AI Adoption That Actually Changes the Company
Source-grounded pack with Diagnose AI Adoption Friction, Build an Adoption Measurement System, and Map AI Adoption Readiness, plus 1 more.
Get this packGrounded in the complete AI Adoption That Actually Changes the Company series.
Open the pack, choose a workflow, and follow its setup and input instructions. You can also open each workflow below.
10 source essays · 4 usable skills · reviewed Jul 2026
Use this pack when
Choose this pack when the work touches AI Adoption That Actually Changes the Company and you need a bounded workflow with explicit inputs, a defined output, and human review gates.
Choose the job in front of you.
4 source-grounded skills. Load one workflow at a time.
Diagnose AI Adoption Friction
Use this workflow when AI usage is uneven, resisted, hidden, or reverting under pressure and operators need to diagnose workflow, trust, skill, policy, incentive, manager, and support friction using champions, skeptics, and shadow use as evidence.
Output specification
Return an adoption_friction_diagnosis with target_behavior, observed_behavior, evidence_by_cohort, job_step, friction_types, shadow_use, broken_assumptions, risk, recommended_change, owner, and next_review_evidence.
Build an Adoption Measurement System
Use this workflow when measuring whether AI adoption changed normal work and whether a pilot became an operating model, using behavior, quality, cycle time, rework, exceptions, controls, ownership, and learning rather than licenses or logins.
Output specification
Return an adoption_measurement_review with decision, cohorts, behavior_funnel, appropriate_non_use, quality, cycle_time, rework, exceptions, risk_events, broken_assumptions, operating_model_durability, recommendation, owner, and next_review.
Map AI Adoption Readiness
Use this workflow when selecting and sequencing AI adoption use cases by consequential work, accountable ownership, input readiness, risk, review capacity, and an observable behavior or outcome change.
Output specification
Return an ai_adoption_readiness_map with candidates, work_value, readiness_scores, evidence, classification, lead_use_case, before_behavior, after_behavior, owner, manager_ritual, risks, prerequisites, stop_condition, and sequence.
Plan AI Behavior Change
Use this workflow when turning an AI use case into a durable team habit by embedding a work trigger, usable artifact, role-specific practice, manager inspection ritual, exception support, reinforcement, and iteration loop.
Output specification
Return a behavior_change_plan with work_trigger, before_behavior, after_behavior, workflow_artifact, roles, practice, manager_ritual, support, exceptions, reinforcement, evidence, owner, and review_cadence.
Keep consequential decisions explicit.
These workflows structure analysis and artifacts; they do not authorize autonomous external, personnel, financial, legal, security, or other high-impact action.