SAN FRANCISCO – The past few days delivered a clear message to the tech sector: The artificial intelligence (AI) gold rush is entering a new phase, and consolidation is the name of the game.
Three major acquisitions announced or reported in rapid succession — Intel Corp.’s pursuit of SambaNova, ServiceNow Inc.’s dual strike with Moveworks and Armis, and NVIDIA Corp.’s acquisition of SchedMD — underscore a strategic shift as tech giants move from building AI capabilities organically to aggressively buying their way into market leadership.
On Wednesday, Coursera Inc. said it acquired rival online education platform Udemy in a $2.5 billion all-stock deal as its industry consolidates amid an AI skills boom.
The flurry of dealmaking represents more than $13 billion in combined transaction value, with Intel reportedly paying $1.6 billion for AI chip startup SambaNova, ServiceNow shelling out $2.85 billion for Moveworks and potentially up to $7 billion for cybersecurity firm Armis, and NVIDIA snapping up Slurm developer SchedMD for an undisclosed sum. The common thread? Each acquisition addresses critical gaps in the AI infrastructure stack.
Intel’s move is perhaps the most telling. Once the undisputed king of computing chips, the company has found itself scrambling to catch up in the AI processor market where NVIDIA has captured an estimated 80% share. By acquiring SambaNova, a company specializing in inference processors with its innovative Reconfigurable Dataflow Unit architecture, Intel gains not just technology but precious time.
ServiceNow’s strategy reveals another emerging trend: The convergence of AI automation with enterprise security and operations. The Moveworks deal, which closed Monday, brings aboard 500 AI experts and technology that serves nearly 5 million users. Following immediately with talks to acquire Armis for what would be ServiceNow’s largest-ever acquisition shows the company recognizing that AI-powered workflow automation must include comprehensive asset visibility and cybersecurity.
NVIDIA’s acquisition of SchedMD might seem modest compared to the multibillion-dollar deals, but it’s strategically brilliant. Slurm powers workload management for more than half of the world’s top supercomputers, making it the de facto standard for high-performance computing. By acquiring the team behind this critical infrastructure while committing to keep it open-source, NVIDIA strengthens its ecosystem moat while appearing magnanimous to the research community.
What makes this wave particularly significant is the timing. The deals come as AI development costs continue to skyrocket and competition intensifies. Training and deploying large language models (LLMs) requires massive computational resources, specialized talent, and battle-tested infrastructure — all of which are faster to acquire than to build. The traditional “not invented here” mentality that once dominated Silicon Valley has given way to pragmatic recognition that speed to market trumps internal development timelines.
The regulatory environment, while still cautious, appears more permissive than many expected. ServiceNow’s Moveworks acquisition faced Justice Department scrutiny but ultimately received clearance, signaling that regulators may distinguish between traditional monopolistic consolidation and strategic investments in emerging technologies where market definitions remain fluid.
AI Boom Fuels Tech M&A Revival
U.S. tech M&A reached $543 billion in 2025 — exceeding the combined totals of the previous two years. Industry analysts project deal volumes will continue climbing through 2026, driven primarily by AI.
AI pushed first-quarter deal values to $64 billion and sparked consolidation across infrastructure providers, semiconductor manufacturers, and data center operators. High-profile transactions include Google’s pending $32 billion acquisition of cybersecurity firm Wiz and increased activity in developer tools and AI infrastructure.
The spending surge extends beyond acquisitions. Big Tech’s collective capital expenditures have exploded to approximately $405 billion in 2025, up 62% year-over-year, with Meta Platforms Inc., Microsoft Corp., Google, and Amazon.com Inc. leading the charge. Meta alone plans to spend up to $72 billion this year, a $30 billion increase.
Looking ahead, forecasts suggest global AI infrastructure spending could reach $571 billion by 2026 and exceed $1 trillion annually by decade’s end. Companies are racing to secure GPU capacity, custom chips, and data center infrastructure as AI demand continues outpacing available supply, fundamentally reshaping the technology landscape.
Looking ahead, experts expect M&A momentum to accelerate rather than slow. Dozens of well-funded AI startups raised capital at peak valuations in 2021-2022 and now face pressure to deliver returns or find exit opportunities. Meanwhile, established tech companies with deep pockets and urgent strategic needs are hunting for capabilities that can be integrated immediately. The math is simple: Building takes years, buying takes months.
The AI revolution won’t be won by lone innovators working in isolation. It will be won by those who can assemble the most comprehensive technology stack fastest — whether through internal development, acquisition, or partnership, industry observers say. This week’s deals are just the opening salvo in what promises to be one of the most active M&A periods in tech history.
Buckle up.
