商品敘述：

In early 2026, Meta Platforms and its hyperscaler peers were investing record amounts in AI infrastructure, with Meta''s capital expenditures climbing from $72.2 billion in 2025 to a projected $135 billion in 2026, largely for data centers and GPUs. Alongside this buildout, Meta extended the useful life of its servers and network assets from four years to five and a half years, a revision that reduced 2025 depreciation expense by $2.9 billion. Every major hyperscaler made similar extensions between 2020 and 2025. Short sellers argued the changes overstated profits by understating the true pace of GPU obsolescence, while management pointed to improved hardware reliability, software efficiency, and operational experience. The case examines the risks and opportunities of Meta''s transition to AI, how the shift is reflected in its financial statements, and the role depreciation assumptions play in shaping reported earnings.

涵蓋領域：

Accounting;Advertising;AI and machine learning;Budgets and budgeting;Capital investments;Change management;Decision making;Decision making and problem solving;Digital marketing;Digital skills;Earnings forecasting;Economic forecasting;Economics;Financial crisis;Financial statements;Financial strategy;Growth strategy;Investment management;Joint ventures;Leadership transitions;Managing uncertainty;Predictive analytics;Risk management;Social marketing;Social media;Strategy;Technology adoption lifecycle;Value creation

相關資料：

, (9-126-081), p, by Jonas Heese, Aliya Korganbekova

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