{"id":674620,"date":"2026-05-30T19:08:09","date_gmt":"2026-05-30T19:08:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/674620\/"},"modified":"2026-05-30T19:08:09","modified_gmt":"2026-05-30T19:08:09","slug":"a-i-doesnt-have-to-mean-layoffs","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/674620\/","title":{"rendered":"A.I. Doesn\u2019t Have to Mean Layoffs"},"content":{"rendered":"

For many chief executives, success in adopting artificial intelligence is measured by the number of jobs they can eliminate. In just the past few weeks, companies have announced tens of thousands of layoffs they attributed to A.I., a wave that one global bank boss undiplomatically described<\/a> as replacing \u201clower-value human capital\u201d with technology.<\/p>\n

But such views reflect \u201ca very narrow understanding\u201d of A.I.\u2019s potential, said Erik Brynjolfsson, who directs the Digital Economy Lab<\/a> at Stanford University. \u201cA lot of people are under the mistaken idea that the only way that you get productivity from A.I. is by removing labor costs.\u201d<\/p>\n

Mr. Brynjolfsson is one of a group of economists who argue that businesses can reap bigger gains by using artificial intelligence to make workers more productive rather than replace them.<\/p>\n

It\u2019s a message that Schneider Electric, a global energy technology company based in France, has taken to heart. Schneider, which has a work force of nearly 160,000 worldwide, is embracing artificial intelligence across the company.<\/p>\n

It started by identifying \u201cwhere our people are either losing time doing repetitive tasks, doing tedious tasks, doing things which fundamentally are not the right ones to do,\u201d said Philippe Rambach, the company\u2019s chief artificial intelligence officer.<\/p>\n

In other words, the work that gets in the way of work.<\/p>\n

Using A.I. in Call Centers<\/p>\n

Call centers were an obvious case for Schneider. Anyone who has languished in the labyrinth of automated phone assistance may groan at the prospect of additional technological tinkering. But Mr. Rambach said the goal was to use the technology to get answers to customers faster.<\/p>\n

Before the company started using A.I., customer service agents received thousands of questions from callers and engaged in a grand hunt through millions of pages of information to track down the answer, Mr. Rambach said. \u201cGuess what?\u201d he said. \u201cOur customers were not super happy with the quality of the answer and not super happy with the speed of the answer.\u201d<\/p>\n

Now A.I. does the hunting and details how the information was selected and the source. The agent then reviews and if necessary, modifies and refines the answer with the caller.<\/p>\n

In the last three months of 2025, call centers fielded 150,000 questions. Three-quarters of the time, A.I. was able to provide the right answer to straightforward questions, such as, \u201cWhy isn\u2019t a newly connected energy monitor showing consumption levels?\u201d In these cases, the agents used the A.I. generated response. The rest of the time, agents worked with callers on more complex problems, including helping building managers with identifying the root cause of energy alerts.<\/p>\n

Response times were quicker and employees have been much happier, Mr. Rambach said, because the time they saved on searching databases to answer common questions left them more time to work with customers.<\/p>\n

Other companies have registered productivity gains for their workers. A study<\/a> conducted by Mr. Brynjolfsson with two other researchers, Lindsey Raymond and Danielle Li, on more than 5,000 customer support agents at a Fortune 500 firm found that A.I. assistance allowed workers, on average, to resolve 15 percent more problems, with less experienced and lower-skilled workers improving most in terms of speed and quality.<\/p>\n

At the same time, they found that callers were more polite and less likely to utter the phrase every customer service agent has come to dread: \u201cI want to speak to a manager.\u201d<\/p>\n

A.I. on the Factory Floor<\/p>\n

At an upgraded factory in Le Vaudreuil, about 60 miles north of Paris in Normandy, Schneider is using artificial intelligence to manage complex industrial processes at a decades-old site that had already been upgraded with robotic and digital tools \u2014 some with a French accent.<\/p>\n

The automated guided vehicles, or A.G.V.s, that glide around the factory floor delivering parts, for instance, are named \u00c9mile and Victor after great French writers like Zola and Hugo.<\/p>\n

Artificial intelligence is not needed everywhere, said Virginie Rigaudeau, a project leader at Schneider. \u201cWe use A.I. only when we know it delivers added value.\u201d<\/p>\n

Like in the production of the 74 million silver tips that the factory produces each year to manufacture electrical contactors \u2014 the switches that are used for turning electrical circuits on and off in elevators, motors, electric vehicles, heating systems, lighting banks and more.<\/p>\n

The recipe for cooking up the tips includes silver nitrate and sodium. The mixture is whirled in a centrifuge and the resulting silver paste is then repeatedly washed in large steel-gray tanks to rinse out excess sodium.<\/p>\n

But knowing how many washing cycles were enough was always something of a guessing game, Ms. Rigaudeau said.<\/p>\n

With A.I., operators can see a visual representation and learn the precise amount of sodium that remains after each rinsing cycle.<\/p>\n

\u201cNow the system tells us when to stop washing, and we immediately know whether the powder meets quality standards,\u201d an operator said.<\/p>\n

The savings have been enormous, Ms. Rigaudeau said. In one year, the company reduced waste from the process by 73 percent, and water use has been cut drastically.<\/p>\n

Samples from every batch no longer need to be sent to an off-site lab for testing, a process that could take between 24 and 48 hours. That has saved thousands of euros in lab costs, while decreasing gasoline consumption \u2014 from trucks that used to ferry samples to and from the lab \u2014 by 22 percent.<\/p>\n

Cameras enhanced with artificial intelligence are also used to assess the quality of finished contactors within seconds.<\/p>\n

Making Employees Better, Not Redundant<\/p>\n

In some European countries, using artificial intelligence to make workers more productive \u2014 and not replace them \u2014 is encouraged by strict labor laws that can make it difficult and expensive to lay off employees.<\/p>\n

In the United States, said Mr. Brynolfsson at Stanford, government policies often encourage companies to invest in capital and cut workers. He pointed to the tax code.<\/p>\n

\u201cIf you\u2019re starting a new venture, and you have a lot of labor, you\u2019re going to have to pay more taxes,\u201d Mr. Brynolfsson said. \u201cIf you only invest in capital, then you pay less taxes.\u201d<\/p>\n

Of course, forecasts about the impact of artificial intelligence on the job market encompass a multiverse of possibilities. And while many economists agree that policymakers and businesses have choices about how A.I. is deployed, some wonder if those options are narrowing.<\/p>\n

It\u2019s \u201cvery unpredictable,\u201d said Anton Korinek, who helped lead the Economics of Transformative A.I.<\/a> project at the University of Virginia. Artificial intelligence \u201cwill create and destroy jobs and it\u2019s not clear which will be more predominant,\u201d he said.<\/p>\n

Mr. Korinek said he started studying how to develop A.I. as a tool for helping the labor force more than 15 years ago, but the spectacular advances have made him more doubtful about society\u2019s ability to steer how it is developed and used. \u201cYou can\u2019t pick the direction in which it\u2019s going as easily anymore,\u201d he said.<\/p>\n

At some point, he said, A.I. will be \u201cso much more productive and cheaper than humans.\u201d (Mr. Korinek, who recently joined the economics research team at Anthropic Institute,<\/a> the research arm of the A.I. company, made his comments before taking his new position.)<\/p>\n

The built-in dilemma is evident even at Schneider, a company that has found ways to use A.I. to complement employees\u2019 work.<\/p>\n

Sandra Ferraguti, the plant general manager in Le Vaudreuil, showcased a new plug-and-play contactor that Schneider\u2019s A.I.-assisted work force developed and that no longer requires an electrician to do the wiring.<\/p>\n

\u201cNow a robot can install it,\u201d Mr. Ferraguti said. \u201cYou don\u2019t need a human.\u201d<\/p>\n

\"\"\/<\/p>\n

Patricia Cohen<\/p>\n

Economics reporter<\/p>\n

The news about layoffs related to artificial intelligence has been pretty disheartening lately. Several economists I had been talking to, though, have emphasized that we have choices about how A.I. is used and developed; that it doesn’t have to be configured to replace workers. As Erik Brynjolfsson, the Stanford economist, put it: People are asking what will A.I. do to labor. \u201c I think that’s kind of backwards,” he said. “It’s what do we want to do with A.I.\u201dI asked around for some examples, and Schneider Electric was mentioned as a company that was taking an approach that sought to augment its workers with A.I. rather than replace them. One interesting question is whether business and policymakers are doing enough to direct A.I. development in ways that can bolster workers. What do you think?<\/p>\n

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