Goldman Sachs Sounds Alarm on AI Stocks, Urges Investors to Focus on Earnings

NEW YORK – Goldman Sachs is signaling a significant shift in the artificial intelligence (AI) stock landscape, cautioning that the freewheeling, broad-based rally of the past few years is likely over. In a new note, Goldman Sachs US equity strategist Ryan Hammond warns that the market is entering a more discerning phase, where investors will demand tangible evidence of AI's impact on a company's bottom line before committing capital. This marks a departure from earlier stages of the AI boom, which were driven more by hype and infrastructure plays.

The memo, issued on Friday, paints a picture of investor fatigue and a growing sense of skepticism. "Our discussions with investors and recent equity performance reveal limited appetite for companies with potential AI-enabled revenues as investors grapple with whether AI is a threat or opportunity for many companies," Hammond wrote. This sentiment is a far cry from the euphoria that propelled the so-called "Magnificent Seven" and other AI-related stocks to historic highs.

The Evolution of the AI Trade: From Hype to Reality

 

Goldman Sachs has previously outlined a multi-phase framework for the AI trade, and this latest note suggests the market is transitioning into the most critical phase yet.

• Phase 1: The AI Infrastructure Buildout. This initial phase was dominated by companies that build the physical backbone of the AI revolution, most notably chipmakers like Nvidia, which has seen its stock soar on demand for its specialized GPUs. This was a period of easy wins for investors, as the sheer scale of the AI arms race guaranteed massive capital expenditure from tech giants.
• Phase 2: Broadening to Infrastructure Players. The second phase expanded the focus to other companies supporting the AI infrastructure, from networking and data center firms to power utilities. These companies also saw significant tailwinds as the demand for AI computation exploded.
• Phase 3: The Moment of Truth. According to Hammond, the market is now on the cusp of entering Phase 3. This is the stage where the trade shifts from "potential" to "proof." Instead of simply investing in the shovels and picks of the AI gold rush, investors will now be looking for companies that are successfully monetizing the technology. This means showing clear, quantifiable revenue gains directly attributable to AI-powered products or services.

Winners and Losers Emerge

 

A key distinction of this new phase is the likely increase in market dispersion. While the earlier phases lifted a wide range of stocks, Phase 3 will be far more selective. "Unlike Phase 2, there will likely be winners and losers within Phase 3," Hammond stated. This is because not all companies will be equally successful at implementing and monetizing AI. For some, AI may prove to be a costly, long-term research and development project with a low return on investment. For others, it may cannibalize existing business models or introduce new competitive threats.

This dynamic presents a new challenge for investors. The "buy the sector" mentality of the last few years may prove to be a losing strategy. Instead, stock-picking will become paramount. Investors will need to conduct rigorous due diligence, analyzing a company's ability to integrate AI into its core operations, its intellectual property, and its long-term strategy for revenue generation.

Investor Skepticism and the Search for ROI

 

The shift in investor sentiment is not without reason. Despite the unprecedented capital pouring into AI, many companies are still in the early stages of figuring out how to turn that investment into profit. The cost of training and running large language models remains high, and the "killer apps" that will generate massive, sustained revenue have yet to materialize in many sectors.

For example, while some pharmaceutical companies are using AI to accelerate drug discovery, the long-term earnings impact is still speculative. Similarly, while banks are employing AI for fraud detection and risk analysis, these are often efficiency gains rather than new, large-scale revenue streams. As Hammond's note suggests, the market is no longer content with the promise of "potential AI-enabled revenues." It wants to see the money.

The Road Ahead

 

So, what does this mean for the market? While the Goldman Sachs note is a near-term warning, it is not a long-term bearish call on AI itself. The technology is undoubtedly transformative, with the potential to boost productivity and reshape entire industries. However, the path to profitability will not be a straight line for every company.

The smart money will likely be on companies that have a clear, demonstrable path to monetization. This could include software companies that are successfully embedding AI into their products, providing a clear value proposition to customers. It may also include traditional businesses that are using AI to create a sustainable competitive advantage, such as a retailer using AI to optimize its supply chain and reduce costs, or a media company using it to generate more effective content.

The coming months will be a test of which companies have a solid business plan for AI and which were simply riding the hype cycle. For investors, the era of easy, passive returns on AI stocks is over. The next chapter will require a more disciplined, evidence-based approach to investing, one that separates the technological marvels from the profitable businesses. The alarm bell has been rung, and the market is about to get a lot choosier.