Morgan Stanley analyst highlights AI adoption challenges amid computing bottlenecks

Morgan Stanley analyst Stephen Byrd has laid out a sobering reality check for the AI boom: demand for computing power is growing so fast that the physical infrastructure underpinning it simply cannot keep pace. The firm’s research points to a US data center power demand of up to 74 gigawatts by 2028, against a supply landscape that would leave a shortfall of roughly 49 gigawatts. The numbers behind the bottleneck Global investment in AI-related infrastructure, including data center expansion, is estimated to approach $3 trillion through 2028. Morgan Stanley revised its data center power demand forecast upward in late 2025, flagging a widening gap in compute capacity driven by what Byrd describes as non-linear AI improvements. From early January 2026, weekly token consumption surged roughly 250%, escalating from 6.4 trillion to 22.7 trillion tokens per week. Byrd notes that while AI tools do yield genuine productivity gains, foundational constraints like energy supply are forecasted to remain a critical bottleneck until at least 2027 to 2028. Beyond electricity: the full stack of constraints Morgan Stanley’s research identifies what it calls “intelligence bottlenecks,” a collection ...