87 percent
Have governance
of organizations surveyed by the American Arbitration Association reported having some form of AI governance in place.1
Applied AI for Compliance and Governance Teams
Applied AI for Compliance and Governance Teams
$500.00
Build practical skills to govern AI use across your organization and address common AI governance challenges. In this five-week course, you will learn how to find and assess AI risks, connect risks to governance obligations, design controls, gather evidence, monitor AI systems, and communicate recommendations to leadership. Designed for compliance professionals, risk managers, legal teams, internal auditors, technology governance teams, and business leaders who support or oversee AI use. You will apply a repeatable governance process to one AI system or use case. Along the way, you will create five connected professional artifacts, including a portfolio-ready AI governance case study.
- In Stock
5-module
series
5
weeks
5 hours
per week
What you’ll be able to do after 5 weeks
Learn how to evaluate AI use, establish practical controls, and help leaders make informed governance decisions. Each module guides you through one part of a repeatable AI governance process.
- Discover and prioritize AI risks: Find AI use across shadow AI, embedded AI, and AI systems the organization builds or commissions. Evaluate each use based on its impact and governance exposure.
- Connect risks to governance obligations: Use the National Institute of Standards and Technology Artificial Intelligence Risk Management Framework (NIST AI RMF) to organize your analysis. Connect AI risks to applicable obligations, evidence requirements, and responsible owners.
- Design operational controls: Turn broad governance requirements into controls that are testable, evidence-producing, and assigned to a clear owner.
- Build reusable governance tools: Create control templates that can be adapted for different AI systems, use cases, and organizational needs.
- Establish ongoing AI assurance: Define evidence, monitoring metrics, thresholds, alerts, audit-trail requirements, and incident-response practices.
- Assess third-party AI: Examine AI provided by vendors and consider how accountability is shared between an organization and its vendors.
- Communicate governance decisions: Explain remaining risks, recommend next steps, and make a specific decision request to leadership.
Built in partnership with USAII
DeVryPro developed this course in partnership with the United States Artificial Intelligence Institute (USAII), an independent international institute focused on AI education and certification. USAII brings specialized AI knowledge and an industry-informed framework, while DeVryPro provides a practical online learning experience designed to help you apply new skills at work. After completing the course, you will earn a Certificate of Completion from USAII and a digital badge.
Why take this AI compliance and governance course?
AI can enter an organization through employee tools, existing platforms, vendor services, and systems developed for a specific use. These systems may create AI governance challenges related to transparency, changing performance, data lineage, and increased autonomy.
This course gives professionals responsible for AI compliance and governance a practical method for evaluating these risks. You will learn how to decide which AI uses need attention first, identify the obligations that may apply, design controls, and assess whether those controls continue to operate as intended.
Identify AI use across the organization
Identify shadow AI, AI features built into existing platforms, and AI systems developed or commissioned by an organization. Evaluate which uses create the greatest governance exposure.
Connect risks to obligations
Use the NIST AI RMF to organize your analysis. Explore how AI governance may connect to employment, lending and credit, healthcare, consumer protection, the European Union Artificial Intelligence Act, and ISO/IEC 42001.
Create controls that can be tested
Design controls with clear owners, schedules, thresholds, triggers, and evidence requirements. Turn those controls into reusable templates for future AI use cases.
Support informed leadership decisions
Describe the organization’s governance posture, identify remaining risks, recommend next actions, and present a specific request to leadership.
Meet Amara
AI Governance Practice Coach and virtual instructor for Applied AI for Compliance and Governance Teams
Amara’s expertise centers on governance, risk, compliance, assurance, and cross-functional decision support. She has helped teams translate broad requirements into practical operating expectations.
How Amara supports you
Amara brings a calm, structured, and conversational approach to complex governance questions. She helps learners distinguish voluntary frameworks from binding obligations, examine what evidence would support a conclusion, and strengthen controls by clarifying ownership, cadence, thresholds, triggers, and escalation.
With Amara, you will learn to:
- Identify AI use, recognize material risk, and connect risk to governance obligations.
- Turn obligations into controls that can be assigned, tested, evidenced, and monitored.
- Build practical course tools and a leadership-ready governance recommendation.
Amara’s coaching philosophy
She combines disciplined analysis with supportive challenge. She encourages learners to be honest about uncertainty, assumptions, unresolved issues, and residual risk while moving toward an actionable recommendation.
What makes this course different
Select a topic to explore
A repeatable AI governance method
Follow a clear process for addressing AI governance challenges by identifying risk, connecting risk to an obligation, designing a control, producing evidence, monitoring performance, communicating remaining risk, and requesting a decision.
Connected professional artifacts
Build five related governance tools instead of completing separate assignments that do not connect. Each artifact becomes an input for the next stage of your work.
Applied governance frameworks
Use the NIST AI RMF as the main organizing framework. Explore areas where AI-related obligations may apply, including employment, lending and credit, healthcare, consumer protection, European Union Artificial Intelligence Act risk tiers, and ISO/IEC 42001.
Controls designed for real use
Learn how to create controls that are testable, evidence-producing, and assigned to a responsible owner.
Ongoing monitoring and response
Define the evidence, metrics, thresholds, alerts, audit trails, and incident-response practices needed to evaluate controls over time.
Realistic governance scenarios
Practice making decisions in compliance and governance situations through guided activities and AI Learning Coach scenarios.
Clear communication for leadership
Present your analysis through a portfolio-ready case study and a concise, two-minute leadership pitch.
Applied AI for Compliance and Governance Teams modules
Select a module to explore
Module 1
Why AI changes the compliance job
Learn how opacity, drift, data lineage, and increased autonomy can affect existing compliance and governance controls. Identify AI entering the organization through shadow AI, embedded AI, and systems that are built or commissioned. Assess governance exposure and select three AI uses for further analysis. Then determine which AI system or use should be governed first.
You leave with
An AI Risk Surface Map that identifies where AI is being used and where governance coverage may be incomplete.
Continue your learning path
If you’re exploring this AI course, you may also be interested in additional courses that can support your growth and broaden your skill set.
Ready to move beyond one-off prompts?
Learn how to give AI the instructions, examples, and background it needs to produce more useful results and more repeatable workflows.
Ready to build broader AI solutions?
Expand into more advanced applications involving multiple tools, teams, agents, agentic workflows, and business use cases.
Interested in a degree program instead?
Explore undergraduate and graduate business, technology, and digital health programs offered by DeVry University and its Keller Graduate School of Management.
Learn more¹From Principles to Practice | AAA-ICDR Institute (May 2026)