UNIVERSITY PARK, Pa — Approximately 88% of organizations around the world implemented artificial intelligence (AI) into at least one business function by the end of 2025, the latest McKinsey Global Survey on the state of AI found. Despite promised productivity gains, passive AI use at work, where employees copy-and-paste AI responses to complete tasks, can make people doubt their skills and find their work meaningless, according to a study co-authored by a faculty member from Penn State’s Smeal College of Business that published in Scientific Reports .
Using prolific, an internet platform designed to help scientists find research participants, the team recruited about 270 professionals working across human resources, communications and management fields to complete a series of writing tests similar to their day-to-day tasks, both manually and with the help of AI tools. Their study found that AI use — specifically whether participants used AI collaboratively to workshop their own ideas or passively to generate and copy responses — played a significant role in participants’ reported scores of self-efficacy, meaningfulness, and psychological ownership. Specifically, passive AI use led to nearly 20% declines in feelings of ownership and 10% declines in perceived meaningfulness, while collaborative AI use showed scores similar to AI-independent work, according to the researchers.
Although AI use has been reported to improve productivity, Yidan Yin , assistant professor of management and organization at Penn State’s Smeal College of Business, explained that less is known about the deeper psychological impacts of AI use in the workplace. Yin explained that while scientists have begun exploring possible long-term costs, the field is still quite new, and much of the research is very broad
“Previous studies have primarily looked at the positive impacts AI can have on work productivity, as well as how AI use can make workers feel isolated and less motivated,” Yin said. “With this study, though, we really wanted to focus on better understanding how AI use reshapes people’s connection to their work.”
To accomplish this, the team primarily focused on measuring AI use’s impacts on three closely related constructs: self-efficacy, or an individual’s confidence in themself to complete a task without AI assistance; work meaningfulness, or how much an individual perceives their work as purposeful and significant; and psychological ownership, or how much ownership individuals feel over their output. The researchers used two additional variables — task enjoyment and outcome satisfaction — to gain a comprehensive view of how AI use impacted participants' psychology, Yin explained.
The researchers built a series of writing tasks tailored to the occupations of participants in the study. In the first task, participants were assigned to one of three conditions and instructed to complete the task either manually without the use of AI, actively collaborate with AI, or passively copy and paste AI-generated responses to complete the task. Participants then answered questions about their feelings of self-efficacy, work meaningfulness and psychological ownership of the output. In the second task, all participants were required to complete the writing task manually without AI assistance, answering the same survey questions afterwards.
“This two-task design made it possible to examine both the immediate effects of different uses of AI and their lingering effects after participants returned to working without AI, all in an experiment that only took about 20 to 30 minutes to complete,” Yin said.
Passive AI use during the first task reduced people’s feelings of ownership by nearly 20%, and self-efficacy and perceived meaningfulness by nearly 10%, relative to manual writing, whereas collaborative AI use did not differ meaningfully from manual writing. The declines in self-efficacy and meaningfulness persisted after the second task, when all participants returned to manual writing, suggesting that the erosions cannot be easily undone by returning to working without AI assistance.
Interestingly, Yin noted that passive AI use led to a substantial increase in reported task enjoyment and outcome satisfaction after the first task, with gains of up to 29% compared to manual writing. However, when participants returned to manual writing in the second task, they reported a large drop in these ratings. Notably, their outcome satisfaction fell to be 21% lower than participants who had previously wrote manually, whereas collaborative AI use buffered against this drop. Yin explained that this pattern shows how critical it is for employees to be mindful of how they are incorporating AI into their day-to-day work.
“Passively relying on AI can erode employees’ confidence in themselves and could make them enjoy their job less in the long-term,” Yin said. “They have an initial burst of enjoyment because they don’t need to put in a lot of effort to accomplish the task well, but it makes an employee reluctant to do the task manually. It also leads them to feel like they’re not needed — they see firsthand that AI can perform a task effectively and could potentially replace them.”
Yin said that change in organizations is usually difficult for employees to adjust to, and the rapid integration of AI has proven no different. Moving forward, the team plans to continue studying the psychological impacts that AI-driven change at work is having on employees, as well as how businesses can employ these tools in a way that is effective both for the employer and the employees in an organization.
“Our findings reinforce that companies need to do more than just ask employees to use AI to maximize their productivity, which may inadvertently encourage passive reliance on AI because doing so saves time in the short run,” Yin said. “That isn’t effectively utilizing the employees’ skills, and long-term, those employees are going to feel very alienated from their work.”
Additional co-authors on the work include Elena Hayoung Lee, a doctoral candidate in management and organization at the University of Southern California (USC); Nan Jia, professor of strategic management at USC; and Cheryl Wakslak, associate professor of management and organization at USC.
Scientific Reports
Observational study
People
Relying on AI at work reduces self-efficacy, ownership, and meaning while active collaboration mitigates the effects
15-Mar-2026