Stock Picks in Tech – Five Niche Leaders with Long Runways of Growth
Five stock pitches
Introduction – AI Demand is Exploding
In just 16 months, Anthropic has now scaled from $1 billion in ARR to a $30 billion run rate. Anthropic is making these kinds of revenues in a world that’s still far short on AI compute and where enterprises can also deploy free open source models on their own GPUs.
So, the key bear thesis on AI capex—that AI isn’t making sufficient revenue—is quickly falling apart. Besides direct AI revenues, we already knew that AI is also generating tremendous indirect revenues by improving user feeds and ad targeting on social media. The other large opportunity is enterprise cost savings and boosting employee productivity—i.e. growing revenues on a flat or decreasing headcount. We’re only at the start of this trend, and the recent large headcount reductions by Block will likely be followed by more software companies. We estimate our own coding productivity has gone up 10-20x with Gemini and Claude, and so we would be surprised if headcounts at software companies don’t go down. However, overall hiring trends for software developers remains strong, as historically many companies and institutions simply didn’t have the required access to engineering talent.
Evercore looks at the tremendous amount of enterprise global opex at $60 trillion and the value that AI can create here. One way to think about this is if AI can save 20% in costs, the annual value of this cost saving would be $12 trillion, which dwarfs the $1 trillion in annual AI capex spend, while GPUs can power workloads for six years and more.
Another way to think about the above, if AI can make that global opex spend 2-3x more productive, the annual economic value added would be around $90 trillion. So, if AI would automate a large proportion of employees away in the knowledge economy, the economic value that this creates would allow for some sort of universal income to be paid out for those unable to find a new job. We briefly read through the Citrini piece that made a lot of headlines last month, and the scenario they outlined where large parts of the population become unemployed and a handful of players in Silicon Valley—like Jensen and Dario Amodei—would capture that economic value, we don’t see that happening. For the obvious reason that there isn’t going to be an electorate or political party that’s going to be in favor of this. Sam Altman has previously proposed to levy a tax based on market cap, e.g. 2.5% of the market cap of the S&P 500 would be remitted into a national public fund every year. Another way would be to impose a tax on every GPU compute hour, similar to the VAT in Europe.
Given the substantial economic value that AI is creating, we remain bullish on the outlook in AI both on the semiconductor side, which is heavily exposed to AI capex, as well as on the application side, which can make annually recurring revenues from AI inference. In the semi value chain, we liked the below chart from Evercore showing that ASML is most exposed of the semicap names to where that AI capex will flow—i.e. leading edge logic and DRAM:
On the other hand, we remain cautious when it comes to neoclouds. As the below analysis from Bloomberg highlights, if parts of data center construction get delayed, neoclouds will be heavily impacted as they are highly levered in order to do these data center buildouts, while revenues that bring in cash will be postponed.
Instead, we’re looking for companies with a strong market positioning—as witnessed in a dominant or strong market share in their niche—a long runway of growth, and ideally, a cheap valuation as the market is completely overlooking this opportunity. Next, we will dive further into our findings on five smaller names. We’ve invested in three of these although we’re also considering investing in the other two.