Although AI tools can improve productivity, recent studies show that they too often intensify workloads instead of reducing them, in many cases even leading to cognitive overload and burnout. The University of Delaware's Saleem Mistry says this is creating employees who work harder, not smarter.
Mistry, an associate professor of management in UD's Lerner College of Business & Economics, says his research confirms findings found in this Feb. 9, 2026 article in the Harvard Business Review.
Driven by the misconception that AI is an accurate search engine rather than a predictive text tool, these "cut and paste" employees are using the applications to pump out deliverables in seconds just to keep up with increasing workloads.
Mistry notes that this prioritization of speed over accuracy is happening at every level of the organization:
• Junior staff: Blast out polished looking but unverified drafts.
• Managers: Outsource their ability to deeply learn and critically think in order to summarize data, letting their analytical skills atrophy.
• Power users: Build hidden, unapproved systems that bypass company oversight.
A management problem, not a tech problem
"When discussing this issue, I often hear leaders blame the technology. However, I believe that blaming the tech is missing the point; I see it as a failure of leadership," Mistry said. "When already overburdened employees who are constantly having to do more with less are handed vague mandates to just use AI without any training, they use it to look busy and produce volume-based work. Because many companies still reward the volume of work produced rather than the actual impact, employees naturally use these tools to generate slick but empty deliverables."
"I believe that blaming the tech is missing the point; I see it as a failure of leadership. Because many companies still reward the volume of work produced rather than the actual impact, employees naturally use these tools to generate slick but empty deliverables."
The real costs to organizations and incoming employees
Mistry outlines three risks organizations face if they don’t intervene:
1. The workslop epidemic
"These programs allow people to generate massive amounts of workslop, which is low-effort fluff that looks good but lacks substance. It takes seconds to create, but hours for someone else to decipher, fact-check, and fix," Mistry notes. "This drains money (up to $9 million annually for large companies) and destroys morale. As an educator, researcher, and a person brought into organizations to help fix problems, I for one do not want to be on the receiving end of a thoughtless, automated data dump, especially on tasks that require real skill and deep thinking."
2. Legal disaster
He also states, "When the cut and paste mentality makes its way into professional submissions, the risks to the organization are real and oftentimes catastrophic. Courts have made it perfectly clear: ignorance is no excuse. If your name is on the document, you own the liability. Recently, attorneys have faced severe sanctions, hefty fines, and case dismissals for blindly submitting fake legal citations made up by computers."
Click here for a list of cases.
3. A warning for incoming talent
For new graduates entering this environment, Mistry offers a warning: Do not rely on AI to do your deep thinking. "If you simply use AI to blast out polished but unverified drafts, you become a replaceable 'cut and paste' employee," he says. “To truly stand out, new grads must prove they have the discernment to review, tweak, and challenge what the computer writes. The hiring edge is no longer just saying, 'I can do this task,' but 'I know how to leverage and correct AI to help me perform it.'"
Four ideas to fix it
To survive and indeed thrive with these new tools and avoid the unintended consequences of untrained staff, organizations should:
1. Reinforce the importance of fact-checking and editing: Adopt frameworks that teach employees how to show their work and log how they verified computer-generated facts.
2. Change the incentives: Stop rewarding busy work, useless reports, and massive slide decks. Evaluate employees on accuracy and results.
3. Eradicate superficial work: Don’t use automation to speed up ineffective legacy processes. Instead, use it to identify and eliminate them entirely.
4. Make time for editing: Give yourself and your employees the breathing room to actually review, tweak, and challenge what the computer writes instead of accepting the first draft.
Mistry is available to discuss:
Why AI is causing an epidemic of corporate "workslop" (and how to spot it).
The leadership failure behind the "cut and paste" employee.
How to rewrite corporate incentives to measure impact instead of volume in the AI era.
Strategies for implementing safe, effective AI policies at work.
How new college graduates can avoid the "workslop" trap in their first jobs.
To reach Mistry directly and arrange an interview, visit his profile and click on the "contact" button. Interested reporters can also send an email to MediaRelations@udel.edu.
