Goldman Sachs has changed its advice on AI investments because of recent ups and downs in the tech market. They’re now telling investors to put their money in companies that make money from AI products and services, rather than companies that build the technology that supports artificial intelligence. This shift in strategy comes as AI stocks are experiencing their biggest drop in value since AI became popular in 2023.
Market correction triggers strategy reassessment
The S&P 500’s February 19 peak marked a turning point for AI stocks, with the sector experiencing its first major pullback after nearly two years of explosive growth. Since that inflection point, companies focused on AI infrastructure have declined 14%, while firms generating revenue through AI applications have dropped 12%, according to Goldman’s latest technology investment report.
“We’re witnessing a natural maturation of the AI investment cycle,” explained Sarah Chen, Goldman Sachs’ Chief Technology Investment Strategist. “The initial euphoria around infrastructure buildout is giving way to harder questions about which companies can translate AI capabilities into sustainable revenue streams.”
This correction follows an unprecedented run that saw the AI sector outperform the broader market by over 45% in 2024, creating valuation concerns even among the strongest advocates of AI. Market analysts point to multiple factors driving the current volatility.
The four phases of AI investment evolution
Goldman Sachs breaks down AI companies into four simple groups to help investors understand where to put their money:
Chip Makers (Phase 1): Companies like NVIDIA that make the special computer chips needed to run AI. These were the early winners, with NVIDIA’s stock up 450% since 2023.
Infrastructure Companies (Phase 2): Businesses like Snowflake and MongoDB that provide the behind-the-scenes technology needed to support AI, such as cloud services and data storage. These companies are now facing more competition and pressure.
Revenue Generators (Phase 3): Companies that sell AI products and services. Goldman now recommends focusing on these companies for investment.
Productivity Users (Phase 4): Regular businesses in all industries that use AI to work more efficiently and save money. This is potentially the biggest group but is still developing.
Goldman believes investors are shifting their attention from companies building AI infrastructure to those making real money from AI technologies. They suggest the most successful investments will be in companies that can show actual profits from their AI products.
Economic headwinds challenge AI spending
The Federal Reserve’s continued restrictive monetary policy has contributed to revised economic growth forecasts, raising concerns about corporate spending capacity for AI initiatives. The technology sector has proven particularly sensitive to interest rate projections, with many high-growth AI companies experiencing valuation contractions as borrowing costs remain elevated.
This dynamic has accelerated the transition toward Goldman’s Phase 3 companies, which can demonstrate tangible returns on AI investments through enhanced revenue generation. Investors increasingly favor businesses that have successfully integrated AI into their core offerings rather than those still in experimental stages.
Competition intensifies in the world market global scale
The competitive landscape for AI technologies has evolved dramatically in recent months, with several international players emerging as significant forces. China’s DeepSeek, backed by substantial government investment, has demonstrated capabilities rivaling those of American AI leaders, challenging assumptions about U.S. technological dominance.
“The AI race has become truly global,” said Dr. Elena Rodriguez, Director of Emerging Technology Research at the International Technology Institute. “Chinese companies are no longer simply replicating Western innovations but increasingly setting their own development trajectories, particularly in areas like large language models and computer vision.”
This intensified competition has pressured valuations across the sector as investors reassess growth projections in light of a more crowded marketplace. Companies unable to differentiate their AI offerings face particular challenges in this environment.
Valuation reset creates selective opportunities
The recent market correction has brought AI valuations closer to historical technology sector norms, creating potential entry points for long-term investors. Goldman Sachs identifies several Phase 3 companies likely to achieve extraordinary sales growth over the next two years despite current market tremors.
Among Goldman’s highlighted opportunities
Palantir Technologies has transitioned from government contracts to commercial applications of its data analytics platform. The company reported 37% year-over-year commercial revenue growth in its most recent quarter, with AI-powered solutions driving the majority of new client acquisitions.
Cloudflare has integrated AI capabilities throughout its cybersecurity and content delivery network, creating valuable differentiation in a competitive market. The company’s AI-enhanced services command premium pricing while delivering measurable performance improvements for clients.
SentinelOne leverages AI for advanced threat detection in cybersecurity applications, an area seeing sustained demand despite broader technology spending pressures. The company’s autonomous protection platform addresses critical security needs while reducing human resource requirements.
GitLab (GTLB) has embedded AI throughout its DevOps platform, significantly enhancing developer productivity and code quality. The company’s AI-powered features have become critical differentiators in competitive sales processes.
“These companies share a common thread: they’ve moved beyond the promise of AI to deliver measurable business outcomes for their customers,” Chen emphasized. “That capability will increasingly separate market winners from the broader field of AI aspirants.”
Emerging markets present alternative AI exposure
While much attention focuses on U.S. technology leaders, Goldman Sachs has also identified significant AI-related opportunities in emerging markets. The firm recently raised its 12-month target for the MSCI Emerging Markets Index to 1,220, suggesting an 11% potential upside from current levels.
This adjustment reflects growing evidence of AI adoption driving enhanced productivity and profit margins across multiple sectors in developing economies. Chinese technology firms, in particular, have demonstrated remarkable progress in developing and deploying AI capabilities at scale.
“The AI revolution isn’t confined to Silicon Valley,” noted Alexander Kim, Goldman’s Head of Emerging Markets Strategy. “Companies across Asia, Latin America, and parts of Africa are rapidly implementing AI solutions, often with fewer legacy system constraints than their Western counterparts.”
This global diffusion of AI capabilities has important implications for investors seeking diversified exposure to the technology’s long-term potential. Goldman recommends a balanced approach incorporating select emerging market opportunities alongside established Western technology leaders.
Investment implications: selectivity and patience
For investors navigating the evolving AI landscape, Goldman Sachs emphasizes the importance of selectivity and realistic timeline expectations. The firm maintains its long-term bullish outlook on AI technology while acknowledging that it will take years to reach its full potential.
“We’re still in the early chapters of the AI transformation,” Chen said. “The companies that prove they can translate technical capabilities into sustainable business advantages will ultimately deliver the strongest returns, but that process takes time and rarely follows a linear path.”
Goldman recommends investors focus on several key criteria when evaluating AI investments:
Demonstrable Revenue Impact: Companies already generating meaningful revenue from AI-enhanced products and services.
Pricing Power: Businesses able to command premium pricing for AI-differentiated offerings.
Defensible Advantages: Organizations with proprietary data, algorithms, or implementation expertise that competitors cannot easily replicate.
Management Vision: Leadership teams articulating clear, credible strategies for AI monetization.
The next AI investment horizon
Despite current market challenges, Goldman Sachs remains confident in the potential of artificial intelligence across virtually every industry. The firm projects that AI applications will contribute more than $8 trillion annually to global economic output by 2027, representing perhaps the most significant technological inflection point since the internet’s emergence.
“We’re experiencing a natural recalibration after the initial enthusiasm,” Chen concluded. “The fundamentals driving AI adoption—enhanced productivity, novel capabilities, and competitive necessity—remain firmly intact. The question isn’t whether AI will transform business operations but which companies will most effectively capitalize on that transformation.”
For investors with appropriate risk tolerance and time horizons, the current market environment may offer compelling entry points into select AI-related companies. Goldman recommends a balanced approach combining established technology leaders with emerging specialists across multiple geographies.
While many companies will benefit from AI advancement over time, successful investing requires identifying businesses with lasting competitive advantages. Investors must look beyond hype and focus on how companies convert AI technology into actual business performance and results in an increasingly crowded marketplace.
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