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In the wake of MIT’s study that concluded 95% of AI pilots fail, the headlines have been filled with warnings about “workslop.” But the deeper research tells a more important story, one that is particularly relevant to patents.

A Stanford/BetterUp study defines “workslop” as AI-generated content that looks polished but lacks substance—slick slides and clean summaries, filled with vagueness and repetition. But the issue isn’t the AI. It’s that AI exposes and magnifies poor work that was already there.

Patent practices illustrate these issues well. If individuals or teams are rewarded largely for volume—number of drafts, sheer document output—AI will happily accelerate that. But if the drafting incentives aren’t tied to quality, strategic value, or client outcomes, all you’ve done is to create more low-value output not tied to strategic objectives.

The real challenge isn’t fixing the AI. It’s rethinking the work: what counts as valuable output, how we define quality, and how incentives align with outcomes. In patent law, that means not just focusing on how quickly or efficiently a draft is generated, but focusing more on whether it moves the ball forward—toward strong, enforceable, strategically sound patents.

AI didn’t create workslop. It exposed it. The firms that thrive will be the ones that can pair AI’s power with expert judgment that ensures the output isn’t just fast, but right.

Source: LinkedIn Post by Michael Drapkin

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