AI Spending Could Soar to $4 Trillion: 2 No-Brainer Stocks to Buy Now (Hint: Neither Is Nvidia)
News Summary
Jensen Huang, CEO of Nvidia, predicts that artificial intelligence (AI) infrastructure spending could skyrocket to $4 trillion by the end of the decade. This forecast is supported by recent trends, with companies like Meta Platforms and Alphabet increasing capital expenditure for AI buildout, and chip designers and cloud service providers reporting consistent demand and revenue growth. The article recommends two "no-brainer" stocks that are not Nvidia. First, Nebius Group offers much-needed capacity to AI customers, resulting in a 625% year-over-year revenue surge to approximately $105 million in the latest quarter, with its AI cloud business achieving positive adjusted EBITDA ahead of expectations. Nebius helps customers save time and money through GPU rentals and managed services, and plans to add 1 gigawatt of power by the end of next year to meet demand. The second recommended stock is Taiwan Semiconductor Manufacturing Company (TSMC). As the world's largest foundry, TSMC manufactures chips for giants like Nvidia, AMD, and Broadcom. This positions TSMC for explosive revenue growth as demand for all these AI products increases. TSMC has also made significant investments in the U.S., expanding its commitment to $165 billion earlier this year to fund three new fabrication facilities, an R&D site, and two advanced packaging factories, which may help shield it from import tariffs. With sustained AI demand and a reasonable valuation of 29 times forward earnings, TSMC is considered a "no-brainer" buy as AI infrastructure spending intensifies.
Background
Currently, the world is undergoing a profound transformation driven by artificial intelligence technology, leading to an explosive growth in demand for AI computing power, especially high-performance Graphics Processing Units (GPUs), across various industries. This has prompted tech giants to invest heavily in building and upgrading AI infrastructure to support complex model training and inference tasks. Chip design companies like Nvidia are central drivers of this wave, while wafer foundries such as TSMC silently underpin the entire AI chip ecosystem. Concurrently, cloud service providers have become crucial players, lowering the barrier for enterprises to deploy AI by offering on-demand computing resources. In 2025, under the leadership of President Donald J. Trump, the "America First" economic policy context particularly highlights the need for localization of critical technology supply chains and protection from tariffs.
In-Depth AI Insights
1. What are the deeper implications of Jensen Huang's $4 trillion AI spending prediction for the global economy and geopolitical strategy? - This massive expenditure is not merely a technological investment; it represents an "AI computing power arms race" among nations and corporations vying for leadership and economic dominance in the AI era. - It will accelerate the restructuring of global supply chains, driving investment and localization in critical areas like chip manufacturing, data center construction, and energy infrastructure to mitigate geopolitical risks and ensure strategic autonomy. - The widespread deployment and deepening of AI infrastructure will spawn entirely new business models and industrial ecosystems, profoundly altering labor market structures and potentially exacerbating the technology divide and inequality between nations. 2. How do Nebius Group's and TSMC's business models offer distinct investment value and risk diversification advantages compared to pure-play AI chip design companies like Nvidia in the current market? - Nebius, as an AI cloud service provider, offers value by providing "AI as a service," reducing customers' initial capital expenditure and operational complexity. This allows it to generate recurring revenue from a broad range of AI applications and rely less on the success of a single chip designer. - TSMC, as an independent wafer foundry, benefits from the growth of the entire AI chip industry. Regardless of which design company dominates at a particular time, as long as overall AI chip demand rises, TSMC profits. This "picks and shovels" role makes it more resilient to fluctuations in specific customers or technological roadmaps. - In contrast, while Nvidia is an industry leader, its revenue is more directly tied to the market acceptance and iteration speed of its own chip designs, facing more direct competition and potential technology roadmap risks. 3. What are the true strategic considerations and potential returns behind TSMC's massive investment in the U.S. under the current Trump administration? - TSMC's substantial U.S. investment is a strategic move driven by both geopolitical pressure and market opportunity. Under President Trump's "America First" and domestic manufacturing resurgence policies, this initiative aims to circumvent potential trade barriers and tariff risks, while also securing U.S. government policy support and subsidies (e.g., the spirit of the CHIPS Act, though not explicitly mentioned, aligns perfectly). - By establishing advanced manufacturing bases in the U.S., TSMC can be closer to its largest AI customer base, better respond to localization demands, and reduce the risk of supply chain disruptions. - Despite high initial costs, this move helps solidify TSMC's strategic position in the global semiconductor supply chain, enhances its bargaining power and customer trust in Western markets, thereby ensuring long-term growth and market share.