# AI Governance & Oversight Course (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/ai-governance-oversight-course-self-paced>

## Overview

As artificial intelligence (AI) becomes mission-critical in government operations, robust AI governance is essential to ensure accountability, compliance, risk management, and public trust. This four-hour, advanced-level training provides government leaders and technical experts with the frameworks, tools, and best practices to design, implement, and sustain effective AI governance programs.

Participants will engage in case studies, policy analysis, and hands-on exercises focused on establishing governance structures, managing cross-functional risks, overseeing third-party solutions, and responding to evolving legal and ethical requirements. The course emphasizes actionable strategies for embedding AI governance into agency policies, procurement, and daily operations.

## What you'll learn

- Define the pillars and principles of AI governance in a government context
- Evaluate and monitor AI systems for compliance, risk, and performance throughout their lifecycle
- Develop governance mechanisms for procurement, vendor oversight, and third-party solutions
- Address emerging legal, ethical, and policy challenges in AI deployment

## Curriculum

#### Foundations of AI Governance

- Defining AI governance and its importance in government agencies
- Core principles: accountability, transparency, risk management, compliance

#### Government Policy Landscape

- NIST AI Risk Management Framework (AI RMF)
- OMB, GAO, and EO guidance on AI governance
- International standards and cross-border considerations

#### Designing AI Governance Structures

- Roles and responsibilities (e.g., CDAO, Chief Data/AI Officers, program managers)
- Establishing policies, charters, and oversight committees
- Governance for agency-developed vs. third-party/vendor solutions

#### Lifecycle Oversight and Risk Management

- Approaches for monitoring AI systems throughout their lifecycle

#### Procurement, Vendor Management, and Third-Party Risk

- Integrating governance into procurement and contracting
- Evaluating vendor compliance and risk posture
- Data sharing, interoperability, and documentation standards

#### Legal, Ethical, and Societal Challenges

- Navigating legal frameworks (privacy, civil rights, liability)

#### Maturity Models and Continuous Improvement

- Assessing and advancing AI governance maturity
- Tools for self-assessment and external audit

#### Action Planning

- Steps to building or strengthening an AI governance program in your agency

## Instructors

### Steve Pesklo — Instructor

Steve is an energetic trainer who focuses on applying technical concepts to everyday work practices. He is the founder and president of SoftLake Solutions, a company that specializes in providing data and AI applications to identify fraud for Internal Audit, Criminal Investigations, Forensic Accounting, Privacy, and Compliance.

Steve brings a large amount of experience across multiple industries and government agencies. He is an expert in implementing large data analysis projects across the world, including Inland Revenue in the UK and Argentina, New Zealand, Africa and across Europe. Previously, he was the manager of Data Architecture and Data Services for a large mortgage company. He is a frequent speaker on data analytics and project management topics and speaks fluent German. He has been teaching at the Graduate School for over 10 years.

Steve has an M.B.A. from the University of St. Thomas and a B.S. in Computer Science from California Lutheran University and the Universität Salzburg in Austria. He is certified as a Certified Fraud Examiner (CFE), Project Management Professional (PMP), and a Certified ScrumMaster (CSM).

## Pricing

**Tuition:** $675