Private AI governance consulting for industrial operations
Updated November 6, 2026
Drivers Seat treats AI governance as implementation work: define the workflow, accountable people, approved data, source authority, permissions, evaluation, human approval, audit records, retention, vendors, and release criteria before an AI system is trusted with operational work.
Drivers Seat does not make a blanket compliance, security, residency, or outcome guarantee. Applicable requirements must be identified with the customer's qualified advisors and translated into controls implemented and verified for the approved architecture.
Related scope and evidence
Private AI consulting in Canada
Derrick Brain implementation record — first-party scope and limitations, not independent validation
Capabilities
- Authority and data map: Workflow, user, role, decision-rights, and approved, restricted, and excluded data/source registers.
- Permissions and behavior: Identity, tool, integration, least-privilege, refusal, escalation, exception, and human-approval rules.
- Evaluation and release: Evaluation sets, acceptance thresholds, evidence, release criteria, pilot monitoring, and controlled expansion decisions.
- Operational controls: Logging, versioning, retention, backup, recovery, vendor, deployment, network, egress, availability, ownership, and incident requirements.
Frequently asked questions
What does private AI governance cover?
It covers the data, sources, users, permissions, models, tools, approvals, evaluation, logs, retention, vendors, incidents, and release rules for a defined workflow.
Does human approval count as a governance control?
Yes, when the accountable person, approval point, evidence, escalation path, and system behavior are clearly defined and tested.
Can Drivers Seat guarantee AI compliance?
No blanket guarantee is made. Requirements must be identified and translated into verified controls for the specific workflow and environment.