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When he was writing A Farewell to Arms, Ernest Hemingway was obsessed with nailing the book’s ending — so obsessed, in fact, that he wrote 39 separate versions of it. When asked in an interview what had so stymied him about the process, his answer was characteristically Hemingway, “Getting the words right.”
These days, the idea of finessing anything to perfection seems almost anachronistic. Why work that hard when ChatGPT can churn out a perfectly serviceable ending for you?
I don’t actually believe that’s true, though. While AI is extremely valuable for many things, the temptation to use it as a crutch in place of thoughtful work is becoming harmful. Instead, we’re seeing a profusion of what has become known as “workslop,” defined as AI-generated work that superficially appears to be high-quality, but that actually lacks the meaningful substance required to advance a particular task.
You’ve probably been a slew of AI workslop yourself. An AI-generated summary that doesn’t actually capture the key points. A polished strategy memo that says nothing. An email that’s grammatically accurate but requires three follow-ups because it failed to address the actual question.
For leaders, monitoring workslop is a new challenge: how do you encourage efficiency without accepting mediocrity? How do you leverage AI’s capabilities without letting it replace the critical thinking that actually moves organizations forward?
The Downstream Effect Of AI Workslop
One of the perils of workslop is that its effect isn’t always obvious. With only a quick once-over, it initially seems like all the pieces are there. In reality, it’s the corporate equivalent of a Potemkin village, impressive at a distance but hollow up close.
That hasn’t stopped it from spreading. Harvard Business Review found that 40% of U.S.-based employees across industries have been workslop recipients in the last month alone. Most of the time it flows between peers, but it’s also sent to managers by direct reports and from managers to their teams. This creates a situation where the recipient has to spend their own time untangling or re-doing what they were given, a sort of slop waterfall effect in which the person at the bottom is responsible for sifting through the mess piled before them.
None of this, of course, is good for building trust or goodwill among team members. “Workslop creates a layer of invisible labor that rarely shows up in job descriptions or performance reviews,” says Jasmine Escalera, a career expert for the resume platform Zety. “Employees are quietly fixing mistakes just to keep work moving, often outside their core responsibilities. Over time, that extra, unrecognized work adds up to exhaustion, frustration and disengagement.”
This is an objectively bad time to strain trust. According to Edelman’s annual Trust Barameter, faith in institutions is already dangerously low. The workplace is one of a few places trust remains relatively stable, Stanford professor Jeff Hancock, one of the co-creators of the term “workslop,” told HR Brew. Not only is it undermining how teams work, he said, “it’s undermining how we think about one another, and so there’s probably an even bigger hidden cost to the trust that is really crucial in organizations.”
What Leaders Can Do About AI Workslop
When AI first became widely available, the impulse of many leaders was to encourage teams to experiment; to figure out for themselves how this exciting new technology would best serve them. While I wholeheartedly agree that employees should be testing and iterating with AI, this openness created quality-control anarchy. Without clear guidelines about when and how to use AI responsibly, teams defaulted to convenience and speed over quality and care. The result is the workslop epidemic we’re now facing.
It’s incumbent on leaders to rein it back in. Hancock and his co-authors found that part of the reason employees settle for slop is that they feel overstretched, with an overall decrease in work engagement due to macro factors like lingering post-pandemic stress, hybrid work fragmentation and burnout. Workslop, they write, is “both a symptom and potential accelerant of these deeper issues.”
Building conscious AI policies is one way to stem the workslop tide. When employees feel they can be honest about how they’re using the technology, it leads to more open conversations about the tasks AI should and should not be doing.
I also encourage time for thinking. Workslop is the result of hurried panic. I’m someone who cherishes the time each day I reserve for deep work, and my teams deserve that, too. When everything is urgent, people seek out shortcuts. As a leader, you have the power to push back on artificial urgency. Distinguish between tasks that genuinely need to be done ASAP and those that need depth. Give people permission to say, “This will take another day to do properly” — and mean it.
Not every meeting summary or line of code needs to be agonized over, farewell to arms-style. But if you never insist on excellence, and if speed always trumps substance, you’re at risk of running not much more than a workslop factory.
