---
description: Workflow recipe — the org-side AI adoption arc, policy to proof, by chaining 4 skills.
argument-hint: [the org: size, industry, what AI tools are in use (officially and not), what's worrying leadership]
---

Run the **Adopt AI Properly** workflow recipe for: $ARGUMENTS

This is a *chain* of skills. Run each stage in order and **carry every stage's output forward as context** for the next. Open with a one-line plan of the 4 stages, then ask once for essential missing inputs (regulatory exposure, current tool spend, which roles AI has changed most, the review framework in use). Don't re-ask between stages.

Run each stage under a clear `## Stage N — <name>` heading:

1. **Set the rules** — apply the `ai-usage-policy` skill: the one-page policy with the data traffic-light (grounded in this org's real data classes), approved tools, disclosure lines, and the decision log for counsel.
2. **Redesign the roles** — apply the `role-redesign-for-ai` skill to the role(s) AI changed most: the before/after task inventory with verification counted as work, capacity deliberately reallocated, and the junior-ladder answer — consistent with the policy from stage 1.
3. **Fix the reviews** — apply the `ai-assisted-performance-review` skill: criteria that measure judgment, verification, outcomes, and leverage; calibration rules for uneven adoption; the three hard-case scripts — aligned to the charters from stage 2.
4. **Prove what paid** — apply the `ai-roi-audit` skill across the tool spend: per-tool verdicts with the measurement method behind each number, the hidden-cost ledger, and baseline plans for the unknowns.

Close with a **leadership one-pager**: the policy headline, the role changes, the new review frame, and the renewal decisions — the packet that turns "we should figure out AI" into four signed-off documents.
