The question has stock watchers on the edge of their seats for Nvidia’s quarterly earnings report on Wednesday afternoon. The results will give critical insight into the company’s future and clues about the chip industry’s financial performance overall.

“It’s the most important stock in the world right now,” EMJ Capital’s Eric Jackson told CNBC’s Closing Bell about Nvidia last week. Meanwhile, tech analyst Dan Ives of Wedbush Securities called Nvidia’s upcoming report nothing less than “the most important tech earnings in years.”

But Nvidia’s results won’t necessarily shed light on the broader AI industry and whether the tens of billions of dollars poured into it will ultimately pay off. That’s because the AI boom isn’t just about Nvidia. It’s also about the AI cloud providers, AI startups, and legacy businesses scrambling to make money from AI tools. And that will take time to play out.

The primary market for Nvidia’s AI chips, called GPUs, are companies training the biggest and most sophisticated AI models. They include OpenAI and Anthropic, as well as tech giants such as Google, Microsoft, and Amazon.

Just to give a sense of demand for Nvidia chips: Facebook and Instagram parent Meta, on its own, is hoarding nearly 350,000 GPUs, likely worth over $9 billion.

But most companies aren’t training massive generative AI models, instead using them to spit out information, or inference in industry jargon. While Nvidia sells chips for inference, it built its high-flying business on supplying chips necessary for the complicated work of training models. As the industry evolves, it is inference that is the bigger long-term opportunity, and there is more competition there for Nvidia.

Also, corporations usually do their inference work in the cloud. Big cloud providers like Amazon’s AWS, Google Cloud, and Microsoft Azure, as well as AI cloud startups like Coreweave and Groq, are all helping companies power and grow their AI inference efforts. Their future of these providers is largely independent of Nvidia and therefore Nvidia’s earnings don’t reveal much about their financial performance. Additionally, the AI cloud industry will take time to mature, according to Daniel Newman, principal analyst of Futurum Research. He expects another one to three years of investment in AI infrastructure before the “Walmart-like use cases” of generative AI, or obvious successes in industries like retail, travel, and hospitality, are known.

For now, there are plenty of companies starting to incorporate AI into their software and operations, Newman said. But when it comes to actually making money and creating viable business models, that’s “still somewhat opaque.”

Stock watchers will certainly focus on Nvidia for some time and whether its shares can continue to soar. After all, during its remarkable rise in stock price since early 2023, the company’s market value has increased nearly 10-fold from $350 billion to $3 trillion this summer. 

But when it comes to the overall AI landscape, many on Wall Street are wondering whether generative AI can ever really become profitable. Patience is starting to wear thin 18 months after the launch of OpenAI’s ChatGPT, considered the watershed moment for the AI industry.

During Microsoft’s earnings call a few weeks ago, Morgan Stanley analyst Keith Weiss said that “right now, there’s an industry debate raging around the (capital expenditure) requirements around generative AI.” Translation: Companies are spending billions on AI infrastructure, including GPUs and cloud, to power the generative AI revolution. But soon enough, their CEOs and boards will expect proof showing their investments are worthwhile.

Nvidia’s upcoming earnings results may indeed fuel more excitement about AI. But it may take several more years before the supersize investment in developing a true generative AI killer app finally produces one.