Choose self-serve practice, team rollout, or a focused sprint that turns one workflow into evidence leadership can trust.
For solo operators who want a guided way to use AI at work without building bad habits.
For teams that need shared practice, governance basics, and evidence managers can review.
A four-week pilot for one delivery team: map real workflows, run experiments, and leave with evidence.
For multi-team rollouts that need governance alignment, security review, and a reporting cadence.
Early pricing is shown for planning. Final scope is confirmed in a short call.
Make AI literacy visible without pretending to sell certification: map risks, decisions, and evidence European teams can review.
NextMindOS supports AI literacy, governance readiness, and responsible workflow evidence — designed for teams that want to make their AI use visible, safer, and defensible.
We avoid presenting NextMindOS as anything it isn’t. The product is honest about its boundaries.
People don’t learn safe AI use by reading prompts. They improve when practice starts from real work, returns later, and proves transfer.
A compact bar chart for showing which methods have the strongest meta-analytic support.
Data: Donoghue & Hattie 2021; Rowland 2014; Wisniewski et al. 2020; Barbieri et al. 2023. Values are standardized effects, not ROI forecasts.
A forest-plot style view for separating strong effects from findings that are basically flat.
Data: Rowland 2014; Adesope et al. 2017; Latimier, Peyre & Ramus 2021. Intervals shown where reported in the source synthesis.
A line chart for explaining why feedback must name the mistake and the next move.
Data: Wisniewski, Zierer & Hattie 2020. High-information feedback includes task, process, and self-regulation information.
Start with the user’s own answer so gaps are visible before AI helps.
Ask people to recall and decide, not just reread instructions.
Bring topics back later so the skill survives beyond the workshop.
Name the exact mistake and point to the next better attempt.
Use examples and hints early, then remove support as skill grows.
Finish with a real workflow artifact managers can review.
See where each plan adds team evidence, governance support, reporting, and hands-on rollout help.
Each stakeholder gets a clearer answer: where AI helps, where it is risky, and what changed after practice.
Productivity, client trust, and risk visibility — without slowing delivery.
Workflow-level adoption your delivery leads can actually defend in reviews.
Role-based AI literacy with evidence — not generic compliance training.
Visibility into shadow AI, tool approval, and decision logs by policy version.
Start with the readiness assessment, pick one workflow, then scope the smallest pilot that can produce evidence.