CLSA: Four Major AI Concerns Appear Overstated; Planned Data Centers at About 200 Gigawatts, More Than Chip Supply

CLSA: Four Major AI Concerns Appear Overstated; Planned Data Centers at About 200 Gigawatts, More Than Chip Supply CLSA issued a research report stating that the global technology sector's AI supply chain is once again beset by concerns over politics, data centers, funding, and the Anthropic IPO, but the firm believes these fears appear overstated and analyzes them along four main lines: politics, gigawatt capacity, trillion-dollar funding needs, and IPOs. The firm notes that both parties have concerns about data centers, but most lean toward setting guardrails rather than a full moratorium, representing a relative breather; US data centers under construction total about 150 gigawatts, with another roughly 46 gigawatts outside the US and China, for a combined total of about 200 gigawatts. The market worries there will be nowhere to put the chips, but the firm instead believes chips may be in short supply, with AI-related incremental demand from now to 2030 potentially around 110 gigawatts, and some delays could help balance overly aggressive data center plans against Taiwan Semiconductor Manufacturing Co., Ltd. Sponsored ADR (TSM.US) capacity. On funding, the firm estimates that to achieve mid-teens capital returns, cloud computing revenue may need to rise from about US$450 billion in 2026 to about US$3.5 trillion in 2035, equivalent to shifting only about 175 basis points more of global GDP; compared with past peaks in computerization and telecommunications end-user spending, which respectively reached about 4.5% and a combined roughly 7.2% of global GDP, the claim that "the money will run out" is seen as overstated. The firm also notes that the Anthropic IPO is stirring sentiment, but it estimates Anthropic accounts for about 11% of global (excluding China) tokens and OpenAI about 27%, and the market appears to be devoting 100% of its energy to worrying about a player with about a one-tenth share; it also lists more than 100 new AI labs with combined private valuations exceeding US$650 billion, showing the industry landscape remains unsettled.