Calgary Industrial AI Governance & Compliance Playbook

Calgary industrial teams adopting AI need governance that is lightweight but enforceable. Practical governance means clear ownership, model lifecycle control, and traceability for every recommendation affecting operations.

Priority Use Cases

• Define approved AI use-case classes by risk tier.
• Set model release gates for test evidence and owner sign-off.
• Create incident review workflow for incorrect recommendations.

Data Readiness Checklist

• Document source systems, retention, and data correction owners.
• Track feature lineage for each production model.
• Validate representativeness across plants, shifts, and seasons.

System Integration Pattern

• Register each model with purpose, inputs, and expected action path.
• Expose source references and confidence in user interfaces.
• Automate rollback to prior model version on threshold breach.

Governance and OT Safety

• Map AI controls to existing OT cybersecurity and QA policies.
• Enforce role-based approval for model and threshold changes.
• Log user interactions for audit and training feedback.

KPIs to Track

• Model drift incidents
• Recommendations accepted vs rejected
• Time to rollback after anomaly
• Audit findings per quarter

30-60-90 Day Plan

• Day 1-30: establish governance charter and model inventory.
• Day 31-60: apply release gates to active pilot models.
• Day 61-90: run full audit and close control gaps.