Who Is Buying Software in 2026: A Public-Source Review of 27 Announced Deals

Every deal in this review was announced publicly and documented by Acquiry Deal Intelligence from company press releases and filings. We took every entry classed as software and AI, fintech or semiconductors with a publication date between 1 July and 15 October 2026. That gave 28 deals. We set aside one, a reported discussion between Goldman Sachs and Palmer Square, because it was still at the talks stage. That leaves 27.

The sample has clear limits. It is weighted towards larger, public announcements, because those are the deals with primary sources. It over-represents listed acquirers, which have to disclose deals, and under-represents private equity add-ons and small founder exits, which often close quietly. It shows who announced deals in this window, not who is actively looking, how many buyers exist or what they will pay.

PitchBook's Q2 2026 US PE Breakdown (opens in a new tab), published on 7 July 2026, recorded US private equity deal value of $177.3 billion for the quarter, down 37.5% on the first quarter and 23.9% on a year earlier. Software was hit hardest. Its deal value fell 65.7% year on year, which PitchBook tied to investors working out the extent and speed of AI disruption for established software firms.

Bain's Global Private Equity Report 2026 (opens in a new tab) describes a narrow, K-shaped recovery: deal and exit values rose in 2025, but low prices, cheap debt and easy multiple expansion are gone. Its shorthand, "12 is the new 5", means today's deals need much faster EBITDA growth to deliver their returns. Bain's M&A Report 2026 (opens in a new tab) says 2025 was the second-highest year on record for deal value, driven by companies reinventing themselves around technology disruption and AI.

Put together, those reports describe a split market. Sponsors became far more selective about software. Corporates, under pressure to add AI capability, kept buying. The deals in this review fit that pattern closely.

Only one deal in the set was led by a traditional private equity firm: Francisco Partners' agreement for Weave. Bending Spoons, which bought Airtable, is an operating company that acquires and runs software businesses rather than a fund. Every other acquirer was a corporate buying for its own platform. That split matches the PitchBook data: in this window, software buying was led by strategics.

Repeat buyers stand out. Salesforce appears twice (Fin and Listen Labs), as does Stripe (OpenRouter and Parafin). Both are adding capability around an existing platform rather than entering new markets.

The strongest pattern is incumbent software companies buying AI-native products that plug into what they already sell. Read across the set, the targets group into four themes.

• AI for existing enterprise workflowsWorkday and C1.ai, Salesforce and Listen Labs, SAP and TechWolf, Automation Anywhere and Boost.ai, and Pearson and Workera all add AI products to a platform with an installed customer base.
• AI engineering and data infrastructureDynatrace and Arize, Harness and Augment Code, Databricks and Row Zero, and Supabase and Turso extend developer and data platforms that already sit at the centre of their customers' software.
• SecurityServiceNow and Armis, IonQ and Elisity, and Visa and BioCatch each bought security capability, ranging from asset visibility to identity and fraud.
• Payments and embedded financeStripe and Parafin, Grab and Atome Financial, NEOPAY and noon payments, Bloomberg and Canoe Intelligence, and Munich Re and At-Bay show payment and financial platforms buying products their customers already need.

Two deals sit at the very top of the market and point the same way: Schneider Electric's $22.6 billion agreement for PTC, an industrial software company, and AMD's $8.2 billion agreement for World Labs, a spatial AI company. Both are large hardware and industrial companies buying software and AI capability to sit alongside what they already make.

The deals announced without a price are mostly product and team acquisitions by much larger companies, where the price is small relative to the buyer and no disclosure is required. That matters for anyone benchmarking: the public record shows the large, priced deals clearly and the smaller strategic buys only in outline.

The sample can't tell us much about recurring revenue thresholds, profitability requirements or deal structures such as earnouts, because few of these announcements published them. We have left those out rather than infer them.

• Fit with a platform is the strongest caseMost targets here added a product to a buyer that already owned the customer relationship. Owners whose product clearly extends a larger platform have the clearest buyer universe.
• AI products are in demand, but so is proofThe buyers here are acquiring AI capability that works inside real enterprise workflows. Usage, customers and integration evidence matter more than positioning.
• Sponsors are more selectiveWith software PE deal value down sharply in Q2, owners planning a sponsor-led sale should expect closer diligence on growth and AI exposure.
• Many good deals never reach an auctionStrategic product acquisitions are often negotiated directly. Owners benefit from understanding which buyers fit before they approach the market.

Owners thinking about timing can read our guide on how to sell a SaaS business or use the free SaaS valuation calculator.

If large platforms are the most active buyers of AI-native software, mid-sized acquirers and sponsors are competing with balance sheets they can't match in an open process. The practical response is to find targets earlier, while they are still founder-led and before an adviser runs an auction.

That means mapping the companies that fit a thesis, opening conversations with owners directly and qualifying them early. Our comparison of deal-sourcing tools for software acquirers covers the platforms that help build a target list, and Acquiry's off-market origination work covers the steps after it.

Our Opportunity Map shows anonymised counts of the buyers and owners in our own network by country and sector. It is a picture of our desk, not a market survey, and we haven't used it as evidence in this review.