There was a lot of information to take away from Nvidia’s (NVDA) earnings call on August 28. The much-anticipated Blackwell chip is ramping up production in Q4, and the firm expects it to generate “several billion dollars” of revenue from it in the quarter; the firm beat on both the top and bottom lines (revenue of $30 billion exceeded expectations of $28.86 billion; EPS of $0.68 beat expectations of $0.64); and management offered solid guidance for the rest of the year, although that fell short of Wall Street’s lofty expectations.
But one important question came up among the buy-side analysts in the Q&A portion at the end of the call: What’s the AI ROI?
In other words, what kind of return on investment are your AI-focused customers generating?
It’s a valid and increasingly important question now that artificial intelligence fervor is reaching the two-year mark.
That said, asking Nvidia how much money their customers earn from AI initiatives is a bit unfair to the company. It’s like asking Microsoft how much money their customers earn using Microsoft Office.
But the reason it’s worth discussing is that the ROI on artificial intelligence is arguably the biggest question on Wall Street.
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Mega-cap tech companies have been quite vocal about their spending plans on AI data center infrastructure, with Meta (META) indicating it could spend as much as $40 billion this year and Microsoft (MSFT) spending $69 billion on CapEx (capital expenditures) in its latest full fiscal year.
At the same time, the ROI question prompted a research note in June from Goldman Sachs called “Gen AI: Too Much Spend, Too Little Benefit?” in which researchers question whether what could be a trillion dollars of spending in the coming years will pay dividends.
On the call, Nvidia CEO Jensen Huang highlighted the significant cost savings from “accelerated computing” as providing an immediate return on investment; he also alluded to potential revenue generation from any number of AI-focused start-ups who would presumably rent computing power from the data centers that are built on Nvidia chips.
Why Does ROI on AI Matter?
Data centers and high-end chips are expensive, and while big tech companies have been shoveling cash towards building them out, at some point their shareholders will need to see a concrete justification for those expenditures.
Sixty-nine billion dollars is not an insignificant amount of money, even for a company like Microsoft, and a return on investment that not only recoups those expenses but provides further room for growth is the finish line.
As it stands, Microsoft lumps all of its cloud revenues together, so there’s no definitive breakdown that shows revenue growth from AI initiatives versus, say, revenue growth from Azure web services.
For the last two years, big tech has been spending money on the promise of what AI can deliver for shareholders, but thus far their spending has really only benefited companies like Nvidia and OpenAI (which is privately held and likely not generating any revenue for itself at this stage; the nature of Microsoft’s investment appears to hinge on cloud computing credit more than actual funds changing hands).
If AI does not successfully monetize, there’s little to differentiate it (as far as investors are concerned) from other much-hyped money-burning tech products like VR (virtual reality) or the Metaverse.
So, what should we be watching for?
Shout-outs in big tech’s earnings calls. If the mega-cap tech companies begin highlighting the additional revenue they’re generating from spending on AI, that’s the ultimate green light. That means they’re now monetizing their initial investment. After that, the pertinent question becomes whether they spent too much rather than should they have been spending at all.
Startup funding. If we start seeing headlines about record fundraising for AI companies, that investment is likely to flow through to the big tech companies. It’s not quite the same green light, but it’s significant progress.
Earnings further down the food chain. “AI” isn’t the magic word on earnings calls the way it used to be, but if companies further down the food chain are referencing new sales wins, significant cost savings, or new products powered by AI, we can presume that those investments support further spending by big tech.
What about red flags?
Most companies won’t come out and admit that they overinvested in some new growth arena (see the Metaverse), but what they will do is go quiet.
You’ll hear less emphasis on large language models (LLMs), generative AI, and AI agents in calls.
Unfortunately, we got a taste of that in Nvidia’s earnings last night when management was quick to highlight their gains in accelerated computing (managing/accessing data faster) but was a little quieter on AI growth prospects.
The most important takeaway is that investment banks are already asking about the ROI on AI, and now buy-side analysts have started too. Without meaningful progress in the next quarter or two, the big risk is that shareholders (especially large institutional investors) will begin to doubt the promise of AI and start slowing their investments into even the picks and shovels companies like Nvidia.
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