Google Cloud has evolved from a financial drain into one of Alphabet’s fastest-growing businesses, posting $15.16 billion in third-quarter revenue—a 34% increase that helped the company reach its first $100 billion quarterly milestone. The cloud division now rivals YouTube as the company’s second-largest revenue source, trailing only Google’s dominant search advertising business.

Under CEO Thomas Kurian’s leadership since 2018, Google Cloud has transformed from controlling just 7% of the global cloud market to an expected 13% by 2025. The division has secured contracts with nine of the ten leading artificial intelligence laboratories, including OpenAI, Anthropic, and Safe Superintelligence.

AI Infrastructure Investments Fuel Expansion

Google Cloud’s remarkable turnaround centers on massive investments in artificial intelligence infrastructure and custom chip technology. The company’s Tensor Processing Units (TPUs) have become a key differentiator against competitors Amazon Web Services and Microsoft Azure, which command 30% and 20% market share respectively.

In a landmark agreement announced in October, Anthropic committed to using up to one million Google TPUs worth tens of billions of dollars, delivering over one gigawatt of AI computing power by 2026. “Anthropic and Google have a long-standing partnership, and this latest expansion will help us continue scaling the compute needed to define the frontier of AI,” said Krishna Rao, Anthropic’s Chief Financial Officer.

The cloud division’s order backlog grew 46% from the previous quarter to a record $155 billion, with CEO Sundar Pichai noting the company closed more deals exceeding $1 billion over the past nine months than during the previous two years combined.

These backlog figures provide visibility into future revenue streams and suggest sustained momentum beyond current quarterly results. The concentration of billion-dollar deals indicates Google Cloud is winning large enterprise accounts rather than just accumulating smaller customers.

Kurian’s Cultural Overhaul Drives Enterprise Focus

Kurian, a former Oracle executive, implemented what employees describe as an “un-Googley” culture focused on enterprise sales and customer needs rather than the company’s traditionally experimental approach. He restructured the sales organization around industry verticals instead of geographic regions and opened offices in lower-cost areas like North Carolina and Poland to reduce expenses.

The strategy has delivered significant results, with Google Cloud now serving over 300,000 enterprise customers. “We are the only hyperscale provider that has both our own chips and models,” Kurian told Reuters, emphasizing the company’s integrated approach to competing with Nvidia, which dominates 80% of the AI chip market.

This cultural transformation represents a significant departure from Google’s engineering-first mentality. By prioritizing enterprise customer relationships and industry-specific solutions over pure technical innovation, Kurian aligned Google Cloud more closely with traditional enterprise software companies than typical Google divisions.

The regional office strategy addresses cost concerns while expanding sales capacity. Hiring enterprise sales representatives in North Carolina costs substantially less than Silicon Valley, improving unit economics while building relationships with customers outside major tech hubs.

Escalating Capital Investments Support Growth Trajectory

Alphabet increased its projected 2025 capital expenditures to a range of $91 billion to $93 billion compared to the original $75 billion forecast, aiming to meet surging demand for AI infrastructure. Despite these massive investments, the cloud division generated $3.59 billion in operating profit, exceeding analyst expectations.

The $18 billion capex increase signals Alphabet’s willingness to sacrifice short-term margins to capture AI infrastructure market share. Cloud computing requires enormous upfront capital for data centers, networking equipment, and custom chips before generating returns. Google is betting that establishing dominant AI infrastructure positions the company for sustained profitability as AI adoption accelerates.

The healthy operating profit despite aggressive expansion suggests Google Cloud has achieved sustainable unit economics. Earlier in its history, the division burned cash pursuing growth. Current profitability while simultaneously increasing investment indicates the business model is working.

Competitive Positioning in AI Infrastructure Race

The TPU strategy directly challenges Nvidia’s GPU dominance while providing cost advantages for Google’s own AI services and cloud customers. By controlling both the hardware layer through TPUs and software layer through models like Gemini, Google creates integration opportunities that pure-play chip vendors or cloud providers without custom silicon cannot match.

This vertical integration mirrors strategies that succeeded in other technology markets. Apple’s control of both iPhone hardware and iOS software created differentiation that pure hardware manufacturers or software companies struggled to replicate. Google is attempting similar vertical integration in AI infrastructure.

The Anthropic deal exemplifies how custom chips attract major AI customers. By offering TPU access at scale, Google provides an alternative to Nvidia GPU clusters that may offer better performance or economics for certain workloads. As AI companies seek computing diversity to avoid single-vendor dependence, Google’s TPU option becomes increasingly attractive.

Market Position and Future Outlook

Google Cloud’s 13% expected market share by 2025 still trails AWS and Azure significantly, but the growth trajectory suggests continued share gains. The 34% revenue growth substantially exceeds overall cloud market expansion, indicating Google is winning business from competitors or expanding the addressable market through AI infrastructure offerings.

The record backlog provides visibility into 2025 performance, though converting backlog to recognized revenue depends on deployment timelines and contract terms. Large AI infrastructure deals may require quarters or years to fully deploy, meaning backlog growth leads revenue growth by significant periods.

Whether Google Cloud sustains this momentum depends on continued AI adoption, successful TPU competition against Nvidia, and enterprise customer retention as contracts renew. The cultural transformation Kurian implemented appears to be working, but maintaining growth while AWS and Microsoft also invest heavily in AI infrastructure will require ongoing innovation and aggressive sales execution.