As AI tools become more common in the workplace, many companies have encouraged employees to use them in their daily tasks. But researchers from Harvard have pointed out a growing concern: something known as “workslop.”
The term comes from “AI slop,” referring to low-quality content produced by artificial intelligence. Workslop describes documents or deliverables that look polished on the surface but lack real insight, context, or practical value. They may seem complete at first glance, but they don’t actually move the work forward.
In simple terms, the work appears professional, yet the real effort is pushed onto the person receiving it, who must review, fix, or rebuild it. This slows productivity and creates tension within teams.
The impact on organisations
Research from the MIT Media Lab and BetterUp Labs shows that about 40% of professionals have received this type of work in the past month. The cost is significant. Each instance requires nearly 2 hours of additional work, totalling roughly $186 per employee per month in lost productivity. In large companies, the total losses can reach millions each year.
The effects aren’t only financial. Poorly thought-out content often leads to frustration and mistrust. When managers also pass along shallow, AI-generated material, it can cause friction and damage team relationships. Over time, collaboration suffers and confidence in colleagues’ abilities declines.
Why it happens
Workslop usually appears when AI is used to avoid thinking rather than to support it. Instead of refining and tailoring the output, some employees rely on the tool to quickly produce pages of content without checking accuracy or relevance.
As a result, the responsibility shifts to others who must correct errors, interpret unclear information, or make decisions based on incomplete work.
How to prevent it
According to Harvard’s findings, leaders can reduce this problem by setting clear expectations for how AI should be used. Employees need guidance on when the technology makes sense and how to review and improve its output.
The key is to treat AI as a tool for support, creativity, and efficiency—not as a replacement for human judgment. When teams use it thoughtfully and take ownership of the final result, companies can maintain quality while still benefiting from the speed and convenience AI offers.
