A survey of 16 economists by The Wall Street Journal, published June 10, found that while nearly all expect artificial intelligence to boost productivity in the near term, opinions diverge sharply on whether the technology will ultimately eliminate more jobs than it creates. The group included a Nobel laureate, academics focused on AI economics, and former top government advisers.
Only a couple of the economists surveyed said they expect the productivity gains to translate into net job growth over the next five years, according to the Journal’s report. Most respondents agreed that AI will increase productivity, but they split on the question likely to worry many Americans: whether AI will eliminate more jobs than it adds.
One economist described the current moment as the “Between Times,” in which the potential of AI is visible but organizational systems have not yet fully adjusted. “Over the next five to 10 years, at least one leading company in each market will likely figure out how to transition to a system solution that is much more productive,” the economist said. Another said the labor impact “will shift from doing things faster to doing different things, requiring a significant reorganization of human roles.”
Several economists pointed to historical precedents to warn that AI could deepen inequality. “There is a lot of evidence suggesting that those workers will lose out and inequality will increase,” one economist said, noting that both imports from China and robot adoption had “fairly negative displacement effects that were long-lasting” because they were sudden and concentrated in local labor markets. Another economist said the Industrial Revolution left average real wages stagnating for four decades, and that “I see no reason to believe that the AI revolution will be different.”
“If it works out well, we will be vastly more productive and hence potentially wealthier,” one economist said. “But whether those gains are broadly shared, and whether the workers whose careers are destroyed make successful transitions, these things do not depend on the technology. They depend on the societal institutions and policies we build to share the gains and redress the costs. The United States does not have a glorious history of doing either. We are currently unprepared, and most signs from Washington and Silicon Valley say: let it rip and damn the consequences.”
The economists offered diverging views on which workers are most at risk. One said experienced workers in routine information-processing roles—adjusting insurance claims, translating documents, writing standard ad copy—face “genuine displacement risk.” Another said the technology is “coming squarely at white-collar workers,” adding, “I now know what blue-collar workers felt like in the 1970s.” However, some economists said AI could benefit entry-level workers by compressing the learning curve, allowing less-experienced people to perform at higher levels sooner.
On the question of which sectors would win and lose, economists identified healthcare, education and finance as likely beneficiaries. “The most important and neglected aspect of AI’s value is in how much it will enhance health and longevity through the healthcare industry,” one economist said, pointing to AI applications in developing new treatments and improving diagnosis. Sectors at risk include legal, real estate and administrative services that rely on routine cognitive labor, where the cost of prediction is expected to drop toward zero.
The economists also pointed to offshoring as the first industry to be hit. “Firms that offshore coding, call centers, payroll and other repetitive tasks to India, Philippines etc are already seeing large drops in demand,” one economist said, predicting that offshore service economies would be most directly affected.
When asked what workers should do to prepare, the economists were largely unanimous in recommending AI literacy and the development of judgment skills. “Stop training to be a prediction machine,” one economist said. “If you are learning something a machine can learn from historical data, your skill is being commodified. Instead, focus on judgment skills and AI literacy.” Another said the most productive workers will be those with the judgment to know which AI output to trust and how to integrate it into a broader system. “You want to be the person who decides what to do, not the one who executes it.”
A Nobel-winning economist advised young students to “choose a field they have genuine passion for” and combine that with a willingness to “tinker, experiment and get your hands dirty with AI in your own domain.” Another said simply: “Learn how to use AI for any task you are given. That is the only way at the moment to learn how to work with AI and take advantage of it.”
One economist, reflecting on the uncertainty of the trajectory, said, “I don’t think we’ve ever really seen anything moving with this scale and speed before. It’s going to be a wild ride!!”