In studying the impact of AI on phone jockeys at a Fortune 500 company’s customer service call-in center, researchers from Stanford University and the Massachusetts Institute of Technology found that newer workers benefited the most.

The AI had pooled the tips, tricks, and expertise of more experienced workers. 

Because the AI could guide newbies through situations that needed more expertise than reading from a script, workers who had been on the job for two months were showing the same level of expertise and productivity as colleagues who had been in place for six months.

“In contrast to studies of prior waves of computerization, we find that these gains accrue disproportionately to less-experienced and lower-skill workers,” the research team wrote in a published paper. 

“This occurs because [machine learning] systems work by capturing and disseminating the patterns of behavior that characterize the most productive agents. Agents with two months of tenure” who use the AI tool “perform just as well as agents [without it] who have over six months of tenure.”

Productivity across the center’s entire workforce jumped 14 percent after AI was installed.

TRENDPOST: AI and machine learning will eliminate the problem of companies losing know-how or expertise when long-time workers quit or retire. That knowledge will be contained within AI and grow over time.

Financial houses have been at it for a while, adding the market savvy and experience of senior traders to AI. When those traders leave or retire, their knowledge stays in the company to be used by younger workers who achieve the same results, not by putting in years to gain practical knowledge but just by having better tech.

According to Business Insider, Wall Street has even coined a term for it: juniorization.

AI has the potential to eventually decimate the mid-career and older workforce, leaving a handful of humans to manage special projects and situations while AI handles day-to-day tasks and decisions.

Whether that potential is realized depends on companies, regulators, and employers.

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