Workshop: AI Governance in Practice

Thursday, October 23, 2025 • 5:30–7:30 PM • Midtown Manhattan, NYC

Modern AI moves fast. Governance needs to move faster. Join us after work in Midtown for a concise, hands-on session focused on real-world AI governance—what good looks like, how to implement it, and how to make it stick across teams.

Who should attend

• Model Risk & Validation, Compliance, Internal Audit
  
• Data Science & ML Engineering, Product, and IT/Risk
  
• Legal & Policy teams responsible for AI/ML oversight
  

What you’ll learn (and practice)

• Policy → controls: Turn AI principles into concrete, testable controls and approvals.
  
• Evidence you can defend: Design validation tests for data quality, performance, robustness, fairness, and drift.
  
• Monitoring that works: Define KPIs, thresholds, and alert-to-remediation workflows.
  
• Change management & traceability: Connect model changes to approvals, tests, and deployment records for auditability.
  

Format (interactive + practical)

Short talks followed by guided mini-exercises using realistic case studies and editable templates. You’ll leave with artifacts you can adapt immediately.

Agenda (2 hours)

• 5:30 PM — Arrival & networking (light bites & drinks)
  
• 5:45 PM — Welcome & goals
  
• 5:55 PM — The AI Governance Stack (roles, RACI, operating model)
  
• 6:10 PM — Mini-Exercise: Map policy requirements to a control library
  
• 6:30 PM — Validation & Acceptance Criteria (what “good evidence” looks like)
  
• 6:45 PM — Mini-Exercise: Define monitoring KPIs and thresholds
  
• 7:05 PM — Capstone: Assemble a lightweight Governance inventory
  
• 7:25 PM — Debrief & immediate next steps
  
• 7:30 PM — Close
  

What you’ll take away

• A governance dossier template (policy mapping, controls, RACI, risk assessment, validation plan, monitoring plan, change log)
  
• Example model card / system card templates
  
• A 60–90 day playbook to stand up or mature your AI governance operating model
  

Logistics

• Date & Time: Thursday, October 23, 2025 • 5:30–7:30 PM
  
• Location: Midtown Manhattan (venue details shared upon registration)
  
• Capacity: Limited to keep the session interactive
  
• Bring: A laptop (recommended for templates); an AI/ML use case from your org (optional)
  

Why attend

• Practical over theoretical: Leave with working artifacts, not just ideas.
  
• Cross-functional by design: Risk, data, and product perspectives in one room.
  
• Audit-ready outcomes: Evidence and workflows you can defend.