Interactive tool
Utility OT AI Risk Register Builder
Create a first-pass risk register for approval-gated transformer APM AI workflows across OT boundaries, source approvals, agent permissions, cybersecurity review, and audit artifacts.
GridAPM use case
Utility AI Governance Risk Register for Transformer APM
Use-case page for utility AI governance, cybersecurity, OT, and procurement teams evaluating bounded agentic AI workflows for transformer APM.
Incoming HV feed
Critical transformer
Distribution bus
Feeders to load
- Focus
- utility AI governance risk register
- Audience
- AI governance, cybersecurity, OT, procurement, asset management, and responsible-AI review teams
Best for controlled pilots where AI assists evidence assembly and draft rationale, while engineers keep final authority.
Where teams get stuck
Evidence, responsibility, and handoff quality decide whether AI is useful.
GridAPM use cases are intentionally practical. They start with a narrow workflow, approved sources, named reviewers, and audit-ready output rather than unsupported autonomous decision claims.
- Implicit boundaries stall pilots
- Agentic AI pilots stall when source boundaries, prohibited actions, reviewer authority, and audit artifacts are not explicit.
- OT-safe governance language
- Critical-infrastructure teams need AI governance language that respects OT boundaries and does not imply autonomous control.
- Register before promises
- Procurement and security reviewers need a risk register before production promises are made.
How GridAPM helps
Local-first APM workflows keep the evidence trail visible.
GridAPM can help utilities evaluate human-reviewed agentic AI for transformer APM, CBM, maintenance planning, and resilience workflows without handing final engineering decisions to software.
- Explicit allowed tasks
- Frame allowed AI-assist tasks such as evidence assembly, review questions, draft summaries, and missing-evidence notes.
- Explicit prohibited actions
- Keep prohibited actions explicit, including autonomous control, protection-setting changes, and unreviewed maintenance approval.
- Linked audit artifacts
- Connect risk register items to security, data handling, pilot scope, and reviewer signoff artifacts.
Pilot scope
A pilot scope template you can inspect.
Inputs and expected outputs for the first controlled workflow — narrow enough for engineering, security, and procurement review.
Pilot inputs
- Candidate AI-assisted transformer APM workflow
- Approved source systems and excluded systems
- Reviewer authority and escalation path
- Cybersecurity, procurement, and OT boundary requirements
Pilot outputs
- First-pass AI risk register
- Agent permission and prohibited-action map
- Audit evidence checklist
- Pilot acceptance questions for governance review
Workflow
One pipeline from evidence to engineer-approved output.
Every solution runs the same five-stage workflow: evidence intake, correlation and quality gates, agent reasoning, engineer sign-off, and a reportable work package.
- Intake
- Correlate & quality gate
- Agent reasoning
- Engineer sign-off
- Work package & report
Pilot lead path
Use a public tool, then move to approved evidence.
Public tools help prepare the conversation. A real GridAPM pilot should use only approved source evidence, explicit reviewer roles, and agreed data-handling boundaries.
Scope a controlled transformer APM pilot
Pick the asset population, evidence streams, reviewers, and measurement plan — engineers keep final authority at every stage.