a softer trading market and the hearing coming out of valuations.”

A separate investor, speaking on background, connects that pressure directly to the AI hype cycle. After the Covid-19 pandemic, many LPs tolerated “continuation funds” that rolled over overvalued holdings in the hope that paper IRRs would eventually become cash. Now, with AI-themed companies also being overfunded, LPs are demanding real exits rather than more markups. Continuation vehicles are harder to sell; co-investment and deal-by-deal capital are in; and anything that can’t show durable economics in an AI-disrupted world gets heavily discounted.

Kevin Flood of First Party Capital sums up the mood: “There’s still appetite to do deals, but investors can’t live off paper returns anymore — they need cash outcomes. The AI hype cycle has flooded the market with companies that look exciting but don’t have defensible models, and LPs are forcing funds to prove what actually works.”

Knegten added, “Everyone has slapped ‘AI’ on their pitch deck, but a lot of what’s out there are just wrappers on top of the big foundation models, and strategics won’t pay a premium for that — they’ll rent the algorithm and buy the dataset or the workflow. The smart money is going after the defensibility, not the buzzword.”

That’s visible in live situations, with Integral Ad Science’s fourth anniversary as a publicly listed company shortly followed by a $1.9 billion take-private by Novacap, with many interpreting this as a capitulation deal: a decent verification business whose public-market valuation and growth profile no longer squared with its 2018 PE entry price.

Meanwhile, TripleLift cut costs sharply under Vista Equity Partners, taking form most recently with “significant layoffs” in July, after a 2021 deal reportedly valued the supply-side platform at north of $1.4 billion. These are precisely the situations where AI becomes both excuse and threat: boards are told transformation is coming, but investors want to know whether that transformation is actually improving margins.

First Party Capital’s Flood underlines the point, describing how PE funds’ limited partners are pushing general partners for tangible liquidity and wary of backing yet another AI-themed fund that can’t show defensible IP or proprietary data. In his view, that will force a more extreme dispersion of outcomes. Mature, mostly “media” businesses with little tech moat will clear at low or no premiums; by contrast, small companies with genuinely proprietary data or infrastructure that can plug into AI workflows could still command the kind of 20X EBITDA multiples people associate with the last cycle — just far more selectively.

The net effect is that take-privates and roll-ups become both a release valve and a sorting mechanism. As several sources told Digiday earlier in the year, PE firms are circling multiple listed ad tech names, but they’re doing so with an eye on how AI will impact those companies’ models over the next five to 10 years, not just today’s revenue mix.

When the AI bubble bursts, who gets bought?

Everyone interviewed for this piece agrees on one thing: there is an AI bubble. The disagreement is over what pops when it bursts.

Silver is blunt about a lot of AI-driven measurement, identity, and optimization startups: many are essentially “wrappers” on commoditized large-language-model infrastructure. From an M&A perspective, that pushes outcomes toward acqui-hires and low-priced “pseudo-acquisitions,” where the buyer wants the team and maybe a dataset, not the algorithm itself. Strategics will rent the models from OpenAI, Anthropic, or Google and pay up only for proprietary data or tight workflow integration.

One investor source describes a bifurcated deal pipeline over the next two years. At one end, “graceful exits” for under-scale point solutions — tiny roll-ups, stock-heavy deals, and classic bargain-basement consolidations that bulk up revenue but don’t move the tech needle. At the other end, a small number of “premium assets” with defensible data or infrastructure that helps big buyers lean into AI: think clean-room operators, CTV data platforms, or workflow tools that sit directly in agency or marketer stacks.

An experienced M&A adviser in media and tech, who requested anonymity in exchange for candor said they expect AI-related “market shocks” in 2026 as this plays through. In their read, 2025 is a mixed year: notable strategic moves such as IAS’ sale and the merger of Broadsign and Place Exchange, but a lot of CEOs staying quiet while they figure out whether to be buyers, sellers, or both. AI, he says, is already improving efficiency in areas like dynamic creative and analytics, but investors are wary of underwriting long-dated AI bets at today’s valuations.

“AI is creating real opportunity in ad tech, but it’s also injecting a level of uncertainty… Investors know it can improve efficiency, but they’re wary of paying up for technologies that may not age well,” said investment banker Robert J. Stenz.

Overlay that with the macro data, and you get something that looks less like a runaway bubble and more like a slow, messy repricing. SI Global’s survey shows deal volumes down, but 70% of buyers still expect activity to increase over the next 12 months, and private equity or PE-backed platforms are involved in the majority of lower-mid-market transactions SI has advised on. This is not 2001, when IPO windows slammed shut, and strategic buyers disappeared; it’s a world where capital is still available, just far choosier.

The dotcom parallel does still hold in one respect, though. Back then, a lot of “internet companies” turned out to be bad businesses; a handful of infrastructure and platform names captured most of the long-term value. The current AI hype cycle in ad tech looks set to produce a similar shake out. Measurement and optimization startups whose “moat” is a ChatGPT prompt will likely end up as low-multiple tuck-ins. Companies with deep, hard-to-replicate data, infrastructure that helps brands and publishers adapt to AI, or durable CTV positions will probably survive the correction — and may even find their pricing power strengthened as weaker rivals are consolidated.

For now, 2025’s M&A market is acting more like a sorting hat than a bubble machine. AI is the buzzword on everyone’s lips, but the deals that clear are increasingly those where the technology is already rewiring P&Ls — not just the pitch deck.