Well-funded artificial intelligence companies are buying smaller rivals at record speed, using mergers and acquisitions to plug product gaps and capture specialized teams faster than they can build capabilities internally. Through September 29, venture-backed AI firms closed 195 acquisitions of other AI startups — 14% more than the full-year total for 2025 — even though the number of acquiring companies grew by just 2%, according to Crunchbase data analyzed in a report published this week. The surge marks a shift in competitive strategy, with heavily capitalized startups turning to M&A to broaden their offerings and reach customers more quickly than organic growth permits.
OpenAI leads all buyers with 20 AI-related acquisitions overall, including 10 completed this year alone. Anthropic and legal AI startup Legora have each announced five deals in 2026, while Harvey has closed four. Customer-service provider Sierra and coding company Cursor have each finished three acquisitions, and Cohere has done two. Over the past three years, 67 repeat buyers accounted for 42% of all tracked transactions. Just 12 of the 195 deals revealed pricing details, making overall spending hard to calculate. The biggest disclosed transactions include Nscale's $1.65 billion purchase of Anyscale, Cyera's $1 billion acquisition of identity security startup Oasis Security, Anthropic's $400 million deal for pharmaceutical AI developer Coefficient Bio, OpenAI's $300 million buy of computational photography startup Glass Imaging, and Sword Health's purchase of Kaia Health valued as high as $285 million.
"It's all about speed in the AI world," said Rama Sekhar, partner at Menlo Ventures, which backs Anthropic and Legora. "It's faster to acquire a team or product than build it yourself." Katie Burke, chief operating officer at Harvey, characterized the firm's approach as "selective but aggressive," noting that the company maintains "an incredibly high bar for talent" and acts quickly when it identifies an additive company. Vertical AI companies, especially those focused on legal technology, are powering much of the consolidation wave. Harvey's four acquisitions this year address distinct capability needs: Hexus for product demos and guides, Lume for linking customer data with AI systems, Benchmark for asset management insights, and Guardrails AI for open-source AI agent testing tools. Stockholm-based Legora has pursued an even wider legal-tech consolidation with five acquisitions spanning Canadian agents for Microsoft Word and Outlook, AI-native legal research, Australian regulatory intelligence monitoring, commercial real estate document analysis, and London-based litigation fact extraction tools.
The acceleration stems from a combination of investor expectations and financial mechanics, according to the report. Growth investors demand 10x expansion, and startups unable to hit that benchmark face a funding gap that pushes them toward acquisition targets. At the same time, sky-high valuations have handed AI startups what the report describes as "cheap currency" — inflated stock they can deploy to close deals with minimal dilution to existing shareholders. OpenAI's buying spree has stretched across healthcare data, scientific writing, developer infrastructure, security tools, and talent acquisitions, including companies focused on executive coaching reports, medical record unification, LaTeX editing, cloud development environments, and presentation generation. TakeOff founder Aakash Thumaty wrote in a July blog post that his 14-month-old startup was posting a "near 8-figure run rate" with just three employees, but the Sierra acquisition offered a chance to "accelerate our shared vision and simultaneously build it at a grander scale." The pattern suggests M&A will remain a core growth mechanism for AI leaders as long as the twin pressures of hypergrowth demands and elevated valuations persist. The combination creates both the urgency and the financial tools for continued dealmaking across the sector. The aggressive pace of consolidation may reshape competitive dynamics faster than product development cycles alone would allow, particularly in specialized verticals where acquiring domain expertise delivers immediate market advantage. For startups caught between modest growth and runaway scale, the choice increasingly boils down to finding a strategic home or risking irrelevance in a market where speed trumps perfection.