Shown, not asserted.
Signalead™ is built to be an evidence-led instrument — built on a multi-sample validation program, and clear about what it does not yet claim. This is the research behind it, in one place.
Tested with working leaders.
199 doctoral-level expert judges evaluated the content. 1,191 working leaders across six independent samples developed and tested the instrument.
174 of 180 candidate items (97%) met all three content criteria.
21 of 21 models added explained variance in AI-related outcomes beyond established leadership measures — 19 of 21 statistically significant.
All 36 behavior scales show strong internal consistency (alpha .75–.94), confirmed in independent samples.
Program totals are as reported in the technical report; the preprint's Table 2 gives the record-level data.
Read the research.
Your AI adoption problem may not be resistance.
A 15-page briefing for CHROs and sponsors: what the validation research found about the scarce leadership routines, what the evidence does and does not support, and five questions for your next AI review.
Read the briefing (PDF) →The 95% Problem
Why AI adoption stalls at the leadership layer, and the leadership behaviors that show up where AI investment pays — the 29-page white paper co-authored with Dr. Mustafa Akben (Elon University).
Read the white paper (PDF) →Validation & Methodology
Development and validation of the AI Leadership Battery — Akben & Coyne (2026), research preprint, arXiv:2609.17965. Validation led by Dr. Mustafa Akben (Elon University).
Read the preprint →See the evidence in action.
The clearest proof is a read of your own signal. See the sample reports, or talk with us.