AI is not to blame for labor market woes (yet)
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Companies are adopting artificial intelligence faster than expected, and producing productivity gains rather than layoffs, Goldman Sachs says.
Why it matters: Research is piling up that indicates that AI is not the culprit for the current weakness in the labor market.
What they're saying: There is a "clear skew for companies using AI to drive productivity and revenue as opposed to cut costs," Joseph Briggs, a senior global economist at Goldman Sachs, tells Axios.
- An internal survey of 100 Goldman Sachs investment bankers on how their clients use AI shows the technology is not taking jobs just yet.
By the numbers: 37% of companies are already using AI, higher than the Census Bureau's 10% estimate, according to the Wall Street firm's analysis.
- 11% of the companies surveyed are using AI to reduce headcount, while 47% said they are using AI to boost revenue and fuel productivity gains.
Threat level: Any job losses from AI are expected to come as a slow drip over the next decade.
- Tech-driven disruption fades within a couple of years, Briggs says, with about a 0.5 percentage point bump in employment within a given year.
- Over the course of the AI transition, Goldman estimates 6% to 7% of workers displaced by the technology over the course of a decade.
- "That seems like a relatively benign labor market outcome, and probably not large enough to lead to a significant reduction in aggregate demand," Briggs says.
Zoom in: The technology and information services industries are at 63% adoption and expected to reach 90% adoption within three years.
- Financial institutions are now the second-largest adopters of AI, with more than 80% adoption expected over the next three years.
The bottom line: AI will shake up the labor market, but not shatter it.
- "These type of things can't happen overnight," Briggs says.
- To "unlock the efficiency gains" associated with AI, significant work will need to be done by companies in rethinking their business, he says.
- That requires executives to have a strong understanding of how much the technology costs to put into effect and what jobs it can potentially replace.
