AI Governance and Risk Engineering
Faiz Ahmad, PHD
CEO @ 1% AI Fund | Governance Researcher
Build, audit, and defend an AI governance program in one live session
You know AI governance is coming. You have read the summaries. You have not done it yet -- not because you do not care, but because nobody has shown you what doing governance actually looks like. Not in a policy document. In a pipeline. On a real system.
So you wait. The EU AI Act takes effect. NIST AI RMF shows up in procurement contracts. A customer asks for your AI documentation and you send back an ethics statement from 2022.
Governance is becoming a specific technical skill. The practitioners who can build and audit it on real systems, not just write about it, are in short supply. That is where the leverage is right now.
This workshop does not teach about governance. It makes you do it. On your own system. With your own data.
You generate a case study before the session. I demo on a hospital triage AI with real failures. You follow along on yours.
You leave with 5 completed artifacts, usable Monday, built on your own system with your own data:
- Regulatory exposure summary
- Quantitative risk assessment
- Rewritten model card section
- 3 governance control specifications
- 30-day action plan
Workshop agenda
- 10:00AM EDT
Welcome and Setup
Meet your cohort. Confirm your case study is ready. Quick round-robin: what governance challenge brought you here today?
- 10:15AM EDT
Module 1: Know What's Actually Enforceable
Regulatory convergence across EU AI Act, NIST AI RMF, state laws. I classify MedScreen live. You classify your system. Artifact 1: Regulatory exposure summary.
- 11:00AM EDT
Module 2: Risk Assessment with Real Evidence
5 risk dimensions and the risk matrix. I score MedScreen's fairness and drift evidence live. You score MedScreen, then your own system. Artifact 2: Risk assessment.
- 11:45AM EDT
Module 3: Quantifying AI Risk
Fairness metrics, drift detection, model card scoring. I score MedScreen's card (7/18) and rewrite two sections live. You rewrite yours. Artifact 3: Audit-ready card.
- 12:35PM EDT
Title: Break
Stretch, grab coffee, review your work so far.
- 12:50PM EDT
Module 4: Where Governance Plugs into Production
Pipeline controls and three-layer architecture. I design 3 controls for MedScreen. You design 3 for your system with owners and metrics. Artifact 4: Control specs.
- 1:40PM EDT
Module 5: Build Your 30-Day Action Plan
Risk register, stakeholder map, gap analysis, three prioritized actions with owners, deadlines, success criteria. Artifact 5: Plan you can execute this week.
- 2:30PM EDT
Closing and Q&A
Review the 5 artifacts you built today. Open Q&A: regulatory gray areas, career positioning, organizational resistance, technical implementation.
Learn directly from Faiz
Faiz Ahmad, PHD
PhD, Penn State. AI safety research + production AI systems. 300+ trained.
Who this workshop is for
Engineers and ML practitioners who build AI systems and know regulation is coming but have not prepared. Act before it becomes an emergency.
Compliance and risk professionals being asked to audit AI systems they have never built. You need technical fluency to do this job credibly.
Aspiring AI governance professionals who see 340,000 new roles but have no portfolio. Build 5 artifacts you can show in your next interview.
What's included
Live sessions
Learn directly from Faiz Ahmad, PHD in a real-time, interactive format.
Your Own AI Governance Case Study
Before the workshop, you generate a case study for your AI system using a prompt we provide. Fairness data, drift patterns, pipeline gaps, model card assessment. Your raw material for every exercise.
5 Governance Artifacts Built for Your System
Regulatory exposure summary, quantitative risk assessment, rewritten model card section, 3 governance control specifications, and a 30-day action plan. Built during the session. Usable Monday.
Certificate of completion
A shareable credential recognizing your completion of AI Governance & Risk Engineering with Faiz Ahmad, PhD.
Participant Workbook
11 reference frameworks, 5 reusable templates, quick-reference cards, and the MedScreen master case study with evidence packets. Yours to keep and reuse across every AI system you govern.
Risk Assessment Toolkit
Auto-calculating Excel spreadsheet, interactive risk classification decision tree, and a model card comparison showing exactly what audit-ready looks like versus what fails.
Full Workshop Recording
annot make it live or want to revisit a module? Full replay access so you can rewatch exercises, review frameworks, and refine your artifacts.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Frequently asked questions
$200
USD