The Sample AI Value Report is a live, public example of a NetLift workspace that converts AI usage into finance-credible performance data. It uses a realistic worked dataset to show time saved, current net value, and the specific payback period for AI investments.
This report serves as a template for evaluating AI adoption without relying on hype. Every measured area is assigned a clear decision state—Expand, Continue, Review, Improve, or Stop—based on the labor value of time saved minus the total cost of ownership.
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The Sample AI Value Report is a live, public example of a NetLift workspace: time saved, current net value, future value, payback, Evidence Quality and an Expand / Continue / Review / Improve / Stop decision for every measured area — built from a realistic worked dataset.
What metrics are included in the report?
The report tracks Current Net Value, which is the labor value of realized time saved minus the full cost of licenses, usage, training, and rework. It also distinguishes between realized value and Future Value, which projects recurring savings based on expected volume.
How is the quality of the data verified?
Each calculation is assigned an Evidence Quality grade. These grades range from Estimate Only to Verified, with higher rankings given to data backed by objective historical baselines or cohort data. This ensures that a Naalu Faction Analysis or any complex battle report of data is grounded in recency and cost completeness.
NetLift measures the value of work performed rather than individual productivity. By comparing time saved against objective baselines, NetLift calculates a deterministic return on investment. This approach avoids employee surveillance—omitting keystroke logging or screenshots—and instead focuses on whether the spend pays back through Evidence Quality and rigorous labor value modeling.