It’s clear that tech minds are working on ways to apply AI to a host of verticals. At Y Combinator’s first day of showing off its Summer 2023 cohort, there were enough companies preparing to use AI in a medical context that we started keeping an internal running tally.
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The focus makes sense; modern AI tools, especially LLMs and all things generative AI, have the potential to make today’s workers faster, perhaps even replacing labor inputs in a number of roles. For companies looking to squeeze their costs while still growing, the ability to use more software to do work that is done by hand today is no small promise.
Startups are not alone. Public tech companies of all sizes are hammering away on the same problem set, albeit from a perch that is already stuffed with existing customer accounts.
Demand is seemingly present. Reading through earnings calls from UiPath (robotic process automation with a growing AI footprint) and C3.AI from this week makes it plain that companies see a lot of enthusiasm from the customer side of the fence.
What keeps hitting me as almost weird is that when we look at growth projections from tech shops with a big AI story to tell, the numbers feel a little modest. Happily, the two recently public tech companies — UiPath went public in April 2021; C3 in December 2020 — provided a bit of context on the growth question that helps make the demand-supply-revenue picture a little bit clearer.
Heading into Q3 2023 earnings, we had our gaze fixed on potential AI results, leading us to ask whether AI-related revenues could help companies reverse net-retention slippage. We also looked at how some tech companies are charging for AI products today, even if a data deficit will wind up making it harder for startups to win the AI race. Let’s extend our investigation by looking at how some AI-forward tech companies on the public markets are forecasting growth and talking about demand as it stands today.
UiPath and C3.ai
Following their earnings reports on Wednesday, shares of UiPath are up 7% as of the time of writing, while shares of C3 are off around 16%. UiPath beat street expectations and announced a $500 million share-buyback effort. (With $102 million worth of share-based compensation in its most recent quarter, that’s five quarters’ worth of antidilution planned, in other words). C3 failed to excite investors as much, forecasting larger losses ahead of itself.
Looking at the diverging investor reactions to the twin earnings reports, you might presume that when it comes to their AI stories, UiPath greatly outclasses what C3 has on tap. But that might not be the right perspective to take.
UiPath announced Project Wingman earlier this year with the goal of helping customers build “automations from simple natural language prompts.” That’s not a small deal for a company that has automation in its core product category (RPA).
During its earnings call, an analyst asked UiPath, “How do you expect to articulate [AI] success monetarily? Do you think in a couple of quarters or a year you’re going to be able to specifically call out the actual tailwind or benefit to growth from [generative] AI?”
Co-CEO Rob Enslin’s response included the following (transcript):
We’ll continue to look at how we benefit from [generative] AI. And I believe we are already showcasing how it’s impacting our results as part of our strategy, and I think that’ll continue. . . . And honestly, when you look at communication mining, document understanding, and what we’re doing in that space, these are game changers for customers in the value they receive. And [that is] what we’ll showcase in terms of the return that we will get in the next quarters and the next years.
UiPath expects the value of generative AI tooling inside of its service to be large, if offset to the future. That’s similar to what we’ve heard from a few other companies. And it feels a little conservative. Given what companies love to tell us about customer interest — UiPath cited “strong demand from customers” regarding its Wingman product earlier in the same call — you have to wonder when the numbers are really going to show up.
C3’s own earnings call helps unpack that point. An analyst asked the following (transcript):
First, on the guidance, and I appreciate this pivot you guys are trying to take advantage of this opportunity where it really feels like the gen AI is — has come online big, right? I think my question is more around the guidance, if you will. And where I’m going with this is given the increase that we’re talking to in the go-to-market investments, which is obviously acting as a drag on your operating losses, no question about it. But why aren’t we seeing some sort of benefit when looking at the fiscal ’24 revenues? Why maintain that guidance as we sit here today?
Which I believe we can translate to: “Hey, you guys are spending more on go to market due to what you consider to be a big opportunity in generative AI, so where’s the revenue growth from all that spend?” Here’s how CEO Tom Siebel answered:
I think we’ve been — we’re doing the best we could do since we’ve been a public company to be credible in setting expectations, and we have met or exceeded expectations in every quarter that we’ve been a public company. OK. Now, we are in uncharted territory still with a consumption pricing model, and we’re definitely in uncharted territory with generative AI. OK? [If] I were to take the sum of all the spreadsheets of all my product groups and their business plans [you] can be sure that they come up to a larger number than we’ve talked about in guidance, OK? But our position is . . . we’re comfortable with the guidance that’s out there today.
[We] feel comfortable that after a couple of quarters of acceleration, we’re going to be able to look you straight in the eye and say [that] we’re planning on significantly accelerated growth. But I don’t want to do it prematurely. I don’t want to lose credibility. And I think this is the responsible thing to do.
That’s pretty clear and helpful. Microsoft, to pick another example, talked to its investors about how the rollout for AI-powered versions of Office will take a few quarters. The demand looks like it is there in early releases, but it’s still a ways out. And modeling the future is never a precise science.
The same vibe fits here: C3 is seeing demand that could blossom into lots of revenue but is trying to avoid overpromising and underdelivering. Public companies are often conservative in their guidance so that they do not misguide Wall Street; the concept of being a little tentative with future revenues from new products or recently expanded demand is reasonable.
What was more surprising in the wake of the C3 report was investor reaction. I presumed that investors in the company, which has a heavy AI focus, would be a bit more content with it investing more in scaling its AI products suite, which it recently expanded to include more generative AI tools. Spend more now, get more revenue later. For a company with around three-quarters of a billion dollars in cash and equivalents, rising short-term losses in the name of long-term growth seems like the right bet to make.
From that perspective, C3 is effectively telling investors with its spend that it anticipates lots of future growth amid a hot market for AI products more generally. Commentary on C3’s earnings, however, has focused on its greater-than-anticipated losses. Reversing the question, would it be better for the company to not spend more now? I wonder.
It seems that companies are confident in AI demand and are even spending in some cases to capture market share. It’s just that revenue acceleration seems to be, still, a few quarters out. Here’s hoping that startups in the AI race are seeing more rapid monetization, as their investors are even less patient than the public markets.
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