Welcome to the world of workslop

A new word for a growing problem

Harvard Business Review has coined the term “workslop” to describe AI-generated content that “looks polished but lacks real substance,”Harvard Business Review Axios reports . It’s a play on the word “slop” (meaning mess or slop) and perfectly describes this phenomenon where AI is used to create content that looks good on the surface but doesn’t contribute any real value.

A recent study from Stanford and BetterUp found that 41% of workers have encountered this kind of AI-generated material, costing nearly two hours per incident in rework. AI "workslop" is crushing workplace efficiency, study finds . It's not just annoying—it's destroying productivity.

The researchers describe workslop as material where "you might recognize the feeling of confusion after opening such a document, followed by frustration. You start to wonder if the sender simply used AI to generate large blocks of text instead of thinking it through themselves." If that sounds familiar, you've been "workslopped."

When enthusiasm meets reality

Here’s the irony: The number of companies with fully AI-led processes nearly doubled last year, while AI use in the workplace has also doubled since 2023.AI-Generated “Workslop” Is Destroying Productivity . But a report from the MIT Media Lab found that 95% of organizations see no measurable return on their investments in these technologies. So much activity, so much enthusiasm, so little actual benefit.

Why is this happening?

The problem often lies in how we implement AI at work. Many companies run with "AI everywhere, all the time" mandates without giving employees tools or guidance on when and how to use the technology smartly.

The result? “Employees are using AI tools to create low-effort work that looks okay but ends up creating more work for their colleagues.” This creates a negative spiral. Over half (53%) of respondents were “annoyed” by receiving AI-generated work, and 22% were “offended.” Almost half said they saw their colleagues as “less creative and trustworthy” after receiving work slips from them.

What can we do about it?

The researchers have some concrete suggestions:

• Set guidelines instead of general mandates. Stop just throwing AI tools at the company and hoping for the best. Give employees specific use cases where AI actually adds value.

• Be transparent. If you are using AI to create content, say so. It helps the recipient understand what they are working on.

• Focus on quality, not quantity. Just because you can generate a 20-page report in five minutes doesn't mean you should.

• Learn the limitations of the tools. AI is great for some things, but it can't replace deep domain knowledge and critical thinking.

  
  

This is just the beginning.

Workslop is really just the tip of a larger iceberg. MIT research indicates that 95% of companies in their dataset experience workslop from their AI implementations MIT report: 95% of generative AI pilots at companies are failing | Fortune , but the core problem is not the quality of the AI models – it’s the “learning gap” for both tools and organizations.

Understanding and implementing AI correctly is crucial. It’s not just about using the technology, but doing it smartly and effectively. By following guidelines and focusing on quality, we can maximize the benefits of AI. Let’s strive to create content that truly adds value, instead of falling into the trap of work-slop.

Remember, AI is a tool. How we use it determines whether we create value or just more work. Let's do it right!