The Real Evolution Of Work Slop

Work slop is a huge mess and problem for most people who work in an office.

It’s bad stuff. It’s a now-bloated report… a generic (and, obviously, generatively generated) strategy document… a “new” deck filled with AI-obvious ideas with just enough plausibility to make someone else responsible for figuring out what was useful. AI makes it easy to create… so people create more of it… faster. Then they send it downstream via email. It’s a problem… or, at least, it’s the first problem.

There’s a lot more coming down that email stream…

This week’s episode of Thinking With Mitch Joel is a conversation with Liane Davey (organizational psychologist and author of the new book, Thoughtload). We started talking about work slop in the familiar way… semi-decent-to-low quality AI output creating more work for the person receiving it. But a more interesting idea emerged as we pushed the definition further…

What happens when the AI-generated work is actually good?

Not hallucinated… not generic… not even disposable. Useful… actionable… genuinely valuable (and, yes, it’s happening based on senior conversations I’ve had in the past few weeks). In fact, I’m hearing more and more about AI work that may be even better than what someone could have produced without the technology. And… it still lands on someone else’s desk. They still have to read it… validate it… decide what matters… determine where it fits… and figure out what should happen next. The machine may have completed a once complicated task, but it has not absorbed the responsibility that comes from putting that task into the work ecosystem.

This feels like the immediate and future-real evolution of work slop.

The slop is no longer necessarily the quality of the output. It’s this uncontrolled transfer of thoughtload. Anyone can create another report… another recommendation… another list of ideas… another possible direction. And because the output may be genuinely valuable (or interesting), it becomes harder to dismiss.

Bad work is easy to ignore… good work… not so much.

So, if AI will reduce our workload… handle the repetitive tasks… speed up the analysis… write and respond to multiple drafts… summarize the meeting… organize the patterns… and then build the presentation, the workload of producing the material may shrink. But more thoughtload shifts to us… forcing us to carry everything that techl now makes possible (unless we also get the bots to do that?). If AI is on this trajectory… if more output creates more/better options… then the obvious flow is that more options create more decisions… more decisions create more responsibility… and, you guessed it, the machine saves the time but also fills that space with much more thinky work.

In the more advanced organizations… we are living this.

AI generates a smart new strategic direction and it gets sent to the team. A colleague uses the tech to develop a thoughtful analysis of how a department could improve. A manager discovers ten new possibilities for a project that was already underway. None of this is wrong… none of it is necessarily wasteful… but it is additive. It arrives without anything else being removed and without any additional space being created. Could this be the most dangerous feature of AI at work right now? Amazing that it gives organizations an almost infinite capacity to generate new possibilities… while humans still have a very finite capacity to absorb them.

The result is predictable.

Be honest, in your organization, is everything suddenly valuable… urgent… deserving of attention? Nothing ever seems to stop. And then we wonder why people are overwhelmed. We tell them AI is going to finally solve this. We tell them that once they endure the transition… they will get time back. We tell them the tools will allow them to focus on higher-value work.

But higher-value work is still work… often harder work.

Work that requires more emotional energy. So it got me thinking that maybe AI will not eliminate the burden of work. Maybe it removes the labour while multiplying what comes next. Because once AI-generated work becomes genuinely good (and we’re edging closer to this each and every day), the answer will never be to use less of it.

We can’t lose sight of the fact that every new opportunity needs a place in an ordered system of attention.

What moves up? What moves down? What gets delayed? What stops entirely? Without those decisions, AI does not become a salvation for work as we have known it. It becomes an industrial-scale generator of possibility… and consequence. The real evolution of work slop is not that the machines are producing much more work for us…

It’s that they may produce better work faster than humans can decide what deserves to matter.

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