I am an author, independent researcher and speaker exploring innovation, information technology trends and markets. I served as co-chair of the 2023 AI Summit in New York, as well as the 2021 and 2022 Summits. I regularly contribute to Harvard Business Review on AI topics.
Lately, there has been pushback against the notion that artificial intelligence — particularly generative AI — is the game-changing, life-changing, world-changing technology it was promoted to be. Consider the contrast with the industry chatter following the first launch of ChatGPT in late 2022 — that it was the most profound thing since the harnessing of fire, or the splitting of the atom. Now, reality is setting in, and expectations are leveling.
The economics of AI versus earlier technological breakthroughs are questionable, observes Jim Covello, head of global equity research at Goldman Sachs. “Even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions,” he says. “AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.
Building an AI-based infrastructure will be greater than $1 trillion dollars over the next several years — data centers, utilities, and applications, Covello observes. “What $1 trillion problem will AI solve?” he asks. “Replacing low-wage jobs with tremendously costly technology is basically the polar opposite of the prior technology transitions I’ve witnessed in my thirty years of closely following the tech industry,” he adds.Biden Vs.
And there’s more — likely a lot more. Many productivity assumptions are based on the notion “that the primary driver of cost savings will be workers completing existing tasks more efficiently and ignores productivity gains from labor reallocation or the creation of new tasks,” Briggs continues.
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