You’re probably wondering what on earth “AI workslop” even means. Fair question.
Niederhoffer et al. (2025) describe workslop as “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” (para. 2)
In simple words, AI workslop is the extra mess created when AI hands you something that looks polished enough on the surface but falls apart the moment you try to use it. It looks like it should save you time, yet somehow you end up spending even more time fixing, rewriting, and reshaping it. It pretends to help but quietly hands you a bigger workload.
Now, what does that have to do with teaching? Well, everything.
We use AI. Our students use AI. Our colleagues use AI. And a huge portion of the AI-generated content circulating through our classes, our inboxes, and our shared planning folders becomes workslop if we don’t check it, refine it, or shape it with real professional judgment. It sneaks into lesson plans, student assignments, team planning documents, project outlines, parent communications, pretty much anywhere text can appear.
And before we know it, we find ourselves waist-deep in low-quality content that someone now has to clean up. Usually the “someone” is the teacher.
The idea really landed with me a few days ago when I revisited Niederhoffer et al.’s piece in Harvard Business Review. Their context was the corporate world, but it felt like they were describing so many conversations I’ve been having with teachers.
The patterns match almost perfectly, sometimes even more sharply, because teaching runs on clarity and timing. If the material is weak, vague, or generic, everything downstream slows down.
Think of the last time a student submitted a piece of writing that looked oddly polished. Or when you opened a shared lesson plan and immediately sensed that AI wrote most of it. Or when a colleague sent a draft you couldn’t really use because the ideas didn’t connect, even though the sentences looked crisp.
All of that is workslop. And the problem isn’t just the writing, it’s the silent extra labor it creates. When (bad) AI shortcuts replace real thinking, the burden doesn’t disappear. It simply shifts. It moves downstream to the person who now has to fix it.
In classrooms, downstream usually means us.
So I decided to dig deeper and put together a short guide that looks specifically at how AI workslop shows up in teaching. My aim wasn’t to criticize AI use, we’re past that conversation. My aim was to name a phenomenon we are already experiencing and give teachers language to talk about it. Once we name something, we can start managing it instead of feeling frustrated by it.
The guide walks through what workslop looks like in real classrooms. When students rely too heavily on AI, we see writing that “sounds right” but doesn’t say much. We see invented citations or examples that don’t match the texts we taught. We see reflections that read like someone else’s thoughts. All of these require careful follow-up, not because the student intended to mislead us but because the shortcut created a gap in understanding.
And it’s not only students. Teachers fall into it, too, especially under pressure. AI drafts that look clean trick us into thinking they are good enough to use as-is. But once we begin teaching from them, cracks appear. Activities don’t align with the learning goal. Examples don’t fit the grade level. Explanations skim over the very parts that matter. Suddenly, we’re reteaching content or rewriting lessons at the last minute.
That’s workslop. It drains time, confidence, and energy in small doses that add up over weeks.
The guide also explores the roots of workslop: unclear policies, rushed planning, weak AI literacy, vague prompting, overtrust in polished phrasing, and the temptation to accept the first draft simply because it arrives quickly. These are things we can address, but only if we see them clearly.
I also included a wide collection of trusted resources: UNESCO frameworks, MIT’s AI guidebook, U.S. Department of Education reports, Digital Promise’s AI literacy framework, and several state and district guidelines. Teachers need reliable documents to ground their understanding of AI literacy, not generic checklists floating around social media. These resources help build that base.
At the end of the day, my point is simple:
Use AI. Use it confidently. Use it creatively. Let it handle the heavy lifting. But don’t hand over your judgment. Don’t outsource your thinking. And don’t trust the smooth surface of an AI-generated paragraph without digging into what’s underneath. The quality of the work still depends on you.
If you want to explore this more deeply, I’ve shared a short guide that breaks the whole idea down and offers practical steps to avoid AI workslop in your own teaching. I hope you find it useful.
Reference
Niederhoffer, K., Rosen Kellerman, G., Lee, A., Liebscher, A., Rapuano, K., & Hancock, J. T. (2025, September 22). AI-Generated “Workslop” Is Destroying Productivity. Harvard Business Review.
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