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September 2025 Market Commentary

WHERE WE STAND ON GENERATIVE ARTIFICIAL INTELLIGENCE (GEN AI)

Where does Generative AI Stand?

Exactly two years ago, we shared our thoughts on Generative Artificial Intelligence (Gen AI), its capabilities, potential economic impacts, and stock investment opportunities. At that time, we were not quite one year into the launch of OpenAI’s ChatGPT, a Gen AI chatbot able to generate human-like responses to written prompts, which was seemingly an entertaining distraction. We concluded that “Patience is warranted as is being selective in investing, but if Gen AI lives up to the expectations and enthusiasm, it will generate tremendous value and wealth for companies and investors for years to come.” Fast forward two years, and we repeat that statement.

We say this despite developments including the imposition of tariffs and export restrictions on semiconductor manufacturers and the recognition of the China-based DeepSeek large language model (LLM), which spurred concerns about Gen AI economics for U.S. companies. The Gen AI train keeps rolling, and these events have done little to quell our excitement around its potential.

ChatGPT, a large language model or LLM, accelerated a lightning-paced race and spending spree to create an ever more powerful LLM. ChatGPT has over 800 million users, according to JP Morgan, and is the second fastest growing digital app in history, while OpenAI, a private company, is worth hundreds of billions of dollars. Other models in the race include Google’s Gemini, Meta’s Llama, and DeepSeek, which made a big splash with the January 2025 release of its updated DeepSeek-R1 LLM that made U.S.-based tech companies take notice of China’s Gen AI progress.

Gen AI performance is accelerating, and ChatGPT has advanced from merely an entertaining distraction. The capability of Gen AI, as measured by the length of tasks Gen AI can complete, has been doubling roughly every seven months, according to Morgan Stanley, and Gen AI’s use cases are far-reaching and already impacting many industries from healthcare (drug development) to manufacturing (automating processes with robotics).

To date, the biggest Gen AI use cases have been in the industry that spurred its creation — technology — assisting developers by writing, translating, and verifying code, effectively streamlining the software development process. Large software companies such as Microsoft (MSFT) and Salesforce (CRM) have spoken about the internal efficiencies garnered by using Gen AI tools. CRM CEO Marc Benioff has said that artificial intelligence is already handling up to half of the company's tasks. “We're looking at productivity levels of 30% to 50% this year in key functions like engineering, coding and support.” MSFT reported that 30% of its code is Gen AI-written. Anthropic’s CEO expects 90% of code to be Gen AI-written in three to six months.

Large technology companies/hyperscalers and Gen AI startups are in heavy Gen AI investment mode. According to JP Morgan, over $315 billion has been invested in Gen AI startups since 2023, with 18% of that alone going to OpenAI. The Magnificent 7 (Mag 7) are on course to spend $700-800 billion in capex and R&D in 2025, up 30-40% from 2024, with this spending centered on Gen AI infrastructure, such as data centers. Morgan Stanley estimates that nearly $3 trillion will be spent on data centers globally through 2028, with over 80% for Gen AI-specific uses.

In fact, tech sector capital spending is so large, according to JP Morgan, that it has been contributing a whopping 35%-45% of overall U.S. GDP growth over the last three quarters.

It is expected that these massive Gen AI investments will eventually generate value and a return on investment (ROI) primarily via labor productivity but also by driving revenue growth through better innovation and data insights. In a February 2025 report, Morgan Stanley estimated that Gen AI will generate approximately ~$150 billion in annual pre-tax income for the S&P by 2028 and $1.5-2 trillion in market value creation, or a 3% increase in the S&P, and up to ~$920 billion in pre-tax profits and $13–16 trillion in potential market value creation over the long-term, or a 25% increase. Further, they pointed out that Gen AI investments have had a negative ROI to date but should yield a positive ROI in 2025. Although as infrastructure investments have continued to climb to levels greater than the estimated $300 billion at the time, it’s not clear whether this prediction will materialize in 2025.

Gen AI returns will come as the technology is adopted across businesses, and although adoption is accelerating, it is still arguably in early stages. According to a Morgan Stanley August 2025 report, approximately 56% of companies worldwide were using Gen AI in 2025, up from 33% in 2024. The technology sector is leading the way in Gen AI use cases, but most industries are experiencing double-digit usage increases. Yet, according to the report, only 259 companies, comprising $8.5 trillion of market capitalization or 15-16% of the S&P 500, viewed Gen AI as a material factor. However, another 412 companies, $8.7 trillion in market cap or 15-16% of the S&P, see Gen AI use on the rise.

The New York Federal Reserve found that fewer, or 25–40%, of firms are using Gen AI, in an August 2025 survey of service and manufacturing businesses in the New York/New Jersey region, although this is up from 15-25% in 2024. Further, Gen AI is being used in a limited fashion, such as in hiring and training. As a result, they found only a modest impact on jobs, as service firms surprisingly reported a reduction in AI-related layoffs in the last year, and manufacturing firms reported no layoffs due to the technology. There is evidence, though, that hiring is being scaled back, as about 25% and 10% of service and manufacturing firms, respectively, said they plan to hire fewer workers in the future due to Gen AI. Morgan Stanley predicts that eventually 90% of occupations will be affected by Gen AI, either through automation (AI replacing tasks) or augmentation (AI assisting workers).

Although Gen AI adoption is a key gating factor to the level and pace of the payback on Gen AI investments, potential bottlenecks, particularly as it relates to data center development, may play a role too. Gen AI models demand a tremendous amount of power, and power availability is expected to worsen as we transition from the training-heavy stage of LLM development to the more energy-intensive inference stage of model use, the phase where a trained AI model uses its learned knowledge to generate new outputs or predictions in real-time, based on user prompts.

According to Morgan Stanley, U.S. data center power demand is forecasted to reach upwards of ~100 gigawatts (GW) by 2028, more than doubling from approximately 40 GW in 2024. This creates an approximately 45 GW shortfall in U.S. grid capacity. As a frame of reference, the power usage for the greater Philadelphia metropolitan area is approximately 3 GWs on average. Further, many U.S. grids currently face massive interconnection backlogs with wait times stretching five to ten years versus two to three years historically.

Other data center development bottlenecks include supply constraints for GPUs (graphic processing units or chips), turbines, cooling and electrical gear, and labor and permitting.

The technology revolution of Gen AI is upon us, but the pace and progress of its impact on economics and society will not be linear. Patience is warranted.

Investment Implications

Given that we are in the development/investment phase for Gen AI, the returns on these investments have been concentrated in a select group of companies that are key to the infrastructure build — semiconductors, cloud operators, technology hardware, and to some extent, the power sector. Generally, the benefit to companies in other sectors has not been as material or is yet to come.

The benefit to semiconductor manufacturers is clear in Nvidia’s (NVDA) results over the last two years, with revenues five times higher, earnings per share (EPS) seven times greater, and the stock up nearly +300%. But other beneficiaries include Microsoft (MSFT) (cloud infrastructure), Broadcom (AVGO) (semiconductors), Arista Networks (ANET) (networking, switching, and routing equipment), Dell Technologies (DELL) (servers), and Vertiv (VRT) (cooling equipment).

Although Amazon’s (AMZN) Web Services (AWS) division (cloud infrastructure) growth has not kept up with MSFT, given capacity constraints and MSFT’s advantageous relationship with OpenAI, we continue to believe that AWS’s growth will accelerate alongside other cloud providers.

We’ve also seen a positive impact on the results of independent power providers like Constellation Energy (CEG) that, given the lack of regulation, are the first in line to take advantage of the soaring power needs. Regulated utilities with clean power, such as natural gas and nuclear, should also benefit, and the signing of deals with big tech companies, like Meta, in the case of Entergy (ETR), is evidence of future growth to come.

Companies that provide equipment used in power production, like Eaton (ETN), should also benefit.

The impact on data center operators, such as Equinix (EQIX), has been more mixed as the higher capex required to meet surging demand has weighed on the stock, yet we still believe EQIX and Digital Realty (DLR) will benefit in the future from tremendous spending on data centers.

Gen AI should drive consumer monetization, such as in search AI-driven ads, and personal shopping assistants, and new categories, such as autonomous vehicles and wearables. We have seen consumer monetization in the results of Meta (META) and Google (GOOGL).

As we get further beyond the infrastructure investment phase of Gen AI and into the deployment of Gen AI products, enterprise software and SAS (software as a service) companies that embed Gen AI capabilities into their products should benefit — companies like Service Now (NOW) and Salesforce (CRM). Further, security software companies like Palo Alto Networks (PANW) and CrowdStrike (CRWD) should benefit as Gen AI most likely creates more security threats. Although software monetization of Gen AI has yet to broadly materialize, we still believe it will as adoption grows.

Some caution and patience in investing, though, is warranted as the market could get ahead of the realization of Gen AI’s potential. Ironically, Sam Altman, CEO of OpenAI, which owns ChatGPT, said in an August 2025 interview: “Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes.”

We don’t waver from our statement about Gen AI of two years ago, but are braced for volatility and intend to keep our sights focused on the long-term potential of this supercharged new technology.

Yours in trust,

Kristin and Paul

Bibliography

Morgan Stanley (2025, February 25). Global Technology. GenAI Monetization – Assessing the ROI Equation.

Morgan Stanley (2025, July 15). Global Infra, Tech, Utilities & Renewables, Cap Goods, Construction, Real Estate. Global Data Center Capacity Growth to Increase 6x.

JP Morgan (2025, July 18). OpenAI: Marching to the Beat of its Own Disruption Drum.

Morgan Stanley (2025, August 27). AI Adoption and the Future of Work.

JP Morgan (2025, September 2). Michael Cemblast. Eye on the Market.

Liberty Street Economics (2025, September 4). Jaison R. Abel, Richard Deitz, Natalia Emanuel, Ben Hyman, and Nick Montalbano, Are Businesses Scaling Back Hiring Due toAI? Federal Reserve Bank of New York.

Morgan Stanley (2025, September 10). Powering AI: Assessing the Landscape.

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