On April 30, 2026, Bloomberg reported that US tech giants’ AI-related spending is projected to surpass $700 billion this year, setting a new all-time high. This figure represents approximately a 15% increase over 2025’s projected spending, reflecting a global AI race accelerating at an unprecedented pace.

Scale of Spending

According to Bloomberg’s data, this $700 billion in spending covers AI infrastructure construction, GPU chip procurement, data center expansion, AI model research and development, and AI talent recruitment. GPU and AI accelerator chip purchases alone account for the largest share of this expenditure.

The New York Times previously reported that AI spending “is setting a record, with no end in sight.” Major tech companies have all raised their AI capital expenditure plans in recent earnings seasons, showing continued confidence in AI’s future returns.

Key Players

The spending growth is primarily driven by several tech giants:

• Microsoft: Continuously expanding Azure AI infrastructure, with Copilot users surpassing 20 million
• Google: Cloud revenue exceeded $20 billion, though the company admitted growth is constrained by capacity
• Amazon: AWS is increasing AI service investments, with OpenAI models set to launch on Bedrock
• Meta: Open-source AI models continue iterating, with AI infrastructure investment unwavering
• Apple: While maintaining a relatively low profile, AI chip and model investments are also accelerating

Investor Concerns

Despite tech companies continuing to ramp up AI investment, investor concerns about returns are intensifying. The Guardian reported that tech giants’ earnings show “a rosy outlook for the AI boom and US stock market,” but there are also voices questioning whether such massive spending can deliver corresponding commercial returns.

OpenAI’s CFO was previously reported to be at odds with CEO Sam Altman over revenue targets, reflecting that even at the cutting edge of AI, commercialization pressures are mounting.

Industry Impact

The $700 billion in AI spending is not only reshaping the tech industry landscape but also having profound effects on the global supply chain:

• Chip Demand: Driving continued capacity constraints at TSMC, Samsung, and other foundries for advanced process nodes
• Energy Consumption: AI data centers’ electricity demands are raising environmental and energy supply concerns
• Talent Competition: AI engineer salaries continue to rise, with competition for top talent reaching fever pitch
• Geopolitics: AI chip export controls and technology competition have become significant issues in international relations

Outlook

Analysts generally agree that despite uncertain returns, tech giants’ AI investments will not slow in the near term. AI is seen as the core variable that will determine the competitive landscape of the tech industry over the next decade — no company can afford to fall behind in this race.

However, as spending scales continue to expand, investors and the market will increasingly focus on AI commercialization progress. Whether massive investments can be translated into sustainable revenue growth will be the most important metric to watch in the tech industry during the second half of 2026.

Source: Bloomberg | The New York Times | The Guardian