Major technology companies including Apple, Microsoft, Meta, and Tesla reaffirmed their massive AI infrastructure investments during their earnings calls this week, dismissing concerns that Chinese startup DeepSeek’s low-cost AI model would derail their spending plans. The announcements came after DeepSeek disrupted markets in January by claiming it trained its R1 model for less than $6 million, causing initial stock declines among AI leaders.
Meta maintained its ambitious $60-65 billion capital expenditure plan for AI infrastructure in 2025, with CEO Mark Zuckerberg emphasizing that “investing aggressively” in AI initiatives will determine the company’s financial trajectory for years to come. Zuckerberg also stated Meta is working to establish an “American standard” for open-source AI models globally, suggesting recent developments have “only strengthened our conviction.”
Microsoft revealed even more aggressive spending, planning to invest $80 billion in AI data centers during its current fiscal year. CEO Satya Nadella disclosed that the company’s AI business has already surpassed a $13 billion annual revenue run rate, representing 175% year-over-year growth. Notably, Microsoft indicated that AI demand is so intense that the company is struggling to provide sufficient data center capacity to meet customer needs.
Apple CEO Tim Cook took a more measured tone, noting the company’s “prudent, deliberative approach” to capital expenditures, though he didn’t specify exact AI spending figures. Apple’s cautious AI strategy, which resulted in launching Apple Intelligence later than competitors, ironically insulated the company from the stock market volatility triggered by DeepSeek’s announcement.
Tesla’s Elon Musk focused on real-world AI applications during the company’s Q4 earnings call, discussing “rapid progress” in technology development, particularly for the humanoid robot Optimus. While not directly addressing DeepSeek, Musk acknowledged that “the cost of training is dropping dramatically with time.”
Dan Ives, managing director at Wedbush Securities, characterized the situation as an “AI arms race,” dismissing DeepSeek as “the Temu of AI” and asserting that the “AI Revolution is just starting.” The consensus among tech executives appears to be that cheaper AI models will actually expand market access and increase overall demand, thereby justifying continued heavy investment in chips and data center infrastructure rather than reducing it.
Key Quotes
Huge week for Big Tech earnings as Zuckerberg, Nadella, Cook, and Musk doubled down on their AI visions and what this means for each of these tech stalwarts looking ahead. This is an AI arms race and the Temu of AI DeepSeek not changing that…AI Revolution just starting.
Dan Ives, managing director at Wedbush Securities, characterized the earnings week as a decisive moment where tech leaders reaffirmed their AI commitments. His dismissive comparison of DeepSeek to discount retailer Temu suggests he views the Chinese model as a lower-quality alternative that won’t fundamentally alter the competitive landscape.
Already, our AI business has surpassed an annual revenue run rate of $13 billion, up 175% year-over-year.
Microsoft CEO Satya Nadella revealed this figure during the company’s FY 2025 Q2 earnings call, demonstrating that massive AI infrastructure investments are already generating substantial revenue returns. This 175% growth rate provides concrete justification for Microsoft’s planned $80 billion spending on AI data centers.
If anything, some of the recent news has only strengthened our conviction that this is the right thing for us to be focused on.
Meta CEO Mark Zuckerberg made this statement in direct reference to DeepSeek’s emergence, suggesting that rather than causing concern, the Chinese company’s low-cost model has reinforced Meta’s belief in pursuing open-source AI development and establishing American leadership in the space.
From a CapEx point of view, we’ve always taken a very prudent, deliberative approach to our expenditure.
Apple CEO Tim Cook defended the company’s more cautious AI investment strategy, which has been criticized for launching Apple Intelligence later than competitors. This measured approach inadvertently protected Apple’s stock from the volatility other tech giants experienced following DeepSeek’s announcement.
Our Take
The tech industry’s unified response to DeepSeek reveals a sophisticated strategic calculation: these companies are reframing a potential threat as a market expansion opportunity. Rather than acknowledging that cheaper models might reduce infrastructure needs, executives are arguing that accessibility will drive exponential demand growth. This narrative serves multiple purposes—it reassures investors, justifies continued spending, and positions American companies as premium providers in an expanding market. However, the real test will come in 12-18 months when we see whether DeepSeek-style efficiency gains become industry standard or remain an outlier. Microsoft’s admission of capacity constraints is particularly telling, suggesting current demand may indeed justify the spending spree. The geopolitical subtext—Zuckerberg’s emphasis on “American standards” for open-source AI—also signals that this arms race has national security dimensions beyond pure business competition.
Why This Matters
This coordinated response from Big Tech represents a critical inflection point in the AI industry’s development trajectory. Despite DeepSeek demonstrating that effective AI models can potentially be built at a fraction of current costs, the world’s largest technology companies are signaling their belief that infrastructure investment remains essential for competitive advantage. This has significant implications for the semiconductor industry, data center operators, and energy providers who supply this ecosystem.
The unwavering commitment to AI spending—totaling well over $140 billion from just Microsoft and Meta alone—suggests these companies view AI as an existential competitive battleground rather than an optional technology upgrade. For businesses and workers, this means AI integration will accelerate across industries regardless of cost efficiencies, potentially disrupting traditional business models faster than anticipated. The framing of cheaper models as demand drivers rather than spending reducers also reveals how tech giants plan to maintain profit margins: by expanding the total addressable market rather than competing solely on price. This “AI arms race” mentality could reshape global technology leadership for decades.
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