Beware of the AI hangover

Artificial Intelligence (AI) related stocks have been on an absolute tear. The Magnificent Seven, which is one proxy for AI plays, has beaten the S&P 500 for six consecutive quarters. But the degree of outperformance is decelerating. This looks like the early stages of an AI hangover.

 

I believe AI stocks are overhyped short term but underhyped long term. Here’s why.
 

 

AI doubts emerge

The exuberance over AI can be exemplified by the market reaction to the earnings of two AI ecosystem stocks, Palantir (PLTR) and Cloudflare (NET), both of which reported double beats on earnings and revenue. Reports of segmented results were strong. In Palantir’s case, the company even raised guidance, but the stock fell because guidance failed to exceed the whisper numbers. In Cloudflare’s case, the market sold off because the company failed to raise guidance.
 

 

From a fundamental perspective, signs are appearing that the narrative is turning from the upside to the downside of AI adoption. The CNBC article, “AI engineers report burnout and rushed rollouts as ‘rat race’ to stay competitive hits tech industry”, tells the story of AI development for the sake of appeasing investors instead of actual productive development. The key points are:

• Artificial intelligence engineers at top tech companies told CNBC that the pressure to roll out AI tools at breakneck speed has come to define their jobs.
• They say that much of their work is assigned to appease investors rather than to solve problems for end users, and that they are often chasing OpenAI.
• Burnout is an increasingly common theme as AI workers say their employers are pursuing projects without regard for the technology’s effect on climate change, surveillance and other potential real-world harms.

At the Berkshire Hathaway annual general meeting, Warren Buffett was asked about AI, his response focused mainly on the downside of AI:

Journalist Izabella Kaminska recently raised an important question of the usefulness of future Large Language Models. Current LLMs are trained on “mainly established authors who have a substantial body of pre-published work that can provide enough learning material to ensure it emulates their intelligence faithfully”, but what happens when LLMs begin to proliferate and try to train themselves on LLM output?
 

 

Technical warnings

From a technical perspective, momentum in AI stocks is flagging. I identified 29 stocks exhibiting strong price momentum in January (see At Least 29 Reasons to be Bullish), most of which were technology stocks. Most, like this chart of NVIDIA, are either consolidating sideways or pulled back like Palantir and Cloudflare.
 

 

By contrast, market leadership has shifted to cyclical names, like Costco, which broke out of a multi-year base and rallied to fresh highs.
 

 

The homebuilding stocks are exhibiting a similar pattern of market strength.
 

 

GE, which is an important cyclically sensitive industrial stock, has been on an absolute tear.
 

 

In other words, leadership has shifted from AI-related technology to value and cyclical stocks. But from a long-term perspective, the AI bull isn’t over. Here is the percentage of NASDAQ 100 stocks bullish on point and figure, which recently bottomed out at below 25% and rebounded. In the last 10 years, such episodes have always seen the NASDAQ 100 stage a relief rally. However, the initial rally was often fleeting and followed by a lower low.
 

 

Another source of warning of near-term NASDAQ weakness can be found in the relative volume of NASDAQ/NYSE volume, which is weakening.
 

Be patient

Even though AI stocks appear to be overhyped in the short run and prone to a hangover, investors are advised to be patient on the long-term potential of AI. A St. Louis Fed study compared the pace of AI adoption to other technologies. It concluded that “early evidence on the diffusion of AI seems to suggest a pattern similar to those of personal computers and cloud computing”. In other words, it will be a long cycle. Investors need to be patient about the pace of AI benefits.
 

 

In conclusion, I believe AI is overhyped in the short run and underhyped in the long run. Recent instances of earnings report reactions of stocks in the AI ecosystem indicate excessive frothiness and even AI bellwethers like NVDIA have begun to consolidate sideways. A St. Louis Fed study of the pace of technology adoption suggests that AI adoption will undergo a long cycle like the PC, so investors need to be patient.

Investors who want to monitor the turn may want to keep an eye on the semiconductor stocks as AI proxies. These stocks are correcting and consolidating sideways after breaching a rising trend line. Upside absolute and relative breakouts of resistance will define the re-emergence of the AI bull.