{
  "id": 10206365,
  "title": "Hyperscaler cloud revenues projected to top $1 trillion by 2030 amid AI, digital asset convergence: Report",
  "url": "https://urgent.news/2026/09/27/hyperscaler-cloud-revenues-projected-to-top-1-trillion-by-2030-amid",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-27T11:37:28.000Z",
  "source": {
    "name": "Economic Times Tech",
    "slug": "economic-times-tech",
    "url": "https://economictimes.indiatimes.com/tech/artificial-intelligence/hyperscaler-cloud-revenues-projected-to-top-usd-1-trillion-by-2030-amid-ai-digital-asset-convergence-report/articleshow/134519352.cms"
  },
  "original_language": "en",
  "account": "By 2030, computing resources for artificial intelligence are expected to generate revenue surpassing $1 trillion, according to a BlackRock report. The convergence of AI and digital assets is propelling compute capacity to become a crucial economic asset. Computing power is transforming into a vital economic resource, with standardized claims on processing capacity offering a practical framework for financing and settlement. Analysts estimate that hyperscaler cloud revenues could reach $1 trillion annually by 2030, as autonomous software agents gain persistence and capability. AI and digital assets share a structural connection, with AI providing machine-native intelligence and digital assets supplying machine-native money. This alignment becomes especially significant with the emergence of agentic AI, systems capable of executing multi-step tasks across external networks with minimal human oversight. Blockchain technology serves as the programmable infrastructure connecting intelligence with economic activity. Both AI and digital assets utilize tokenization models, with large language models breaking down language into tokens for numerical assessment, while distributed ledgers register economic entitlements as machine-verifiable tokens. Agentic commerce necessitates programmable payment channels, as traditional financial mechanisms struggle with continuous, low-value microtransactions. Autonomous software systems utilize stablecoins and specialized transfer protocols like x402 and ACP for high-frequency, low-value, always-on transactions. Although promising, the current operating environment remains in its early stages, with liquidity in compute claims and agent-driven transaction volume being modest. However, as machine autonomy deepens, digital assets, tokenized real-world assets, and base settlement cryptocurrencies are expected to become foundational components of machine-to-machine financial activity.",
  "summary": "Hyperscaler cloud revenues could exceed $1 trillion annually by 2030, driven by expanding demand for computing resources required to train and run artificial intelligence (AI) systems, according to a BlackRock report. It highlighted how compute capacity is turning into a vital economic resource as AI and blockchain-based digital assets increasingly converge.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}