AI Dominates Tech Earnings While Remaining a Blind Spot Elsewhere

Wall Street is intensely scrutinizing how technology companies are building and funding artificial intelligence. Far less attention, however, is being paid to how AI is actually being used by companies outside the tech sector even as US businesses collectively spent an estimated $86 billion on AI systems this year.

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Despite the scale of that investment, questions about generative AI remain surprisingly limited across much of corporate America. According to Bloomberg News’ review of earnings call transcripts, fewer than half of companies in the S&P 500 Index were asked about generative AI during earnings calls in 2025. In the most recent quarter, while more than 80% of technology firms fielded AI-related questions, just under one-third of companies across the broader index faced similar inquiries.

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That lack of curiosity stands out, particularly given the market backdrop. The S&P 500 has surged roughly $30 trillion over the past three years, a rally that began around the same time OpenAI launched ChatGPT. The debut of the chatbot fueled sweeping predictions that artificial intelligence would fundamentally reshape office work, customer service, and countless other business functions.

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Some market veterans find the silence puzzling. Heath Terry, global head of technology and communications research at Citigroup Inc., said he is astonished that earnings calls can pass without meaningful discussion of AI. From his perspective, the issue should be front and center for investors. Companies without a clear AI strategy, he warned, risk being left behind as the technology reshapes competitive dynamics.

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Bloomberg’s analysis reviewed more than 7,000 earnings call transcripts using a large-language model. The study focused on questions related to AI designed to replicate or enhance human capabilities, such as reasoning, decision-making, problem-solving, and completing complex tasks. It intentionally excluded discussions centered on factory automation, autonomous vehicles, and data-center leasing or financing.

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Some sectors are getting partial attention. Energy producers, utilities, and select industrial, materials, and real estate companies are increasingly being asked how they plan to benefit from the massive infrastructure investments required to support AI, including power generation and data-center capacity. Yet analysts rarely press these same companies on how they are deploying AI internally to improve efficiency, reduce costs, or drive growth.

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In industries such as finance and real estate, management teams are beginning to face more questions about AI initiatives, but those conversations remain the exception rather than the rule. Earnings calls typically revolve around what analysts view as the most immediate financial drivers, and for many non-tech companies, AI is still seen as peripheral.

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From that perspective, artificial intelligence is often viewed as too small to materially impact earnings at least for now. Ohsung Kwon, chief equity strategist at Wells Fargo & Co., noted that outside the technology sector, AI often does not yet “move the needle” enough to dominate analyst discussions.

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That assumption may soon be challenged. A recent Bloomberg Intelligence survey of more than 600 senior executives across nine industries found expectations of significant AI-driven disruption in every sector surveyed. Leaders in five industries financial services, media and cable, hospitals, pharmaceuticals, and telecommunications said AI would lead to a “high” or “very high” increase in operating costs in the near term.

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Spending figures reinforce that shift. Excluding companies that are directly building AI infrastructure and platforms, US businesses spent approximately $86 billion on AI in 2025, according to IDC vice president Rick Villars. That figure is projected to jump sharply to $131 billion next year, highlighting how rapidly adoption is accelerating across the economy.

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On earnings calls, analysts have been pressing the companies building AI chipmakers, cloud providers, and software platforms to explain how and when massive investments will translate into profits. When it comes to companies outside the tech ecosystem, however, analysts often appear to be searching for concrete use cases rather than demanding clear financial returns.

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When AI does come up during question-and-answer sessions for non-tech firms, the discussion typically centers on implementation and experimentation. Some analysts are beginning to ask about AI-related spending plans and expected payoffs, but management teams more frequently emphasize productivity gains, efficiency improvements, and long-term potential rather than near-term returns.

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This imbalance could mean Wall Street is missing valuable signals. By not probing how widely and aggressively AI is being adopted, investors may be overlooking insights into future demand for AI products and services. Lessons from the dot-com era suggest that understanding user adoption can be just as important as tracking the companies building the technology.

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As Bloomberg Intelligence equity strategist Gillian Wolff pointed out, the internet ultimately transformed the global economy, but the early bubble formed because investment raced ahead of adoption. Capital flooded into the space faster than businesses and consumers were ready to fully embrace the technology.

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Wolff sees a similar risk emerging with artificial intelligence. While she believes AI will be transformative over time, she cautions that investment may be moving faster than adoption. If investors begin demanding rapid returns before companies are prepared to deploy AI at scale, expectations could reset quickly.

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For now, Wall Street’s focus remains heavily skewed toward AI’s creators rather than its users. But as spending climbs and adoption broadens, the questions analysts ask and the answers they demand are likely to evolve.