AI infrastructure boom Goldman Sachs reshapes TMT investment banking landscape! Betting on the trading torrent of the "computing power era"

With the rise of the global artificial intelligence technology industry, as well as almost all infrastructure business portfolios serving this frontier industry on a global scale, including Wall Street financial giants Goldman Sachs, Morgan Stanley, and JPMorgan Chase, market leaders in investment banking are undergoing large-scale restructuring of their technology, media, and telecom (TMT) investment banking teams. A recent report on the Asian AI computing power industry chain released by Goldman Sachs shows that the demand for AI server clusters is expected to continue to grow strongly through 2026, with optical network equipment demand also very strong, DRAM memory chip market supply growth remaining moderate, and demand continuing to significantly outstrip supply. According to a media report citing an internal memo, Yasmine Coupal and Jason Tofsky will lead a new global infrastructure technology business division, which will be integrated and built by Goldman Sachs' telecom and CoreTech business teams. Kyle Jessen will be appointed head of infrastructure technology M&A, while also remaining responsible for semiconductor business coverage. The internal memo also revealed that another new business division is the global internet and media sector, which will be led by Brandon Watkins and Alekhya Uppalapati. A Goldman Sachs spokesperson confirmed the contents of the internal memo disclosed by the media. Since the popularity of ChatGPT worldwide in early 2023, Wall Street financial leaders including Goldman Sachs and Morgan Stanley have been seeking opportunities for large-scale investments in the AI technology industry (including AI-related large-scale mergers and acquisitions, IPOs, etc.); in this industry, companies are investing or financing billions of dollars in AI data center and providing substantial funding to global AI developers such as the developers of ChatGPT like OpenAI. OpenAI has pledged to invest around $1.4 trillion to support the construction of ultra-large-scale AI infrastructure for AI training/inference. Goldman Sachs recently visited core companies in the Asian AI computing power supply chain and found that the demand for AI servers remains strong and is expected to continue until 2026. The shipment growth rate of AI ASIC computing clusters led by Google is expected to exceed that of AI GPUs, but the latter will also continue to grow strongly, with no signs of slowing down. On the AI computing power infrastructure supplier side, NVIDIA's Rubin architecture series AI GPU computing clusters are scheduled to start production in mid-2026 and achieve strong capacity ramp-up in the second half of 2026 as planned. Goldman Sachs stated that Asian core suppliers particularly emphasized that Broadcom's demand for TPU AI chips for Google is growing most strongly in the computing power infrastructure. Demand for optical network equipment continues to be strong, primarily driven by significant speed upgrades (such as transitioning from 800Gb to 1.6T) and price increases. Goldman Sachs research also shows that DRAM market supply growth remains moderate, with demand continuing to significantly outstrip supply, and traditional DRAM pricing is expected to increase significantly. Regarding the trend of the US stock market in 2026, Goldman Sachs' stock strategy team stated that with the widespread application of artificial intelligence technology and the resilience of the US economic growth, the US stock market is expected to reach new highs next year, with corporate profits expected to increase by double digits. In their latest report, the Goldman Sachs strategists led by Ben Snider stated that they expect overall earnings per share of S&P 500 index companies to surge 12% next year and further increase by 10% in 2027. Based on the improvement in profit expectations and the continued dominance of the AI craze in the US stock trading, Goldman Sachs reiterated its target of the S&P 500 index trading around 7,600 points next year, indicating about 10% potential upside from current levels. Goldman Sachs' strategists' forecasting model shows that the productivity enhancement driven by artificial intelligence is gradually translating into actual corporate profits, and the adoption of core AI technologies such as large-scale AI models is still in its early stages, but large companies have reported much faster progress in the penetration of AI in daily operations than small enterprises. Google's Gemini3 undoubtedly triggered a new wave of AI applications globally in the recent period. The release of the Gemini3 series brought an incredibly large volume of AI token processing, forcing Google to significantly reduce free access to Gemini 3 Pro and Nano Banana Pro, and temporarily limit access for Pro subscription users. Coupled with recent trade export data from South Korea showing strong demand for HBM storage systems and enterprise SSDs, it further validates the "AI craze is still in the early stage of the construction phase of computing power infrastructure" loudly proclaimed by Wall Street. For Wall Street giants Morgan Stanley, Citigroup, Loop Capital, and Wedbush, the global artificial intelligence infrastructure investment wave centered on AI computing hardware is far from over and is now only in its infancy. Driven by an unprecedented "AI inference endpoint computing power demand storm," this round of AI infrastructure investment wave is expected to reach scale as high as $3 trillion to $4 trillion through 2030.