Why AI is Leaving Many Employees More Overworked and Less Productive

Good morning. For years, corporate tech leaders have been deploying AI tools inside their organizations with the hopes that it will increase employee productivity and give them more time to focus on higher-level tasks.

And in some cases, that idea has borne fruit. But for many employees, continually encountering a barrage of nascent, foreign and constantly changing tools has left them feeling overwhelmed and overworked. That’s according to new research from executive search firm Korn Ferry, which published its third annual global workforce survey this month.

“We’re still in the curve where the tools are adding burden as much as they’re providing efficiency,” said Bryan Ackermann, Korn Ferry’s head of AI strategy and transformation.

Korn Ferry surveyed more than 16,000 professionals—from entry-level all the way through C-suite—across 11 major markets, including the U.S., U.K., Australia, Brazil, France, Germany, India, Japan, Saudi Arabia, Singapore, and the U.A.E.

Irrespective of the introduction of new AI tools, 62% of respondents said they already felt like their workloads had increased significantly in the last few years. 52% of respondents said AI tools had increased the number of tasks expected in their roles.

“When you combine already overworked employees now having to learn to use a tool, you get more overworked employees, not more productive employees,” Ackermann said.

This initial productivity dip, sometimes known as a J-curve, isn’t surprising and is in some ways a necessary step toward ultimately achieving bigger gains down the road once employees get comfortable with the tooling, Ackermann said.

But part of the problem is that some organizations aren’t necessarily taking the right strategies to dig themselves out of the trough. More support, trainings and upskilling seem like a good solution, but often simply add more burden, he said.

The real solution starts with making sure you’re carving out time in an employee’s daily job. For example, that includes giving them an extension on existing projects to make sure they have the bandwidth to focus on learning. Then it’s important that any trainings are really personalized and role-specific rather than generic.

“I recognize that’s not always easy. It takes work in the organization to clear enough of the decks for that to happen. But that’s why this is a leadership challenge,” Ackermann said.

The WSJ Tech Council brings together CIOs, CTOs and CISOs advancing innovation and shaping the future. Join this trusted community where tech executives connect with peers to explore emerging trends and gain the perspective they need to stay ahead of disruption.

Request an Invitation

Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute’s new Executive Resilience series, where she’s profiling America’s top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here’s his LinkedIn.