Global tech spending to reach $5.6T in 2026 as AI infrastructure race accelerates
Global technology spending is forecast to grow 7.8% in 2026 to $5.6 trillion as countries and corporations push AI infrastructure buildouts. Forrester attributes about two-thirds of the 2026 spending surge to foundational technology for AI—data centers, semiconductors and compute hardware. Hyperscalers (major cloud providers) were primary drivers in 2024–25, with the largest U.S. hyperscalers spending nearly $300 billion on AI in 2025 and Q3 hyperscaler capex hitting $142 billion. Total U.S. AI spending in 2025 approached $450 billion; China spent over $100 billion (≈50% year-on-year growth). Other notable 2025 AI budgets: UK ~$28B, Canada ~$15B, Israel ~$15B, Germany ~$11B, India ~$11B. S&P Global projects an even stronger 9% growth in 2026, forecasting big gains for hyperscalers and semiconductor makers—cloud revenue up ~20% and semiconductor industry up ~24%. Analysts note the shift from experimentation to large-scale deployment, with winners being those with access to capital, energy and compute. While concerns about an AI market bubble exist, much capital is being directed to long-lived physical infrastructure, signalling structural investment that could support sustained AI-driven economic activity.
Neutral
The article describes large, structural capital deployment into AI-related physical infrastructure—data centers, semiconductors and cloud capacity—which generally supports long-term growth rather than immediate speculative asset booms. For crypto markets this is neutral overall: infrastructure investment can indirectly benefit blockchain and crypto through improved compute, cloud services and enterprise adoption, but the report does not link direct capital flows into cryptocurrencies or crypto-specific infrastructure. Short-term effects: neutral-to-slightly bullish for crypto risk appetite when macro confidence rises (more capital available), but no clear catalyst for immediate price spikes. Long-term effects: potentially bullish for projects that leverage AI/compute-heavy use cases, on-chain data marketplaces, and tokenized infrastructure financing, because sustained capex in compute and cloud reduces barriers for sophisticated dApps and AI-blockchain integrations. Historical parallels: prior waves of cloud and GPU capex expanded markets for GPU-mined tokens and NFT/metaverse projects, but those moves required explicit integration or demand; without direct crypto investment, large hardware spend mainly benefits semiconductor and cloud equities rather than crypto prices. Overall classification is neutral because primary flows target traditional tech infrastructure, not crypto-specific capital.