Your company
Defaults reflect a 100-person mid-market company, the worked example from the What Actually Returns series. Every output is a range, on purpose.
Global baseline: only 20% of employees are engaged (Gallup, 2026). Mid-market firms routinely have 60+ points of headroom.
Capped at 30% on principle: no peer-reviewed causal return exists yet for financial-wellbeing programs. The output labels this slider directional, and that restraint is the point.
Want to present this?
Your numbers generate a board-ready briefing: the investment case, the architecture gap, and every figure cited to its source.
The link reproduces your exact settings, so you can share it with a colleague and build consensus before the meeting. Nothing is stored on our servers.
The defensible number
Uplift is applied only to AI-addressable work, never to total payroll.
Show the math & sources
This model estimates productivity-denominated value and selected human-capital effects. It does not capture revenue innovation, risk reduction, customer-experience gains, or implementation-quality variance. That is precisely why the number is a conversation starter, not a guarantee. Methodology and full citations: see the evidence ledger below.
Help answer what AI and people investment actually return
I'm building a study from the organizations doing the work, so this calculator keeps pace with what they're seeing on the ground. Take part and you'll see the findings first, with early access to the research report when it launches. Add your email and I'll reach out when the first survey opens.
Seen research we should know about?
This evidence base is refreshed quarterly, and good sources come from everywhere. Submit a study, article, or dataset for consideration. Every submission is human-reviewed and held to the same verification standard as everything else on this page. Peer-reviewed work moves fastest.
The next step
See where your organization actually stands
The calculator shows the size of the prize. The AI Transformation Diagnostic shows you where the architecture gap sits in your own organization, and what to do first.
Decide what to change first → Take the AI Transformation Diagnostic →The evidence ledger
Every figure in the calculator traces to a published source, graded by tier: T1 peer-reviewed experiments · T2 large-N institutional research · T3 secondary, flagged. Contested findings stay in, and stay labeled. Organized by the five pillars of the AI Transition Maturity Model.