The news: Alphabet’s stock is up 160% over 12 months, closing at a $4.7 trillion valuation versus Nvidia's $5.3 trillion. The latest catalyst: a $200 billion, five-year cloud commitment from Anthropic, which alone could represent over 40% of Alphabet's $462 billion cloud backlog, per CNBC.

Google is gaining investor confidence because it controls many layers of the AI stack: its own chips (TPUs), models (Gemini, DeepMind), cloud infrastructure, and distribution across search, YouTube, and Android. 

That diversification gives Google more ways to make money while attracting deals from competitors like Apple and Anthropic, per The Economic Times. 

However, Alphabet expects capital expenditures of up to $190 billion this year, per CNBC. This is more than double 2025 levels—indicating the financial scale needed to compete in AI. 

Why it's worth watching: Alphabet’s AI stack has four tentpoles that can aid its ad growth.

• TPUs lower costs (custom chips): Google’s lower cost per query than Nvidia GPUs in general lets it run AI-powered search, YouTube recommendations, and Performance Max campaigns at scale with less margin erosion.
• Gemini and DeepMind models: Stronger models can improve conversational search ads, automated bidding, and creative generation (image/text for Display and YouTube), potentially resulting in more clicks and higher cost-per-clicks (CPC).
• Cloud and infrastructure: Anthropic’s five-year commitment funds major infrastructure upgrades that can help Google run its own ad workloads for near-zero marginal cost, while competitors are paying retail.
• Distribution (Search, YouTube, Android) strengthens data capability: Apple is tapping Gemini for iPhone AI, showing how rivals need Google’s reach; that distribution feeds first-party data back into models, enabling better-performing ads.

The caveat: Anthropic’s $200 billion, five-year compute commitment, with capacity ramping starting in 2027, effectively ties 40% of Google’s cloud future to a single AI lab that is also a potential long-term model competitor. As Anthropic scales, partly using Google's own compute, it becomes better positioned to reduce dependency or undercut Google Cloud with its own infrastructure partnerships over time. 

Implications for brands: Google's scale and spending signal a multiyear window of stronger AI-powered ad performance—but also increases Google's ability to raise prices. 

• Brands should use that window to negotiate better terms, run tests that isolate what's actually driving results, and avoid locking into long-term commitments. 
• They should also  reduce dependency by building first-party data, testing other channels, and keep a close eye on how AI Overviews and conversational search are changing ad conversions.

This content is part of EMARKETER’s subscription Briefings, where we pair daily updates with data and analysis from forecasts and research reports. Our Briefings prepare you to start your day informed, to provide critical insights in an important meeting, and to understand the context of what’s happening in your industry. Non-clients can click here to get a demo of our full platform and coverage.