Corporate Training

AI Project Management

Lead AI portfolios, programs, and projects with confidence — based on the PMI Standard for Artificial Intelligence in Portfolio, Program, and Project Management.

A 12-module instructor-led course covering AI strategy, governance, risk, data and model lifecycle management, Responsible AI, and value realization — built for project, program, and portfolio professionals leading AI-driven change.

12

Modules

48

Learning Objectives

12

Course Outcomes

24

PDUs Available

COURSE OVERVIEW

Project Management Built for the Age of AI

AI is transforming how organizations plan, deliver, and govern projects. This course, based on the PMI Standard for Artificial Intelligence in Portfolio, Program, and Project Management, equips project professionals with the frameworks, vocabulary, and practical tools to lead AI initiatives responsibly — from business case through value realization.

Strategic Alignment

Connect AI initiatives to organizational strategy and measurable value.

AI-Specific Risk

Manage risks unique to AI — bias, drift, explainability, and privacy.

Responsible AI

Lead with fairness, transparency, and human oversight built in.

Real Business Value

Measure benefits realization and continuously improve delivery.

Who Should Attend

Built for Auditors, Advisors, and AI Practitioners

Twelve modules, each with concrete, practical learning objectives.

Common questions

Learning Objectives by Module

Foundations of AI Project Management
  • Explain the fundamentals of Artificial Intelligence and its impact on portfolio, program, and project management.
  • Differentiate between traditional software projects and AI-driven projects.
  • Describe the AI project lifecycle and its unique characteristics.
  • Understand the role of AI within organizational strategy and digital transformation initiatives.
  • Align AI initiatives with organizational vision, strategy, and business objectives.
  • Identify high-value AI use cases using structured assessment techniques.
  • Develop AI business cases and value propositions.
  • Prioritize AI initiatives within organizational portfolios.

 

  • Explain governance structures required for AI initiatives.
  • Establish roles, responsibilities, and decision-making frameworks for AI projects.
  • Apply governance practices to ensure accountability, transparency, and oversight.
  • Integrate AI governance with enterprise governance models.
  • Understand emerging AI regulations and governance frameworks.
  • Apply compliance requirements throughout the AI lifecycle.
  • Align AI projects with international standards such as ISO/IEC 42001, NIST AI RMF, and applicable AI regulations.
  • Prepare AI projects for audits and regulatory assessments.
  • Lead cross-functional AI teams effectively.
  • Facilitate collaboration between business, technical, legal, and governance stakeholders.
  • Make informed AI project decisions using data and governance principles.
  • Foster a culture of innovation, responsible AI, and continuous learning.
BY THE END OF THIS COURSE

Overall Course Learning Outcomes

Understand the principles and practices of AI Portfolio Management.
Align enterprise AI portfolios with organizational strategy and business objectives.
Govern AI investments using structured portfolio governance frameworks.
Evaluate, prioritize, and optimize AI initiatives to maximize strategic value.
Balance innovation, risk, compliance, and resource allocation across AI portfolios.
Measure and realize business benefits from enterprise AI investments.
Establish Responsible AI governance that promotes fairness, transparency, accountability, privacy, security, and human oversight.
Identify, assess, and manage enterprise AI risks using a portfolio-wide approach.
Monitor AI portfolio performance through executive dashboards, KPIs, and maturity assessments.
Lead enterprise AI transformation by engaging executives, stakeholders, and cross-functional teams.
Ensure AI portfolio compliance with international AI governance frameworks, including the PMI Standard for AI in PPM, The Standard for Portfolio Management (PMI), ISO/IEC 42001, NIST AI RMF, and the EU AI Act.
Build and sustain an adaptive, resilient, and high-performing AI portfolio that delivers measurable business value, supports responsible AI adoption, and enables long-term organizational competitiveness.

Common questions

Frequently Asked Questions

Is this course based on an official PMI standard?
  • Yes. The curriculum is built around the PMI Standard for Artificial Intelligence in Portfolio, Program, and Project Management, alongside PMI’s Standard for Portfolio Management.
  • AI Program Management coordinates a set of interdependent AI projects toward shared outcomes. This course addresses the enterprise level above that — prioritizing and governing AI investment across all programs and projects organization-wide.
  • Executives, PMO leaders, and portfolio managers who set AI investment strategy and sit on AI governance boards — often after building foundational experience through our AI Program or AI Project Management courses.

Yes. We offer private cohorts tailored to your organization’s AI investment governance model, tools, and existing portfolio structure.

Participants can reschedule to a future cohort at no charge up to 5 business days before the start date. Contact our training team for details specific to your enrollment.

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Ready to Train Your Team?

Tell us about your organization’s AI governance and AI delivery goals, and we’ll put together a corporate training proposal.