AI Project Management: Deliver AI Products That Ship

Most AI projects never make it to production. This course teaches you how to deliver the ones that do.

Companies are spending record amounts on AI, yet about 95% of enterprise GenAI pilots show no measurable impact on profit (MIT NANDA, 2025), and more than 80% of AI projects fail, twice the rate of other IT projects (RAND). The technology is rarely the problem. The problem is delivery.

AI products behave differently from traditional software. They give plausible answers that are sometimes wrong, they depend on data, and they change over time. Agents go further: they take actions in real systems. Pure waterfall breaks down because you can't specify accuracy up front. Pure agile breaks down because leadership, risk, and compliance teams need evidence before they approve a release.

This course gives program and project managers a practical AI Delivery Framework that bridges both worlds. Executives get gates and evidence, and teams keep room to iterate.

What you'll learn

• Why AI delivery is unique: hallucinations, agent autonomy, human-in-the-loop design, evaluation, drift, and adoption

• Phase 1, Opportunity & Intake: turn vague AI ideas into scoped, measurable initiatives with a risk tier and a governance path

• Phase 2, Design & Build Iterations: make the four design decisions that shape every AI product, run a four-lane backlog, and apply an "AI Definition of Done" that gathers evidence as you build

• Phase 3, Readiness & Release: stress testing, red teaming, operational and people readiness, ring-based rollouts, and a documented go/no-go decision

• Phase 4, Monitoring & Evolution: one dashboard that answers Is it good? Is it working? Is it used? Is it safe?, plus drift detection, AI incident playbooks, and keep/change/retire reviews

See it applied

You'll follow a real-world initiative through all four phases and see every deliverable along the way: opportunity briefs, charters, evaluation plans, readiness checklists, rollout plans, and monitoring dashboards.

Make it stick

The course closes with concrete steps for your first week and first month, and the four traps that catch teams adopting a new framework.

No coding required. The framework works alongside the methodology you already use (Agile, Waterfall, SAFe, or hybrid) rather than replacing it.

About your instructors

Zorina Alliata is Director of AI Enablement and AI Adjunct Faculty at Georgetown University and OPIT. She helps enterprises move AI from pilot to production, people first. Lyuba Berzin is the co-founder of DeepPlum AI, a consulting company advising small and medium business of using AI efficiently.