Is AI giving employees a distaste for effort?

What happens when doing the work becomes optional?

AI can draft a memo, summarize a meeting and write working code in seconds. The more employees rely on it, the less they may need to wrestle with the problems those tasks once required them to solve themselves.

That has some workplace experts wondering whether AI is doing more than saving time. Could it also be giving employees a distaste for effort?

Tom Davenport, the President's Distinguished Professor of Information Technology and Management at Babson College in Massachusetts, thinks that risk is already emerging.

"The reason they get into using AI is to do things more quickly and improve their productivity, and they're less interested in exercising their brains," Davenport said.

Distaste for effort, or something else?

Asked whether employees are developing a distaste for effort, Davenport said yes.

"I think it's pretty endemic that people are trying to find ways to do things more easily, all the way from students to professionals," Davenport said, "and it's going to lead, already is leading, to some slip-ups."

Steven Shaw, an assistant professor of marketing at King's Business School at King's College London in England, pushed back a little on the word distaste, saying it almost implies a deliberate choice. He co-authored the 2026 paper "Thinking—Fast, Slow, and Artificial" on cognitive surrender, in which people adopt AI answers with little scrutiny, while he was a postdoctoral researcher at the Wharton School in Philadelphia.

"I can see distaste as a downstream consequence, but I think the mechanism that I would see as more likely is something to do with operant conditioning or reinforcement," Shaw said.

"It can be easy for a lot of people to slip slowly into this concept of cognitive surrender where they are now outsourcing that effort, outsourcing the whole reasoning process," he said.

Shaw said people who are rewarded for that, whether through higher productivity or a good result from following AI's answer, may repeat it until it becomes a habit.

Gabriella Kellerman, an expert partner and director at Boston Consulting Group in the San Francisco Bay Area, has researched how employees respond to AI at work.

"I haven't seen any evidence of an overall distaste for effort, but what I have seen is evidence of an over-reliance on AI for specific tasks," Kellerman said. "This over-reliance can lead to cognitive atrophy and deskilling, though it can be prevented."

When faster output hides weaker skills

Recruiting is one example Davenport gave of what he calls process slop, where AI-generated work touches every stage of a process. A company writes a job description with AI, and the loop continues from there.

"The applicant uses AI to personalize a resume and a cover letter and then sends it back to the company, and the company reads it with AI and rejects it and writes a rejection letter, if they're polite, to the person using AI," Davenport said. "Trust in the recruiting process has really broken down."

Shaw said mandating AI across a team can make it hard to tell healthy use from over-reliance, and can change who looks like the strongest performer.

An employee who holds back on AI could be penalized even if they're using more human judgment, he said.

"The peer beside them, if they rely or over-rely on AI a lot, maybe they actually look better on paper. They're performing things faster, they're getting things done quite well," Shaw said. "And so there can be a bit of an arms race there as a result."

Kellerman's Harvard Business Review research on "AI brain fry," which is defined as mental fatigue from excessive use or oversight of AI tools beyond one's cognitive capacity, points to a different kind of strain.

"Our research actually suggests that people are engaging with AI at intensive levels, even beyond their natural cognitive capacity, going above and beyond their natural levels of effort," Kellerman said.

A 2026 IBM Institute for Business Value study, covered by HRD America, found that 60% of employees worry about skills erosion, with critical thinking cited most often as declining. HRD America has also reported on researchers warning that AI could erode a workforce's ability to think when it absorbs the difficult decisions that build judgment.

What employers can do about it

Davenport said employees need to learn which tasks call for their own effort.

"We need to learn to discriminate between the situations where it's really necessary to provide our own inputs and those where you can legitimately get away with having AI do most of the work," he said.

He said he tries to get his students to use multiple prompts and combine the outputs into a coherent single document.

"Even once you have that, trying to see how you can add value to it, make it more interesting, take out some of the more cliché styles of writing that language models do, add your own perspective," he said.

Davenport also said organizations should hold employees accountable for the quality of the work they submit under their name.

"I think deskilling and cognitive surrender should be part of AI literacy and having some awareness that this is possible can help people maybe develop some intentionality with their use," Shaw said.

"I think managers just need to be cautious and allow for different levels of adoption and also appreciate different types of output, unless the goal is to automate the team," he added.

The managers being asked to make those calls are also using AI heavily themselves. A 2026 Omni Calculator survey of 705 U.S. adults who use AI for writing found that 54% of managers run 70% or more of what they write past AI before sending it.

Gallup found that just 25% of U.S. employees said in May 2026 that their organization had communicated a clear plan for integrating AI. Kellerman said her latest study with Harvard Business Review on how leaders talk about AI found that employees don't respond to productivity messages about AI.

"Instead, employees want to understand how AI can benefit them and their work," she said.

Kellerman said she's also helping clients track how their people use AI.

"I'm working with many clients now to also redesign their analytics so that they can measure how their people are using the technology and track these impacts, just as we would track other significant workforce analytics," she said.

"If things are implemented well and carefully with the right guardrails, you can actually enhance learning or enhance abilities in the job," Shaw said.