Alphabet Conference: Google Cloud Sees Surging AI Demand, Bigger Enterprise Deals

Google Cloud is experiencing accelerating enterprise demand: New-customer additions have more than doubled year over year, while contracts exceeding $100 million have more than doubled both quarter over quarter and year over year. Customers typically spend more than 50% above their initial commitments.

Alphabet is positioning an integrated AI stack as a competitive advantage: The offering spans TPUs, NVIDIA GPUs, processors, Gemini models, data tools, cybersecurity and Workspace, with Google citing improved price performance and sub-two-year payback periods for AI servers.

Gemini Enterprise and cybersecurity are driving expansion: Gemini Enterprise is used by more than 90% of Fortune 100 companies, while Google says over 90% use its cyber-defense tools. AI customers adopt 1.8 times as many Google Cloud products and have an estimated 1.5 times higher five-year lifetime value.

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Google Cloud CEO Thomas Kurian said Alphabet (NASDAQ:GOOG) is seeing accelerating enterprise demand for its cloud infrastructure, artificial-intelligence products and cybersecurity offerings, citing growth in customer additions, large contracts and cross-selling across its product portfolio.

Speaking at a company conference, Kurian said Google Cloud has more than 17 product lines with annual revenue above $1 billion. He said new-customer acquisition has grown more than twofold year over year, while deals exceeding $100 million have increased more than twofold both quarter over quarter and year over year.

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Kurian said customers that make commitments to Google Cloud typically spend more than 50% above their initial commitments, which he said reflects adoption and expansion within the existing customer base.

Kurian emphasized Google Cloud's strategy of offering first-party products across the technology stack, including its own tensor processing units, or TPUs; NVIDIA GPUs; Arm-based processors; Gemini models; data-management tools; security products; and enterprise applications such as Workspace.

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"Some people buy us for silicon, some people use our models, some people use our data platforms," Kurian said, describing a business model designed to capture revenue through multiple channels as AI monetization evolves.