Lilly Tech Systems
AI Governance Framework
Build robust organizational AI governance structures. Learn how to create policy templates, establish accountability frameworks, define decision rights, and set up ethics boards to ensure responsible AI adoption across your organization.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is AI governance? Why organizations need structured governance, regulatory landscape, and key stakeholders.
2. Governance Structure
Organizational models, roles and responsibilities, decision-making hierarchies, and cross-functional governance teams.
3. Policies
AI policy templates, acceptable use policies, risk classification frameworks, and compliance documentation.
4. Ethics Board
Establishing an AI ethics board, member selection, review processes, escalation procedures, and case studies.
5. Monitoring
Continuous governance monitoring, KPIs and metrics, audit trails, compliance dashboards, and reporting frameworks.
6. Best Practices
Mature governance programs, scaling governance, industry standards, continuous improvement, and future trends.
What You'll Learn
By the end of this course, you'll be able to:
Design Governance Structures
Create organizational frameworks that ensure responsible AI development and deployment across teams.
Write AI Policies
Draft comprehensive AI policies covering acceptable use, risk management, and regulatory compliance.
Establish Ethics Boards
Set up and run effective AI ethics review boards with clear mandates and decision-making authority.
Monitor Compliance
Implement governance monitoring systems with dashboards, audits, and continuous improvement processes.