Artificial Intelligence: Ten Investment Truths

Morgan Stanley

Jitania Kandhari

Research

11 Pages

Morgan Stanley presents ten perspectives on AI as a long term capital cycle with implications extending well beyond technology stocks. The paper highlights how rising compute demands, massive infrastructure spending, and intensifying global competition are reshaping industries, while suggesting the ultimate winners may differ from today’s market leaders.

Key Takeaways

Capital Spending Surge: Since the Transformer breakthrough in 2017, approximately $2.3 trillion of AI related capital expenditures have been committed, while token consumption increased more than 10x during 2025.
Compute Needs Escalate: Reasoning AI models require roughly 1,000 times more compute than generative AI, while agentic AI workloads can demand nearly 1 million times more compute resources.
Competition Is Narrowing: Chinese frontier AI models reportedly operate with only 18% of U.S. hyperscaler investment levels, yet have reduced performance gaps to approximately one month.
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