PM Practice - AIPMO

NEW - Change Management for AI Projects: Preparing People for a New Way of Working

AI change management goes beyond training people on a new tool. It requires helping them develop new mental models for working with probabilistic systems — and addressing the trust, accountability, and expertise questions that conventional IT change management was never designed to handle.

By AIPMO

/ 29 Jan 2026 · 13 min read

NEW - Third-Party AI and Vendor Management: Risks You Don't Control

When you deploy third-party AI, you deploy the decisions its developer made about training data, fairness testing, and risk mitigation — and you remain accountable for the outcomes regardless of who built the system. Here's what PMs need to know before signing the contract.

By AIPMO

/ 29 Jan 2026 · 14 min read

NEW - Monitoring AI Systems in Production: The Work After Go-Live

AI systems degrade in production even when no one touches the code. Post-deployment monitoring is not optional: for high-risk AI it's a legal requirement, and for all AI it's the only way to know whether the system is still doing what it was designed to do.

By AIPMO

/ 29 Jan 2026 · 17 min read

NEW - Testing and Validation for AI Systems: More Than Accuracy

Every AI project needs testing — but the test plan looks nothing like traditional software QA. The NIST AI RMF TEVV framework requires testing across five dimensions: accuracy, fairness, robustness, safety, and explainability. A system can pass every conventional test and still discriminate.

By AIPMO

/ 29 Jan 2026 · 17 min read

NEW - Stakeholder Engagement for AI Projects: Beyond the Usual Suspects

AI systems affect people who never appear on a traditional stakeholder register — and under the EU AI Act, informing them and giving them a mechanism to contest decisions is a legal obligation. Here's how to build a stakeholder approach that goes beyond the usual suspects.

By AIPMO

/ 29 Jan 2026 · 14 min read

NEW - Human Oversight in AI Systems: Designing for Control

Human oversight of AI isn't a design preference — it's a legal requirement. EU AI Act Article 14 mandates five specific capabilities in every high-risk AI system. As PM, each one is a project deliverable, not a governance aspiration.

By AIPMO

/ 29 Jan 2026 · 19 min read

NEW - Model Cards and Datasheets: Documentation That Matters

AI projects need documentation that doesn't exist in conventional IT: model cards, datasheets, and system cards. Under the EU AI Act, technical documentation must exist before deployment — and be retained for 10 years. Here's what each document must contain and why.

By AIPMO

/ 29 Jan 2026 · 17 min read

NEW - AI Risk Registers: Beyond Traditional Risk Management

AI risk registers use the same mechanics as conventional ones — identify, assess, mitigate, monitor. What changes is the taxonomy of risks, how likelihood behaves at scale, and the fact that the register doesn't close at deployment. Here's what needs to extend.

By AIPMO

/ 29 Jan 2026 · 17 min read

NEW - The AI Project Charter: What's Different

The AI project charter covers the same fundamentals as any charter — plus questions that conventional projects never ask: Why AI rather than an alternative? Who might be harmed? What decisions will never be automated? What data is this project permitted to use?

By AIPMO

/ 29 Jan 2026 · 19 min read