Module 3: Agile delivery for AI uncertainty

Module 3: Agile delivery for AI uncertainty#

AINS6008 — AI Project Management & Deployment

Essential Question#

How do AI projects adapt when results are empirical?

Scenario#

a delivery team deciding whether an AI project should move from experiment to deployment

Stakeholders: project sponsor, product owner, ML lead, operations manager, and governance reviewer

Core Moves#

Define the decision boundary
Compare baseline and alternative
Interpret evidence and assumptions
Identify failure modes
Recommend next action

Lab & Assignment#

Plan sprints around experiments and decision gates.

Artifact: deployment decision package with project charter, acceptance gates, risk log, and monitoring plan focused on agile delivery for ai uncertainty: Plan sprints around experiments and decision gates.