Is AI Delivering Real Value to Tech Investors? The Truth Behind the Hype

As traders and investors, we thrive on trends, but do we have our eyes on the right ball when it comes to AI? The recent analysis by Jeffrey Funk and Gary Smith sheds light on the often unfulfilled promises of artificial intelligence and how they’re impacting tech investments. The question we must ask ourselves: Are AI advancements translating into real revenue and productivity, or are we witnessing a classic case of hype over substance?

The Reality Check on AI Projections

Let’s get straight to the point—AI has been heralded as the game-changer of our age. Bill Gates and others foresee a future where AI will eclipse the need for many professions. However, we have to consider the Solow paradox – “you can see the computer age everywhere but in the productivity figures.” In essence, though we’re inundated with AI technologies, actual productivity gains and meaningful revenue still seem miles away.

Back in the glory days of computers, we saw a steady stream of revenue growth before productivity improvements kicked in. The trajectory for AI, however, is still murky. Prominent industry insiders predict it may take decades before we experience tangible productivity benefits. While this sounds disheartening, it’s also a crucial insight for us as trend-following traders.

Promises vs. Performance

Look at the high-profile AI cases: IBM’s Watson was once touted as a revolutionary tool for cancer treatment. Fast forward a few years, and after a significant investment, the results were so lackluster that MD Anderson Cancer Center pulled the plug. This raises a vital point – how many more ‘next big things’ are out there waiting to underdeliver?

Historically, experts have declared AI’s dominance just out of reach. Geoffrey Hinton’s ominous warnings about rendering radiologists obsolete have proven premature as the profession has only grown in the U.S. This cyclical pattern of prediction followed by reality check is putting us traders at risk if we act too hastily based on aspirations alone.

The Profitability Bottleneck of LLMs

Let’s talk numbers. AI’s large language models (LLMs) have shown they can perform a range of tasks such as drafting simple messages or developing constrained coding problems. Still, generating profits remains an elusive goal. Why? It boils down to their inability to provide reliable results, especially in high-stakes domains like healthcare or legal advice. Mistakes come at substantial costs, which makes businesses hesitant to fully embrace AI solutions.

Even Microsoft’s CEO Satya Nadella admitted that the current supply of AI capabilities far exceeds demand. The AI hype is rampant, yet confidence in actual delivery remains shaky, evidenced by recent corporate decisions to halt large capital projects connected to AI—certainly a red flag

Dollars-and-Cents AI Investment

But how much are companies truly investing in AI? Due to a lack of transparent revenue data, this question is challenging to answer definitively. As it stands, AI revenues among major players hover around $30 to $35 billion annually—a far cry from the bustling figures that the market seems to expect. As traders, we need to analyze whether these revenue figures can justify the staggering investments in data centers that are projected to reach $270 billion this year. The odds don’t seem to stack up favorably.

Looking to the Tech Titans

Even tech giants like Microsoft, Google, and AWS report mixed results in their AI segments. Google’s surge in cloud revenue—largely due to existing services—adds a layer of complexity rather than clarity, indicating that AI is just another feather in the cap rather than a core revenue driver. Microsoft’s rough estimates show possible AI cloud revenues of $10 billion in 2024, but it’s unclear how much of that is focused directly on profits.

What does this mean for us as traders? It signals that the big players might weather any downturn in AI expectations thanks to diversified portfolios, but smaller firms lack that cushion, making them vulnerable.

Implications for Traders on Trend

The market is ripe for sentiment shifts. If predictions of AI profits continue to lag behind reality, we may see a pullback reminiscent of the dot-com bubble. Investors will eventually tire of the same bleak forecast, and that bubble will burst faster than you can say “generative AI.”

As savvy traders, we need to keep our ears to the ground, monitor sector sentiment, and make strategic choices based on hard data rather than dreams. Look for signals that indicate a pivot in market perceptions about AI—be it revenue growth, enterprise adoption, or changes in investor sentiment. Timing is everything, and in a landscape filled with hyperbole, clarity is our greatest ally.

In summary, while the AI revolution may one day take hold, tread cautiously. The profits aren’t here yet, and it’s the prudent investor who keeps a skeptical eye on the hype machine.