With mounting evidence of a slowdown in the US and increasing financial market volatility, investors face a critical decision: chase the allure of high-flying AI stocks or opt for the stability of companies with predictable earnings.
While the so-called AI-dominated "Magnificent 7" mega-cap stocks have dominated headlines and captured imaginations, Levantine & Co-Managing Partner Attila Kadikoy believes there's a compelling case to be made for investing in businesses with more reliable financial performance.
The looming economic slowdown
In a market where more and more indicators suggest that markets are heading into a period of deceleration, Kadikoy says this environment favours companies with predictable earnings because these business models are more resilient to downturns and offer products or services with inelastic pricing.
He says traditional valuation metrics, such as dependable forward earnings, become more important in a slowing economy, allowing investors to clearly identify fundamentally attractive opportunities.
Recent data supports this cautious outlook. The OECD's Leading Indicator for G7 countries and the ISM Manufacturing PMI show signs of weakness, with cyclical sectors weighing on overall earnings growth for the S&P 500. The Richmond Manufacturing Survey has also recently displayed a level of weakness rarely seen outside of a recession.
The AI hype cycle
Kadikoy notes that the current frenzy surrounding AI is reminiscent of past market bubbles, including the emerging market, dot.com, crypto and remote working technology during Covid bubbles.
Zoom is a good example: its share price rose to over $550 in 2020/21, and now it trades at around $75. This significant decline in the share price of a former market favourite is a reminder of the risk of valuing companies based on short-term sentiment rather than investment fundamentals.
Over the past year, AI-driven companies, particularly the "Magnificent 7," have seen their shares trade at astronomical valuation multiples, pricing in ambitious growth forecasts. However, these companies' earnings remain unpredictable.
A Goldman Sachs report, “Gen AI: too much spend, too little benefit?” forecasts that tech giants and other companies will spend around $1 trillion on AI-related capital expenditures in the coming years. This includes significant investments in data centres, chips, and other AI infrastructure. Yet, as the report notes, "this spending has little to show for it so far."
The AI sector appears to be following the classic Gartner hype cycle when a new technology comes to market. In a recent report, the American tech research firm explains the different phases of the hype cycle: “After the early “peak of inflated expectations” comes a “trough of disillusionment,” followed by a “slope of enlightenment,” which eventually reaches a “plateau of productivity. “
It views most generative AI technologies as either at the peak of inflated expectations or still going upward, suggesting that most of these technologies are two to five years away from becoming fully productive.
The perils of long-term forecasting
Predicting market dynamics and company performance decades into the future is a fool's errand, particularly when, as a RAND Corporation study highlights, 80% of AI projects fail, more than double the rate for non-AI projects.
Kadikoy says that AI-driven companies will experience unexpected rivalries and disruptive innovations over the next decade. A case in point is Tesla, initially considered the leader in electric vehicles but now faces fierce competition from established automakers and Chinese electric vehicle manufacturers.
He notes that recent earnings reports from major tech companies have already shown signs of strain. Tesla's shares fell after earnings showed slowing profitability and delays in AI-related projects. Alphabet investors weren’t happy with the company’s $13 billion quarterly investment in AI investments because this has yet to translate into substantial revenue growth.
Consumer priorities and market fundamentals
Another fundamental challenge AI companies are likely to face is many consumers prioritise utility and affordability over cutting-edge features, says Kadikoy. “While some consumers want state-of-the-art products, most seek products that meet their needs efficiently and cost-effectively.” This preference for "good enough" technology could limit the addressable market for premium, AI-driven products and services.
In addition, the market's enthusiasm for AI may not reflect actual consumer adoption. Sequoia Capital questions how much of the market enthusiasm for AI will translate into consumer adoption: "Outside of ChatGPT, how many AI products are consumers really using today?" The venture capital firm believes AI companies will need to deliver significant value for consumers “if you consider how much value they get from Netflix for $15.49/month or Spotify for $11.99.” says Kadikoy.
The bottom line
Instead of trying to predict which AI companies will dominate decades from now, Kadikoy argues for a more prudent investment approach that focuses on businesses with proven track records of generating consistent earnings. “These companies may lack the excitement of their tech-focused counterparts, but they offer a compelling combination of stability, predictability, and long-term value creation,” concludes Kadikoy.
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