Google’s AI capital spending plans trigger technical warning on stock
Alphabet's ballooning AI capex budget and a planned $80 billion equity raise have analysts drawing uncomfortable parallels to the company's 2021 peak before a 45% crash.
Alphabet is spending money on AI like it just discovered what a credit card is. The Google parent company updated its 2026 capital expenditure guidance to $180-190 billion in April, up from the $175-185 billion it projected just two months earlier in February. For context, the company spent roughly $91 billion across all of 2025.
The technical picture looks familiar, and not in a good way
Technical analysts have flagged overbought RSI (Relative Strength Index) patterns on Alphabet shares. The last time the chart looked this heated was November 2021. What followed was a roughly 45% decline in the stock’s value.
Alphabet announced in June 2026 that it expects to raise around $80 billion through equity sales. The proceeds are earmarked for AI infrastructure and general corporate purposes. The company has also signaled that capex will increase further in 2027, meaning this isn’t a one-year splurge.
Big Tech’s collective AI arms race
Combined capital expenditures for 2026 across Alphabet, Amazon, Microsoft, and Meta are projected near or above $700 billion, with AI infrastructure serving as the primary driver.
Where crypto enters the picture
Google has provided at least $5 billion in credit support and acquired equity warrants in Bitcoin miners that are pivoting their operations toward AI workloads. The company holds an approximately 14% stake in TeraWulf and a 5.4% stake in Cipher, two publicly traded Bitcoin mining firms repositioning their data center infrastructure for AI computation.
Investors watching this space should pay attention to two things. First, whether Alphabet’s AI revenue growth in upcoming quarters justifies the capex trajectory, or whether the spending-to-revenue ratio continues to widen. Second, how the Bitcoin mining companies with Google equity stakes perform operationally during the transition from mining-first to AI-first business models.