A new study suggests the potential of generative artificial intelligence (AI) to increase workplace productivity.
The study — conducted by researchers at Stanford University and MIT — found that customer service workers at a software firm who had access to generative AI tools were 14% more productive than those who worked without them.
The findings come amid a steady stream of announcements by companies planning to integrate AI into their offerings.
According to a report Monday (April 24) by Bloomberg News, the study is the first to measure the effect of generative AI on the workplace outside of a laboratory.
“Having people use it for over a year in this company, you get a much better sense of how that translates into real-world productivity,” Erik Brynjolfsson, one of the study’s co-authors, told Bloomberg. “As far as I know, this is the first time it’s been done in a real-world setting.”
The researchers monitored a group of 5,000 customer support agents, some of whom had access to AI tools that were trained using successful customer service conservations and some with no AI access.
Among the findings in the study was that the company’s least-skilled workers saw the most benefit from AI, getting their work done 35% faster. These novice employees were also able to improve their work performance faster with AI.
The findings also fly in the face of the conventional wisdom that lower-skilled workers are most hurt by automation, the report said.
The study follows a report last month by Goldman Sachs which argued that generative AI could trigger a major disruption in the labor market, impacting a quarter of jobs in Europe and the U.S.
PYMNTS looked at the potential for AI to boost productivity in the construction sector earlier this month in a conversation with Patrick Murphy, Founder and CEO at construction technology company Togal.AI.
He spoke of the way productivity in construction has remained at a standstill since the 1970s as the industry deals with a glut of information.
“There’s so much information in construction, from the actual plans, the blueprints, the spec books, all the various contracts across owners, suppliers, third parties…the list goes on and on,” Murphy said.
With this “constant friction” around surfacing relevant information in mind, he argues there’s great potential in using generative AI to “reduce friction with all the documentation” and “consolidate the thousands of pages” for every project so that humans are no longer wasting time and energy on problems that are tangential to the project.
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