Billions Flood Into AI Infrastructure as OpenAI, Nvidia and Meta Strike Mega Deals

AI infrastructure is getting funded at unheard-of levels. Here's what finance leaders should track

Across chips, cloud, and data centers, multi-billion-dollar deals are locking in compute for the next wave of AI products. The throughline: secure supply, secure talent, and prepay for capacity before your competitors do. For finance teams, this isn't noise - it's visibility into capex cycles, pricing power, and who gets margin leverage next year.

OpenAI-centric deals

• Amazon is considering an investment of around $10 billion in OpenAI. Talks are fluid, but the intent is clear: align with a leading demand engine for compute.
• Disney will invest $1 billion and grant OpenAI a three-year license to use characters from Star Wars, Pixar, and Marvel in Sora's video generator and ChatGPT Images. Early next year, Sora will start generating videos with licensed characters; talent likeness and voices are excluded. Details on Sora
• Broadcom will co-develop OpenAI's first in-house AI processors, adding a second route to compute supply.
• AMD signed a multi-year chip supply deal with OpenAI and gave it the option to acquire up to roughly 10% of AMD.
• Nvidia plans to invest up to $100 billion in OpenAI and will supply data-center chips, taking a financial stake alongside a strategic customer relationship.
• Oracle reportedly signed one of the biggest cloud deals ever: OpenAI to buy about $300 billion in compute over roughly five years.
• CoreWeave inked a five-year, $11.9 billion contract with OpenAI in March.
• Stargate, a SoftBank-OpenAI-Oracle joint venture, was announced with up to $500 billion earmarked to build AI data centers.

Meta's compute grab

• Meta will acquire Chinese startup Manus to push agentic AI across Facebook, Instagram, and WhatsApp. The deal reportedly values Manus at $2-$3 billion.
• CoreWeave signed a $14 billion agreement to supply compute to Meta.
• Oracle is in talks with Meta on a multi-year cloud deal worth about $20 billion.
• Google agreed to a six-year cloud deal with Meta worth more than $10 billion.
• Meta acquired a 49% stake in Scale AI for about $14.3 billion, bringing CEO Alexandr Wang into a central role in Meta's AI strategy.

Nvidia's expanding footprint

• Nvidia will license chip tech from Groq and hire its CEO Jonathan Ross and other engineers. CNBC reported Nvidia agreed to acquire Groq assets for $20 billion.
• Microsoft will invest up to $5 billion and Nvidia up to $10 billion in Anthropic. Anthropic will commit $30 billion to run workloads on Microsoft's cloud and up to 1 GW of compute powered by Nvidia's Grace Blackwell and Vera Rubin hardware, while collaborating on chip and model performance. About Grace Blackwell
• An investor group including BlackRock, Microsoft, and Nvidia is buying Aligned Data Centers for $40 billion, adding nearly 80 facilities to their footprint.
• Nvidia will invest $5 billion in Intel for roughly a 4% stake after new shares are issued.
• CoreWeave placed an initial $6.3 billion order with Nvidia and guaranteed Nvidia will purchase any unsold cloud capacity.

Google's capacity build

• Google will invest $40 billion in three new Texas data centers through 2027 (Armstrong County and two in Haskell County), while continuing to build out its Midlothian campus and Dallas cloud region within its 42-region global network.
• Google hired key staff from code-generation startup Windsurf and will pay $2.4 billion in license fees for non-exclusive use of its technology.

Why this matters for finance

• Upfront capex vs. long-dated revenue: Multi-year capacity bookings (Oracle, CoreWeave, hyperscalers) create backlog visibility for providers and cost clarity for buyers. Expect deferred revenue growth and improved utilization metrics.
• Supply chains and pricing: New chip paths (Broadcom with OpenAI, AMD options, Groq tech at Nvidia) broaden supply and may temper unit pricing - but leading-edge GPUs still command a premium.
• Power and real estate: 1 GW-scale compute commitments and $40B data center buys signal a race for power, land, and cooling. Watch grid interconnect timelines and power contracts; they can bottleneck deployments.
• Concentration risk: A small set of buyers (OpenAI, Meta, Anthropic) is pre-booking massive capacity with a small set of suppliers (Nvidia, CoreWeave, Oracle, Microsoft, Google). This amplifies counterparty and dependency risks.
• Content licensing economics: Deals like Disney-OpenAI introduce new cost lines (IP royalties) into model training and generation. Gross margin on AI video may look different from text models.
• M&A and talent: Asset buys (Aligned), minority stakes (AMD), and acquihires (Groq talent) point to tightening labor and IP markets. Expect retention packages and amortization to show up in OpEx and non-cash adjustments.

Practical checks for 2026 plans and models

• Map exposure: Chips (Nvidia, AMD, Intel), cloud (Microsoft, Google, Oracle), infra (CoreWeave, Aligned), content owners (Disney), model providers (OpenAI, Anthropic), and platforms (Meta).
• Stress test GPU assumptions: Price per H100/GB200-class GPU hour, lead times, and utilization. Small changes swing unit economics for AI features and margins for AI-exposed vendors.
• Track power constraints: Model delays tied to interconnect queues or substation build-outs; adjust revenue timing where data center readiness is critical path.
• Watch accounting: Capitalized R&D for chip co-development, prepayments for capacity, and revenue recognition on multi-year commitments.
• Scenario plan: If compute gets cheaper 20-30% with new silicon, who expands TAM vs. who loses pricing? If supply stays tight, who has priority allocation?

If you're evaluating practical AI use across finance workflows, here's a curated list of tools worth tracking: AI tools for finance.