Description

The Problem

Every day you wrestle with fragmented AI governance guidelines that never line up with the energy sector's strict regulatory framework. The result is endless re‑work, audit findings, and stalled projects. This playbook removes that friction and gives you a single, compliant roadmap.

What You Get

✅ Module 1: Foundations of AI Governance for Energy
✅ Module 2: Regulatory Landscape - NERC, FERC, and International Standards
✅ Module 3: Risk‑Based AI Model Assessment
✅ Module 4: Data Lineage and Cybersecurity Controls
✅ Module 5: Stakeholder Alignment and Change Management
✅ Module 6: KPI Design for AI Compliance
✅ Module 7: Audit‑Ready Documentation Practices
✅ Module 8: Continuous Monitoring and Incident Response
✅ Module 9: Governance Maturity Assessment
✅ Module 10: Implementation Roadmap Development
✅ Module 11: Ethical AI Decision Framework
✅ Module 12: Sustainment and Future‑Proofing

✅ AI Governance Maturity Assessment Workbook
✅ Regulatory Gap Analysis Matrix for Energy Utilities
✅ AI Model Risk Exposure Matrix with Severity Scoring
✅ Stakeholder Mapping and Communication Plan Template
✅ Data Lineage Documentation Runbook
✅ Cybersecurity Controls Checklist for AI Pipelines
✅ AI KPI Dashboard Excel Model
✅ Compliance Audit Checklist - NERC & FERC
✅ Implementation Roadmap Planner with Milestones
✅ Ethical Decision Framework Guide
✅ Process Handoff SOP for Model Deployment
✅ Quick Reference Cards - Top 10 Compliance Pitfalls

How It Is Organized

The learning path starts with the 12‑module course, each lesson building the knowledge you need to design a compliant AI program. Once the concepts are clear, you move to the Implementation Toolkit. The toolkit is divided into ten practitioner journey folders:

Getting Started - launch checklist and governance charter.
Assessment & Planning - maturity assessment and gap analysis files.
Models & Frameworks - risk exposure matrix and ethical decision framework.
Processes & Handoffs - SOPs and data lineage runbook.
Operations & Execution - cybersecurity controls checklist and deployment SOP.
Performance & KPIs - KPI dashboard and performance reporting template.
Quality & Compliance - audit checklist and compliance documentation guide.
Sustainment & Support - roadmap planner and sustainment plan.
Advanced Topics - advanced risk modeling and future‑proofing strategies.
Reference - quick reference cards and practitioner pro‑tips.

This Is For You If

You have been tasked with building an AI governance program for a utility and need a board‑ready plan within the next quarter.
Your current compliance documents are scattered across teams and you cannot demonstrate a unified risk posture to regulators.
You must align AI model risk assessments with existing NERC cyber‑security standards without reinventing the wheel.
You are responsible for establishing KPI tracking for AI models and need a dashboard that speaks to both technical and business stakeholders.
You face recurring audit findings because your AI processes lack documented handoffs and you need a ready‑to‑use SOP library.

What Makes This Different

The course delivers a step‑by‑step curriculum that turns a novice into a governance specialist, while the toolkit provides the exact files you fill in to operationalize each lesson. No separate PDFs or scattered spreadsheets - the learning and doing are tightly coupled.

Every template is pre‑structured for immediate entry. The Pro Tips sections capture hard‑won lessons from energy‑sector implementations, so you avoid the same mistakes that cost other teams weeks of rework.

Developed by a team with 25 years of combined experience in AI compliance, cyber‑security, and energy regulation, this bundle is a complete system rather than a collection of fragments. You receive a proven methodology that has been field‑tested across multiple utilities.

Get Started Today

This playbook gives you a finished, proven system: a structured learning track that equips you with the theory, followed by ready‑to‑fill implementation files that translate that theory into compliant, operational AI. Skip months of drafting, testing, and re‑aligning. Start executing a governance framework that meets regulatory expectations and drives operational efficiency from day one.