Thoughts on
$NOW and more…
$NOW reported 20% revenue growth, raised its guidance, showed impressive AI momentum, and guided to 36% free cash flow margins. Yet the stock got hammered. How does a company deliver results like that and still disappoint investors so badly? Welcome to the wonderful world of expectations.
The 2 cent earnings miss certainly doesn’t explain a selloff of this magnitude. The concern is Q4 guidance of 18.5%, down from 21% in Q3. Investors expected AI to accelerate growth, but so far, the overall business is showing signs of slowing. That’s not a disaster, but it’s a problem when expectations are high.
And expectations were certainly high. The stock had rallied 43% in 3 months and was trading at 33 times forward earnings. Consider what happens when investors decide a business deserves 26 times earnings instead of 33. The stock falls 21%, even if the earnings themselves haven’t changed.
A company can become more profitable while its stock becomes less valuable, simply because investors were expecting even better results. The market doesn’t reward businesses for being wonderful. It rewards them for being more wonderful than the price already assumes.
But the most interesting part of
$NOW’s story is AI, and investors are overlooking an important contradiction. Management raised its AI annual contract value target to more than $1.7 billion, while agentic AI consumption increased thirteenfold. Impressive numbers, but if AI is doing so well, why isn’t the entire business accelerating?
Imagine a company with 1,000 customer service employees, each requiring software licenses. AI eventually allows that company to accomplish the same work with 300 employees and hundreds of AI agents. Wonderful for the customer, but potentially terrible for the software provider collecting revenue from those employees. What happens when the technology you’re selling also reduces demand for some of your existing products?
Now consider the other side. Those AI agents still need access to databases, security permissions, applications, and workflows. Someone needs to coordinate everything, and
$NOW wants to become that platform. Perhaps it loses revenue from human users but earns considerably more from managing the work of AI agents.
Both outcomes are possible, and that’s what makes this fascinating. AI could simultaneously damage parts of
$NOW’s business while creating an even larger opportunity. The question isn’t whether AI works. It’s whether
$NOW captures more economic value from AI than it loses elsewhere.
Here’s another way to think about it. Suppose a customer saves $100 million annually using
$NOW’s AI products. How much of those savings can
$NOW capture? $5m or $20m? The technology can be revolutionary without necessarily producing revolutionary profits.
There’s also a benefit that receives far less attention. Management said more than $1 billion in efficiency gains from using AI. What if AI allows
$NOW to grow revenue without increasing expenses at the same pace? That could be just as valuable as selling additional AI products.
Imagine revenue grows 15% annually while free cash flow margins expand from 36% to 40% over say 5 years. Free cash flow would compound at over 17% annually, even though revenue growth has slowed. That’s a wonderful outcome for a business that requires relatively little additional capital. Of course, we still need to account for acquisitions, stock compensation, dilution, etc.
And this brings me to why I found
$NOW particularly attractive in the $80 range. At that price, AI didn’t need to transform the company, revenue growth to accelerate, or investors to assign it an extraordinary valuation. The business simply needed to remain good and continue generating more cash over time. The price gave room to be wrong about some things and still potentially earn an attractive return.
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