Shadow AI Risk and Governance Training Course

Overview

The Shadow AI Risk and Governance Training Course is a five-day intermediate course for risk managers, compliance teams, information security teams, technology leaders, procurement teams, and business managers who leave with a Shadow AI Control Plan. The course connects use discovery, business need, data exposure, risk tiering, vendor review, approved alternatives, policy, monitoring, incident response, and adoption measures. Agile Leaders Training Center delivers this course on shadow AI risk and governance.

Who Should Attend

• Risk functions responsible for identifying, assessing, and treating technology risk
• Security functions responsible for data exposure, access, monitoring, and response
• Compliance functions responsible for policy, evidence, and control assurance
• Technology functions responsible for approved AI services and application visibility
• Procurement functions responsible for supplier review and contractual controls
• Business functions responsible for AI use cases and employee adoption

The course assumes participants contribute to risk, technology, procurement, or business controls and leaves out penetration testing, legal opinions, and product implementation.

Departments and Industries

The course supports shadow AI control decisions across regulated and operational environments.

• Risk, compliance, and internal control functions
• Cybersecurity, technology, and data governance teams
• Finance and professional services
• Healthcare and education services
• Manufacturing, logistics, and energy operations

Learning Objectives

By the end of this course, participants will be able to:

• Analyze shadow AI usage patterns and underlying business needs
• Build an inventory of tools, users, data flows, and owners
• Apply risk tiers to data, security, compliance, and action exposure
• Evaluate vendors, controls, approved alternatives, and exceptions
• Prioritize monitoring, response, education, and enforcement actions
• Create a Shadow AI Control Plan

Course Agenda

Day 1: Shadow AI Context and Discovery

• Shadow AI Definition and Use Scenario Map
• Business Need and Approved Capability Gap Canvas
• Application Agent and API Discovery Source Register
• User Group Usage Pattern and Data Transfer Analysis
• Shadow AI Inventory and Ownership Template

Day 2: Risk Assessment and Prioritization

• NIST AI RMF Govern Map Measure Manage Application
• Data Sensitivity and Exposure Path Matrix
• Security Compliance Legal and Action Risk Scorecard
• Human Oversight and Decision Impact Assessment
• Shadow AI Risk Tier and Treatment Register

Day 3: Vendor and Control Design

• AI Supplier Security and Governance Review Checklist
• Contract Data Use Retention and Audit Question Set
• Identity Access and Least Privilege Control Map
• Approved Tool and Alternative Service Decision Matrix
• Exception Request and Compensating Control Record

Day 4: Governance Monitoring and Response

• Shadow AI Policy and Acceptable Use Structure
• Application Usage and Data Exposure Monitoring Dashboard
• Education Communication and Reporting Path Plan
• AI Incident Triage and Escalation Protocol
• Control Effectiveness and Adoption Measurement Framework

Day 5: Shadow AI Control Practice

• Suggested Exercise: Usage Discovery and Inventory Review
• Suggested Exercise: Data Exposure and Risk Tier Assessment
• Suggested Exercise: Vendor and Approved Alternative Decision
• Suggested Exercise: Incident and Exception Response Simulation
• Capstone Exercise: Shadow AI Control Plan

Practical Exercises

The course includes suggested activities for moving from invisible AI use to proportionate organizational control.

• Suggested activity: map an unmanaged AI use case, data flow, user group, and owner.
• Suggested activity: assign a risk tier and document treatment options.
• Suggested activity: compare a vendor and approved alternative against defined controls.
• Suggested activity: present a Shadow AI Control Plan with discovery, monitoring, education, response, and measures.

FAQs

Who suits the Shadow AI Risk and Governance Training Course?

Risk, compliance, security, technology, procurement, and business managers suit the course; it assumes involvement in AI use, governance, or organizational controls.

How does shadow AI risk differ from general AI governance?

Shadow AI risk focuses on unauthorized or unmanaged tools, agents, APIs, users, and data flows that are outside established inventory, approval, monitoring, and control processes.

Why do employees use shadow AI?

Employees may use shadow AI when approved options are unavailable, difficult to access, poorly matched to tasks, or less convenient than public tools, making unmet needs part of the risk assessment.

How should organizations respond to discovered shadow AI?

Organizations should assess use, data, impact, and need; then select education, migration, approval, monitoring, restriction, exception, or blocking actions proportionate to the risk.

What belongs in a Shadow AI Control Plan?

A Shadow AI Control Plan links discovery sources, inventory, risk tiers, vendors, approved alternatives, policies, controls, exceptions, monitoring, incident response, owners, and measures.

Conclusion

Participants leave with a Shadow AI Control Plan connecting visibility, business need, data exposure, risk tiers, approved options, monitoring, and response. The work product changes hidden AI usage into documented control decisions. It gives teams a reusable structure for vendor review, exceptions, education, enforcement, incidents, and performance measurement.