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productivitymeasurementroiA Evidence

Measuring AI Productivity Gains: Beyond the Hype

How to quantitatively measure real productivity improvements from AI tools and avoid common measurement pitfalls.

Citations

  • McKinsey Global Institute. (2024). "The Economic Potential of Generative AI: The Next Productivity Frontier." MGI Report.
  • Brynjolfsson, E., et al. (2024). "Generative AI at Work." NBER Working Paper No. 31161.
  • Accenture Research. (2024). "Total Enterprise Reinvention with AI." Accenture Technology Vision 2024.

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Practice prompt

Re-write your Measuring AI Productivity Gains: Beyond the Hype prompt with explicit success criteria and critique instructions.

Try this now

Run the Analyzer pack twice (manual vs. AI) and compare the Overestimation Δ.

Common pitfall

Skipping reviewer verification time hides the real cost of rework and hallucinations.

Key takeaways

  • Run a manual vs. AI comparison to see actual lift.
  • Capture Overestimation Index and micro-TLX together.
  • Document what “good” looks like so teams can replicate it.

See it in action

Drop this into a measured run—demo it, then tie it back to your methodology.

See also

Pair this play with related resources, methodology notes, or quickstarts.

Next Steps

Ready to measure your AI impact? Start with a quick demo to see your Overestimation Δ and cognitive load metrics.

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