As the tech industry's earnings season unfolds, one pressing question looms over Wall Street: When will artificial intelligence start delivering real financial returns?

Since the launch of ChatGPT 18 months ago, tech giants have plunged billions into AI development, anticipating a revolution across industries. However, the tangible outcomes have been modest—ranging from chatbots with unclear monetization paths to AI-driven cost-saving measures like automated coding and customer service tools. These developments, though promising, fall short of the grand visions that initially spurred the AI race.

Despite the massive investments, Big Tech has yet to demonstrate substantial revenue growth or introduce groundbreaking AI products that justify the spending spree. Investors are beginning to express concern.

Amazon's (AMZN) recent earnings report, which disappointed the market, was largely attributed to worries that the company is heavily investing in AI without significant returns to show for it. This unease contributed to a nearly 9% drop in Amazon's stock on Friday. Similarly, Intel's (INTC) stock plummeted by 25% following the company's announcement of a $10 billion cost-cutting plan, including massive layoffs, after extensive AI-related expenditures.

Investors are increasingly questioning whether these AI investments are truly worth the cost, or if they represent another fleeting trend in the tech industry's relentless pursuit of growth. Morgan Stanley analyst Keith Weiss highlighted this skepticism during Microsoft’s earnings call, noting the ongoing debate about the capital expenditure requirements for generative AI and whether the monetization will ever match these investments.

UBS analyst Steven Ju similarly pressed Google CEO Sundar Pichai on the timeline for AI to start contributing to revenue generation and creating tangible value beyond just cutting costs. A Goldman Sachs report also raised concerns about the balance between AI spending and its benefits, asking if there was “too much spend, too little benefit” in the current AI landscape.

Shares of Google and Microsoft both dipped after their earnings reports, reflecting investor dissatisfaction with the returns on AI investments. Meta, which faced similar frustrations last quarter, managed to avoid a similar outcome this time by demonstrating how its AI investments are bolstering its core business, particularly through AI tools that help companies create compelling ads.

Some investors had hoped that this quarter would signal a scaling back of AI infrastructure investments, as AI returns have yet to meet expectations. However, tech giants like Google, Microsoft, and Meta have instead signaled plans to increase spending as they lay the groundwork for a future dominated by AI. For instance, Meta raised its full-year capital expenditure guidance to between $37 and $40 billion, while Microsoft and Google also projected significant increases in spending on AI infrastructure.

Tech leaders are asking for patience, emphasizing that AI investments are long-term bets. Microsoft CFO Amy Hood stated that the company’s data center investments would support AI monetization "over the next 15 years and beyond." Meta’s CFO Susan Li echoed this sentiment, acknowledging that returns from generative AI are expected over an extended period and not as a significant revenue driver in 2024.

However, this long-term outlook is unsettling for many investors who are used to consistent quarterly growth. As D.A. Davidson analyst Gil Luria pointed out, public companies are generally expected to deliver returns on investment within shorter time frames, making the current AI spending levels a source of discomfort.

Some investors even doubt whether AI will ever deliver the promised returns. Goldman Sachs analyst Jim Covello argued in a recent report that the technology might not be designed to solve the complex problems needed to justify its costs.

For instance, Tesla's AI-based "full self-driving" technology, which has been in development since 2015, still requires human oversight and faces ongoing safety concerns, nearly four years after its release to customers. This example highlights how long it can take for AI products to fully materialize and deliver on their promises.

For now, tech CEOs seem to agree that the risk of underinvesting in AI far outweighs the risk of overinvesting. As Google’s Pichai noted during the earnings call, missing out on the AI race due to insufficient computing capacity is a gamble no company wants to take. Despite investor unease, the core businesses of these tech giants are still strong enough to sustain the current level of AI spending.

However, Luria predicts that by late this year or early next, the pressure to scale back AI investments in favor of letting revenue growth catch up will intensify, leading some tech leaders to reconsider their strategies.