Elon Musk Shares Skepticism Through the AI Hype Elon Musk Shares Skepticism Through the AI Hype
Elon Musk recently remarked at the Milken Institute Global Conference on issues related to AI through a lens of skepticism. While... Elon Musk Shares Skepticism Through the AI Hype

Elon Musk recently remarked at the Milken Institute Global Conference on issues related to AI through a lens of skepticism. While the tech mogul is known for his ambitious ventures into space and electric vehicles, his latest observation on generative AI’s current utility—or lack thereof—for his companies like SpaceX and Starlink.

It seems that he is trying to offer a sobering counter-narrative to the prevailing AI enthusiasm seen across industries. The critique came after experimenting with AI in solving complex problems in electrochemistry and rocket design.

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His verdict? The technology is not yet up to the task. This confession is particularly striking, given it comes from a leader whose companies are at the forefront of technological innovation. “Generative AI just isn’t useful right now for some businesses I run,” Musk declared, highlighting a sentiment rarely expressed among the high-powered executives attending the conference.

This view runs a bit counter to the excitement around AI. According to reports, the implications of AI are enormous, with predictions of its impact on the global economy reaching a staggering $7.9 trillion, about 8% of worldwide GDP, according to McKinsey consultants.

Musk himself envisions a future where only 1% of knowledge will remain “biological,” indicating a massive shift toward AI dependency. This future aligns with his ongoing efforts, as Bloomberg reported Musk is nearing a $6 billion funding round for his AI startup, xAI, which aims to further develop the Grok chatbot.

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Though there is plenty of enthusiasm for AI’s capabilities, others don’t feel the same. Business leaders like Ken Griffin, founder of Citadel, noted at the same conference that when pressed about real-world AI applications, CEOs often deflect with vague references to other projects.

This echoes a pattern where companies boast of AI-driven productivity increases of 30%—a figure that, while enticing, is so uniformly cited it feels more like conventional wisdom than a substantiated metric.

Despite the impressive potential of AI, actual transformative applications remain scarce. McKinsey’s research identifies numerous theoretical use cases, yet the real-life, impactful examples are few and far between. This disconnect between potential and reality serves as a cautionary tale against the petabytes of hype surrounding AI.

The financial implications are also significant. As the International Monetary Fund notes, even in an optimistic scenario, it could take years for AI to affect 40% of worldwide jobs. The capital required for such a technological overhaul risks being misallocated, potentially straining profitability for extended periods.

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To add to this, small adjustments in demand forecasts could disproportionately impact fixed-asset valuations, illustrating the financial intricacies companies must navigate as they integrate AI technologies.

No matter the view, it is clear that AI’s predicted impact is yet to be fully realized shortly.



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