The official description of workslop, per researchers from Stanford’s Social Media Lab and BetterUp, an online coaching platform, is “AI-generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” 

But, let’s be honest, most office workers won’t need a definition. We’ve all encountered examples of workslop in the wild. It’s the memo jammed with stuffy words like “underscore” and “commendable” that leaves you scratching your head, or the report littered with em-dashes that, upon a close read, feels hollow. 

It’s one thing to get a clumsy AI-created marketing email or solicitation from a vendor; it’s another to get one from your colleague or boss. Managers who shared workslop horror stories with the Stanford and BetterUp team described redoing a direct report’s project or sending it back for heavy revisions, while others spent time worrying about how to tell colleagues that their work was subpar. 

Jeffrey Hancock, a professor of communication at Stanford University and founding director of the Stanford Social Media Lab, shared an example of the feedback the researchers heard: “Receiving this poor quality work created a huge time waste and inconvenience for me,” one project manager said of some workslop. “Since it was provided by my supervisor, I felt uncomfortable confronting her about its poor quality and requesting she redo it. So instead, I had to take on effort to do something that should have been her responsibility, which got in the way of my other ongoing projects.”

A benefits manager said of one AI-sourced document a colleague sent her, “It was annoying and frustrating to waste time trying to sort out something that should have been very straightforward.”

So while companies may be spending hundreds of millions on AI software to create efficiencies and boost productivity, and encouraging employees to use it liberally, they may also be injecting friction into their operations. 

After surveying full-time employees at 1,150 companies, the researchers found that workslop is flowing in all directions inside firms. Mostly it spreads laterally between peers, but managers are also sending slop to their reports, and employees are filing it to their bosses. In total, 40% of respondents said they had received a specimen they’d define as workslop in the past month from a colleague.

An anti-workslop workshop

Does this mean companies should cut back on AI? Probably not. In a competitive marketplace, it’s hard to ignore a technology that even the study authors say “can positively transform some aspects of work.” What companies can do, however, is set up guardrails. They may even consider building an anti-workslop workshop for employees. Here’s what it might include:

• Develop AI literacy. Employees should treat AI output as that of an untrained intern, prone to making factual and stylistic errors, says Thor Ernstsson, CEO of ArticBlue.ai, a consulting company that specializes in prototyping AI use and has worked with dozens of Fortune 500 companies. Employees should know the quirks and limitations of the tools they’re using. What data can it handle? Is it prone to hallucinating? “People don’t understand that just because AI sounds authoritative, it isn’t necessarily correct,” Ernstsson says.

• Be specific about when AI is appropriate. “When organizational leaders advocate for AI everywhere all the time, they model a lack of discernment in how to apply the technology,” the study authors write. “It’s easy to see how this translates into employees thoughtlessly copying and pasting AI responses into documents, even when AI isn’t suited to the job at hand.”  

• Use AI to polish work, not create it. Train employees to use AI as a thought partner or coach, says Ernstsson. Workers might write a draft of a report or memo, ensuring that it contains all relevant information and context, before they turn to an AI agent for tips and suggestions.
  
• When work is subpar, address it. “Teams that are focused on task quality—they critique each other, they accept critiques, and have high standards—experience less workslop,” Stanford’s Hancock told Fortune. The same expectations that apply to collaborative work between two employees should also apply to work completed by a human and AI, the researchers suggest. 

• Communication lessons. There’s a reason that some people now argue that today’s communications majors may be tomorrow’s leaders. In the era of AI, it’s more important than ever that employees understand and practice how to communicate clearly person-to-person before they even think about using AI.

By the way, you’d better schedule your anti-workslop workshop soon. The researchers say that “lazy” AI-generated work is not only slowing people down, it’s also leading to employees losing respect for each other. After receiving workslop, staffers said they saw the peers behind it as less creative and less trustworthy.

This story has been updated to include comments from Stanford University professor Jeffrey Hancock.