Pillar POV
Evidence BAI Literacy Assessment: From Gut Feel to Measured Δ
Instrument literacy in under a week so execs see real Overestimation Δ and TLX tiles instead of anecdotes.
Stop asking 'how confident are we with AI?' and start showing a baseline Δ chart plus the workload pulses that explain it.
Executive TL;DR
- •Replace opinion surveys with 5-day measurement cycle yielding actual Δ scores
- •Teams using Δ tracking see 40% reduction in overconfidence within 2 sprints
- •Workload (TLX) data prevents burnout—catches fatigue before quality drops
Do this week: Launch your first 5-day literacy assessment sprint Monday morning
Why literacy must be measured, not debated
AI literacy is not a personality trait. It is a repeatable behavior: document the scenario, run it twice (manual vs. AI), log Overestimation Δ, log TLX, repeat next week. The moment you do that, the conversation changes from “who is good at AI” to “which rituals stay within ±5 Δ”.
Three signals to capture
- Manual vs. AI timing (lift %).
- Overestimation Δ per contributor.
- micro-TLX (mental demand + frustration).
Assessment loop (5 days)
- Day 1 – Frame the packs. Pick one innovation ritual and one engineering ritual. Lock the rubric, reviewer, and prompt scaffolds. Link the Fair Trial checklist so everyone sees the guardrails.
- Day 2 – Manual baseline. Run each pack without AI. Self-rate quality, capture reviewer minutes, jot fatigue notes.
- Day 3 – AI assist. Re-run with AI scaffolds. Lock prompts; no on-the-fly tweaks.
- Day 4 – Coach the Δ. Plot self-ratings vs. reviewer scores. Anyone above +5 gets a coaching plan anchored to real outputs.
- Day 5 – Publish tiles. Paste the Δ chart, TLX pulses, and reviewer notes into the exec memo. Decisions stop being hypothetical.
““The second we showed Δ on slide 2, Legal stopped worrying about AI enthusiasm and started asking for the Fair Trial checklist.””
Hook it into Methodology + Demo
Drop the Analyzer demo into every stand-up (“Run the 3-minute version together”) so literacy never becomes a one-off workshop. Then send the execs to /methodology so they see the scoring model that keeps Δ and TLX credible.
- ✓Include Δ, TLX, and reviewer minutes in every retrospective note.
- ✓Bookmark
/methodologyso skeptics can audit the scoring math. - ✓Show the pinned resources on
/resourcesfor people who want more context.
Apply this now
Choose your next step to put these concepts into practice
Run Interactive Demo
Experience the evaluation flow with sample tasks and see Δ + TLX in action
PM Quickstart Guide
Product Manager's guide to measuring AI impact and building evidence
Want to understand the science? Review our methodology
Share this POV
Paste the highlights into your next exec memo or stand-up. Link back to this pillar so others can follow the full reasoning.
Next Steps
Ready to measure your AI impact? Start with a quick demo to see your Overestimation Δ and cognitive load metrics.