You likely see neat reports and slick slide decks that seem finished at first glance. Researchers at BetterUp Labs and the Stanford Social Media Lab call some of these outputs "workslop": items that look solid but lack the substance to move a task forward.
In a recent survey of 1,150 US employees, 40 percent said they received this kind of material in the last month. People reported losing almost two hours per instance to review, verify, and redo the content.
That shift comes as more teams adopt generative tools like ChatGPT and Gemini for writing, code, and summaries. When technology makes polished drafts easy, the burden can move to receivers to check facts, fix logic, and add missing research.
Key Takeaways
- Workslop can look polished but often lacks the sources and reasoning you need.
- A recent study found 40 percent of employees saw it in the past month.
- Receivers spend time verifying and redoing content, hurting productivity.
- Expect this in slides, summaries, email drafts, and code when tools are used without judgment.
- Ask for sources and rationale so AI-assisted work helps, not slows, your team.
What “workslop” is and why it’s showing up in your workflow right now
At first glance, summaries and code can appear complete even when they miss key details. Workslop describes deliverables that look polished—clean slides, tidy reports, or plausible code—but lack real substance to move a project forward.
Researchers wrote in a recent study from BetterUp Labs and the Stanford Social Media Lab that this pattern appears as workers hand off tasks to fast tools. As technology speeds drafting, the burden shifts to you to check facts, add sources, and fix logic.
You’ll see gaps when AI tools generate content without project context. That leads to hallucinated facts, missing data, or generic filler you must replace. In coding, snippets may pass a quick glance yet fail tests or miss edge cases.
Watch for signs like jargon without evidence, summaries that don’t match inputs, or reports with no clear next steps. Ask for sources, numeric evidence, and stated assumptions so the work has real substance from the start.
Beware coworkers who produce AI-generated ‘workslop’
Polished slides or tidy summaries can still hide gaps that slow your project down.
The Stanford Social Media Lab and BetterUp research found 40 percent of people got this kind of product in the last month. Recipients often feel annoyed, confused, or offended, and 42 percent say they trust the sender less.
Flows run both ways: about 18 percent of the flawed drafts were sent up to managers, and 16 percent came from managers downward. That dynamic puts workers and leaders in a bind when someone must rewrite, reject, or approve work that misses evidence or action steps.
Tech and professional services stand out in the study as areas where fast turnarounds make these slips common. Respondents told researchers that vague reports and slides create extra meetings and lost time.
Protect your credibility by pairing any draft with your analysis, sources, and clear next steps. A short note that says where you used tools and what you verified can keep trust intact and improve team standards.
The hidden costs: time, trust, and the shaky ROI story
A tidy slide or brief summary can quietly shift hours of effort onto you.
On average, employees spend about 1 hour and 56 minutes validating and fixing each instance of workslop. That loss of time erodes productivity and adds up fast across teams.
Estimates put the cost at roughly $186 per employee per month. For a 10,000-person company, that scales to about $9 million a year in lost productivity.
There is a cultural hit too. Recipients report feeling annoyed, confused, or offended, and trust in senders drops by 42 percent. Researchers say the effort often moves downstream, forcing you to interpret or redo work.
ROI claims look shaky. An MIT study found only about 5 percent of companies report a measurable return from generative tools, and a UK report on Microsoft 365 Copilot showed no clear productivity gain.
Track incidents, log hours lost, and measure redo work. That data helps you weigh big-vision promises against real results and protect productivity across the industry.
Moving forward in the present: how you protect productivity without abandoning AI
Preventing extra cleanup starts with rules that make every draft immediately useful. Set a “no blank outputs” rule: add sources, assumptions, and your notes so the work reads like your product.
Adopt verify-then-ship workflows. Fact-check claims, run code and tests, and validate links so managers don’t have to redo work or waste time clarifying intent.
Standardize prompts and checklists, use quick peer reviews, and require runnable code and unit tests for coding tasks. Track incidents and hours lost so companies can judge vendor returns and product choices.
Ask your CEO and leaders to champion “AI with accountability.” That aligns workers, managers, and tech teams toward real results and better productivity across services and products.