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70% Grid Failure Rate Threatens $5.2T AI Infrastructure Buildout — and Hyperscaler Valuations

70% Grid Failure Rate Threatens $5.2T AI Infrastructure Buildout — and Hyperscaler Valuations

More than 70% of US grid interconnection requests are withdrawn before approval, according to Berkeley Lab, threatening the $5.2 trillion in AI data center capex planned through 2030. Goldman Sachs projects data center power demand to surge 165% by 2030 versus 2023 levels, but the grid was built for 1–2% annual growth. For Microsoft, Amazon, and Alphabet, the mismatch between capex deployment and capacity delivery is a direct threat to earnings visibility.

LM Salvado•
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What we're seeing
Enterprise Software Races to Govern and Consolidate Around Agentic AI
Enterprise software vendors are repositioning around autonomous AI agents. Salesforce is acquiring Braze, ServiceNow is launching agent governance tools (AI Passport, Super Intelligence Control Tower), SAP is pushing its 'Autonomous Enterprise', and Zeta is launching AthenaOS and its own inference model. Palantir is embedding itself in banking, aviation and sovereign AI infrastructure through partnerships with Customers Bank, Surf Air, Ondas and Armada. Governance, data sovereignty and enforced policy are emerging as preconditions for regulated sectors like finance. Investors such as Norwest see room to disrupt ERP and finance software, and they caution that AI should not be trusted with financial calculations. Consolidation and shareholder disputes (Salesforce/Braze, Tiny/Oso Cloud, ZenaTech/Boardwalktech) show the market reshaping.
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EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
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Where sources disagree
Ford Motor Company
Both facts give cash for Ford Motor Company at the same point in time (2025-12-31; FY 2025 year-end and Q4 2025 year-end are the same date). Both are labelled USD, but the values are 23,356,000,000 and 23.356, which cannot both be true in USD. The two numbers agree once the second is read as billions (23.356 bn = 23,356,000,000), so the economic content is consistent and the conflict is a unit/scale error in the Q4 2025 record. The period is not the reason for the conflict: a Q4 and an FY figure at the same year-end date should match.
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