Organizations around the world are scrambling to adopt artificial intelligence, with the hope of streamlining their operations and gaining a leg up on their competitors. But according to MIT Media Lab, 95 percent of AI pilot programs fail to produce measurable cost savings or profit increases.
One potential culprit is workslop: AI-generated work contributions that are heavy on words but light on substance. It may come in the form of a long-winded email or a report that doesn’t offer any actionable solutions. You’ve probably encountered it, but we haven’t had a name for it until now.
What Is Workslop?
Workslop is low-effort, AI-generated emails, reports and other work content that masquerade as good work but ultimately lack the substance necessary to advance a given task. Workslop is detrimental to productivity, trust and collaboration in a workplace.
The term, which was coined by Stanford Social Media Lab and BetterUp Labs, is inspired by “AI slop,” which refers to all the low-quality, AI-generated photos and videos flooding social media platforms. Workslop is similarly devoid of human thought or intention, confusing recipients with its flowery but meaningless prose.
But work is not social media, and AI-generated workslop comes with real-world costs for productivity, trust and collaboration in the workplace. With the help of workplace researchers, we’ll explain what causes workslop, how it harms organizations and what leaders can do to clarify expectations around AI usage.
What Is Workslop?
Workslop is AI-generated work content that “masquerades as good work,” according to Stanford and BetterUp researchers. The output may seem passable at first glance, but it “lacks the substance to meaningfully advance a given task,” either because it’s “unhelpful, incomplete, or missing crucial context about the project at hand.”
In its survey of 1,150 U.S. employees, the Stanford and BetterUp researchers found that 40 percent of workers were on the receiving end of workslop in the last month, and that roughly 15 percent of the content they receive at work qualifies as workslop. When the researchers asked these respondents how it feels to receive workslop, 53 percent said they were annoyed, 38 percent were confused and 22 percent were offended.
A big chunk of this reported workslop (40 percent) is exchanged between colleagues. Eighteen percent of workslop is submitted upward to managers and 16 percent of it flows downhill from managers and executives.
Why Do People Produce Workslop?
Workslop is what happens when companies push workers to use artificial intelligence without offering any sort of broader strategy, training or communications about AI usage, according to researchers at Stanford and BetterUp.
“Without clear expectations from leaders, employees may see AI as a shortcut rather than a productivity enabler, leading to an increase in mid-quality work that seems finished but doesn’t add tangible value,” Kristina Rapuano, senior research scientist at BetterUp Labs, told Built In.
Employees may also use AI indiscriminately if leaders don’t provide guidelines for appropriate usage. Only 19 percent of knowledge workers have clarity on what type of work should be done with AI, according to Asana’s State of AI at Work report.
“When organizational leaders advocate for AI everywhere all the time, they model a lack of discernment in how to apply the technology,” the researchers at Stanford and BetterUp wrote. “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.”
The push to adopt and experiment with AI is coming at a time when workers are clinging to their jobs out of fear of being replaced by the technology. Roughly 65 percent of workers are worried about AI taking their job, according to an EY study, or that their lack of AI skills will cause them to fall behind at work. In lieu of training, workers are experimenting with AI tools on their own. More than 70 percent of workers now use it weekly, all the while juggling grueling workloads and digital exhaustion, according to the Asana study. More than half of professionals surveyed by LinkedIn said learning AI feels like a second job.
“There’s an intensity and a pressure to keep up,” Erin Eatough, cofounder and chief science officer of organizational psychology consultancy Fractional Insights, told Built In. “But when we move too quickly and we’re outpacing what our systems can accommodate to ensure that the quality of work is really high, I think that’s where we see more cutting corners.”
The Costs of Workslop
Artificial intelligence is supposed to make workers more productive, but ironically, low-effort workslop can take a toll on the productivity of others. People on the receiving end must spend time deciphering the AI-generated content, double-checking its accuracy and redoing work that doesn’t meet expectations. In effect, it shifts the burden of the work downstream from creator to receiver.
The Stanford-BetterUp survey found employees spend nearly two hours dealing with each instance of workslop. Using those workers’ self-reported salaries, researchers estimated workslop cost roughly $186 per month. If 41 percent of employees within a 10,000-person organization receive workshop, it would cost the company more than $9 million per year.
Workslop also hinders trust and collaboration in the workplace. About half of the people surveyed said they viewed workslop creators as less creative, capable and reliable than they did previously. Forty-two percent of respondents said they viewed these colleagues as less trustworthy, and 37 percent saw them as less intelligent. When workers learn not to trust their colleagues or the work they produce, they will have trouble collaborating with them on projects.
Worse yet, AI-generated workslop may go unnoticed and cause larger problems in the future. Similar to “tech debt” or unforeseen costs caused by poorly managed work, Asana’s State of AI at Work report warns companies about the risks of “AI debt.” Without specific AI policies and training, organizations may find themselves with poor data quality, security vulnerabilities or AI agents that create more problems than they solve.
“There’s an organizational cost [to building] a castle on a pile of workslop,” Mark Hoffman, a leader at Asana's Work Innovation Lab, told Built In.
What Organizations Can Do About Workslop
It’s not surprising to learn that workers are using AI inappropriately, as AI’s evolution has largely outpaced leaders’ ability to develop a strategy, training or guidelines to shape employees’ usage of it.
“The implementation of AI has gone so fast that we are seeing systemic failure, not necessarily people failure or a moral failure,” Eatough said. “Organizations have not adequately revised the systems of work in order to accommodate this very powerful technology.”
Having these conversations upfront will bring clarity to a subject that is still seen as shadowy in some workplaces. In a recent survey, Eatough’s firm Fractional Insights found that 68 percent of workers concealed the scope of their AI usage from their manager, their team or their IT department. Most were afraid of being seen as cutting corners, breaking policy or making themselves look replaceable.
Instead of criticizing workers for producing workslop, Eatough suggests managers lead these conversations with curiosity, as they might reveal “what types of pressures employees are feeling or where they might have knowledge gaps.”
“It’s really an opportunity for the start of conversations about how we’re going to move forward in this era,” Eatough said.
These conversations are also an opportunity for managers to clarify what types of work should be done with AI, including examples of how this technology fits into the workflows of individuals and teams. The BetterUp-Stanford study suggests leaders frame AI “in service of shared outcomes, rather than as a vehicle for subversively dodging responsibility.” Hoffman added that team-based learning and experimentation can help employees see the collaborative potential of AI.
“When there’s many people evaluating and using AI together in a team-based situation, there’s less of that workslop possibility than me just passing off my work to AI,” Hoffman said.
The Stanford and BetterUp researchers also found employee mindset to be an important factor. When organizations imbue employees with optimism and a sense of agency around AI, those employees are more likely to use it in creative, purposeful ways. When employees have low optimism and agency, they are more likely to take shortcuts to avoid doing work themselves.
“Organizations that proactively address workslop by setting clear expectations, building optimism and agency among employees and modeling responsible use can ensure AI enhances creativity and collaboration instead of replacing meaningful work,” Rapuano said. “The future of AI at work isn’t pre-determined. It depends heavily on how leaders guide its use.”
Frequently Asked Questions
What is workslop?
Workslop is AI-generated work material that appears acceptable at first glance but lacks substance to meaningfully advance a task. It may be unhelpful, incomplete or missing crucial context about the project at hand.
How common is workslop in the workplace?
Forty percent of workers received workslop in the last month, according to the Stanford and BetterUp study. Roughly 15 percent of the content employees receive at work qualifies as workslop.
Who is creating and receiving workslop?
According to the Stanford and BetterUp study, 40 percent of workslop is exchanged between colleagues, 18 percent is submitted to managers and 16 percent is submitted by managers and executives.
