--- title: "Opportunity to Buy the Dip in US AI Stocks After Sell-off? Morgan Stanley Bullish on NVIDIA and Other Tech Giants, Maintains Capex Forecast of $1.6 Trillion by 2027" type: "News" locale: "en" url: "https://longbridge.com/en/news/304866337.md" description: "Morgan Stanley believes the adjustment in the AI sector following the US midterm elections is an overreaction by the market, with the long-term investment logic remaining unchanged. The bank advises investors to buy large-cap tech, semiconductor, and software companies on dips. Although some data center projects may be delayed, the forecast for AI capital expenditure remains unchanged, expected to reach $1.6 trillion in 2027 and $1.8 trillion in 2028" datetime: "2026-11-09T14:29:03.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/304866337.md) - [en](https://longbridge.com/en/news/304866337.md) - [zh-HK](https://longbridge.com/zh-HK/news/304866337.md) generator: "portal-rs" --- # Opportunity to Buy the Dip in US AI Stocks After Sell-off? Morgan Stanley Bullish on NVIDIA and Other Tech Giants, Maintains Capex Forecast of $1.6 Trillion by 2027 Morgan Stanley stated in its latest global thematic research report released on November 8 that concerns about the prospects of data center construction following the US midterm elections triggered a significant correction in artificial intelligence (AI)-related stocks. However, the bank believes the market reaction was excessive and the long-term investment logic for AI has not fundamentally changed. Morgan Stanley recommends that investors adopt a selective buy-on-dip strategy, focusing on large-cap tech companies, semiconductor and data center infrastructure firms with significantly corrected valuations, and software companies poised to benefit from the commercial application of AI. Morgan Stanley believes that policy changes resulting from the US midterm elections will mainly affect the construction timelines of certain data center projects, rather than the overall demand for AI investment. Although newly elected governors may push for stricter approval and construction requirements for data centers, projects already in the construction phase are not expected to be significantly affected. The bank estimates that approximately 20% of US data center projects originally scheduled for 2028 may be postponed to 2029, involving about 5 gigawatts of IT load capacity, equivalent to roughly 10% of related global projects. As a result, new data center capacity in the US is expected to decline by about 4% year-over-year in 2028, before rebounding by approximately 38% in 2029. However, Morgan Stanley emphasizes that project delays do not equate to investment cancellations. On the contrary, extended construction cycles may make the growth in AI capital expenditure more sustainable, help alleviate supply-demand imbalances in the supply chain, improve financing conditions, and support computing power leasing prices. **Maintains AI Capex Forecast: $1.6 Trillion in 2027 and $1.8 Trillion in 2028** Despite adjusting the construction timelines for some data center projects, Morgan Stanley currently maintains its forecast for the overall capital expenditure of large cloud computing and tech enterprises, expecting it to reach approximately $1.6 trillion in 2027 and $1.8 trillion in 2028. The bank believes that large tech companies will continue to expand their computing infrastructure as much as possible to support the rollout of large language models and AI applications to billions of users. As AI model capabilities continue to improve, demand for computing resources for related products will remain strong. However, Morgan Stanley also warns that if delays in data center approvals continue to expand, the capex forecast for 2028 may face downward pressure. From a supply and demand perspective, power supply remains one of the main bottlenecks for AI infrastructure expansion. Morgan Stanley's model shows that the global shortage of data center capacity with available power supply is expected to reach 44 gigawatts in 2028, an increase of about 15% from previous forecasts. This means that even if some projects are delayed, data centers that can timely secure power supply and become operational will still possess high scarcity value. Meanwhile, Morgan Stanley believes that stricter construction approvals and higher project costs may further strengthen the competitive advantages of large tech companies. Compared to smaller AI infrastructure operators, companies like Amazon, Alphabet, and Meta Platforms have more ample capital, more mature technology systems, and stronger project execution capabilities. **Bullish on Amazon, Alphabet, Meta Platforms, and Microsoft; NVIDIA Remains a Core Beneficiary** Regarding specific investment directions, Morgan Stanley is first bullish on large tech companies with advantages in scale, capital, and technology. The bank assigns an "Overweight" rating to Amazon (AMZN.US), Alphabet (GOOGL.US), Meta Platforms (META.US), and Microsoft (MSFT.US), believing that these companies can leverage their capital strength and AI model R&D capabilities to continue expanding their market share in an environment where computing resources are constrained. According to the target prices listed in the report, Morgan Stanley assigns a target price of $820 to Meta Platforms, implying a potential upside of approximately 35.5% from the reference stock price in the report; a target price of $375 for Alphabet, implying a potential upside of about 32.7%; a target price of $335 for Amazon, implying a potential upside of about 28.7%; and a target price of $650 for Microsoft, implying a potential upside of about 21.3%. In addition, Morgan Stanley is also bullish on NVIDIA (NVDA.US), assigning it an "Overweight" rating and a target price of $300, implying a potential upside of approximately 60.7% from the reference stock price in the report. The bank points out that although NVIDIA is not a cloud computing giant, its chips and related technologies can enhance the AI computing power and commercial value generated per unit of electricity. In situations where power and data center capacity are limited, the importance of improving computing efficiency will further rise. Morgan Stanley also expects that AI model developers will place greater emphasis on improving computing efficiency, achieving stronger AI capabilities with fewer computing resources through methods such as model distillation, architecture optimization, and improvements in training and inference processes. **Opportunities Remain in Semiconductor and Data Center Supply Chains, But Stock Selection Requires Greater Caution** In addition to large tech companies, Morgan Stanley believes that the recent sharp correction in stock prices has also created investment opportunities for some semiconductor and AI infrastructure companies. In the semiconductor sector, the bank prefers industry leaders with larger scale and strong capital strength, including NVIDIA, Broadcom (AVGO.US), Taiwan Semiconductor (TSM.US), MediaTek, and Samsung Electronics. Among them, Morgan Stanley assigns a target price of $505 to Broadcom, implying a potential upside of about 72% from the reference stock price in the report. The bank is also paying attention to hardware sectors with recently corrected valuations, including hard drive manufacturers Seagate Tech (STX.US) and Western Digital (WDC.US), as well as optical communication and networking equipment companies Lumentum (LITE.US), Coherent Corp. (COHR.US), and Arista Networks (ANET.US). However, Morgan Stanley warns that delays in data center construction projects may lead to risks of slowed order growth, increased inventory, and declining profit margins for some upstream supply chain companies in 2028. Therefore, the bank does not recommend that investors broadly buy all sold-off AI infrastructure stocks, but instead emphasizes the need to screen based on valuation, supply and demand conditions, and corporate profitability. In the data center and power infrastructure sectors, Morgan Stanley focuses on companies such as Equinix (EQIX.US), Terawulf (WULF.US), Hut 8 Mining (HUT.US), Riot Platforms (RIOT.US), and Applied Digital (APLD.US). At the same time, the bank remains bullish on some companies that can provide power solutions for data centers, including Bloom Energy (BE.US), Vistra (VST.US), Talen Energy (TLN.US), and Constellation Energy (CEG.US). Morgan Stanley believes that as some US data center construction projects face approval restrictions, the competitive advantages of companies with ready-made power resources capable of rapidly delivering computing infrastructure may further strengthen. **AI Investment Opportunities Are Spreading from Chips and Infrastructure to Software and Applications** Morgan Stanley also emphasizes that an important change is occurring in the AI investment cycle: market focus is expected to gradually shift from chip and infrastructure construction to software services and the practical application of AI technology. The bank points out that in previous cycles of computational technology development, investment returns usually concentrated first on semiconductor companies, then expanded to infrastructure, and finally shifted to software and services. As companies begin to put AI technology into actual business operations, a similar trend may emerge again. In the software sector, Morgan Stanley is bullish on companies such as Microsoft, Snowflake (SNOW.US), Datadog (DDOG.US), MongoDB (MDB.US), CloudFlare (NET.US), and ServiceNow (NOW.US). In the cybersecurity sector, the bank is focusing on Palo Alto Networks (PANW.US), CrowdStrike (CRWD.US), Okta (OKTA.US), and Rubrik (RBRK.US). In addition, Morgan Stanley believes that productivity gains brought by AI applications are gradually spreading to traditional industries such as finance, healthcare, consumer goods, and industrial sectors. Companies such as Bank of America (BAC.US), Citigroup (C.US), Unitedhealth (UNH.US), Procter & Gamble (PG.US), and Visa (V.US) are also included in its list of key companies benefiting from AI applications. ### Related Stocks - [AMZN.US](https://longbridge.com/en/quote/AMZN.US.md) - [ANET.US](https://longbridge.com/en/quote/ANET.US.md) - [APLD.US](https://longbridge.com/en/quote/APLD.US.md) - [AVGO.US](https://longbridge.com/en/quote/AVGO.US.md) - [BAC.US](https://longbridge.com/en/quote/BAC.US.md) - [BE.US](https://longbridge.com/en/quote/BE.US.md) - [C.US](https://longbridge.com/en/quote/C.US.md) - [CEG.US](https://longbridge.com/en/quote/CEG.US.md) - [COHR.US](https://longbridge.com/en/quote/COHR.US.md) - [CRWD.US](https://longbridge.com/en/quote/CRWD.US.md) - [DDOG.US](https://longbridge.com/en/quote/DDOG.US.md) - [EQIX.US](https://longbridge.com/en/quote/EQIX.US.md) - [GOOG.US](https://longbridge.com/en/quote/GOOG.US.md) - [GOOGL.US](https://longbridge.com/en/quote/GOOGL.US.md) - [HUT.US](https://longbridge.com/en/quote/HUT.US.md) - [LITE.US](https://longbridge.com/en/quote/LITE.US.md) - [MDB.US](https://longbridge.com/en/quote/MDB.US.md) - [META.US](https://longbridge.com/en/quote/META.US.md) - [MSFT.US](https://longbridge.com/en/quote/MSFT.US.md) - [NET.US](https://longbridge.com/en/quote/NET.US.md) - [NOW.US](https://longbridge.com/en/quote/NOW.US.md) - [NVDA.US](https://longbridge.com/en/quote/NVDA.US.md) - [OKTA.US](https://longbridge.com/en/quote/OKTA.US.md) - [PANW.US](https://longbridge.com/en/quote/PANW.US.md) - [PG.US](https://longbridge.com/en/quote/PG.US.md) - [RBRK.US](https://longbridge.com/en/quote/RBRK.US.md) - [RIOT.US](https://longbridge.com/en/quote/RIOT.US.md) - [SNOW.US](https://longbridge.com/en/quote/SNOW.US.md) - [STX.US](https://longbridge.com/en/quote/STX.US.md) - [TLN.US](https://longbridge.com/en/quote/TLN.US.md) - [TSM.US](https://longbridge.com/en/quote/TSM.US.md) - [UNH.US](https://longbridge.com/en/quote/UNH.US.md) - [V.US](https://longbridge.com/en/quote/V.US.md) - [VST.US](https://longbridge.com/en/quote/VST.US.md) - [WDC.US](https://longbridge.com/en/quote/WDC.US.md) - [WDCVV.US](https://longbridge.com/en/quote/WDCVV.US.md) - [WULF.US](https://longbridge.com/en/quote/WULF.US.md) - [UTSD.SG](https://longbridge.com/en/quote/UTSD.SG.md) ## Related News & Research - [Equinix Opens SG6 in Singapore, Expanding AI-Ready Capacity in One of Asia-Pacific's Most Connected Markets | EQIX Stock News](https://longbridge.com/en/news/304604440.md) - [Equinix opens $290M SG6 data center in Singapore](https://longbridge.com/en/news/304795811.md) - [Learn Why The Bull Case For Bank of America Stock Could Change Following AML Lawsuit](https://longbridge.com/en/news/305006008.md) - [Visa (V) Builds Six Global Capability Hubs In Singapore](https://longbridge.com/en/news/304391796.md) - [Citi obtains securities license in China after five year wait - report](https://longbridge.com/en/news/305024599.md) --- > **Disclaimer: This article is for reference only and does not constitute any investment advice.**