• Publication

The Standard for Artificial Intelligence in Portfolio, Program and Project Management

Project Management Institute275pages

The first and only global AI Standard for Project Professionals, built to turn AI uncertainty into structured, responsible practice.

Publication Type
PMI Standard

Overview

AI is changing how project-based work is planned, governed and delivered. Yet many organizations are adopting AI faster than they can align on how to use it responsibly and effectively.

The Standard for Artificial Intelligence in Portfolio, Program and Project Management helps close that gap. As the first and only ANSI-approved AI standard for the project profession, it provides a practical framework for moving from ad hoc AI use to more structured, accountable practice.

Created for Project Professionals, PMO leaders, executives and organizations adopting AI, the standard addresses two connected needs: using AI in project-based work and managing AI-driven initiatives. It helps organizations strengthen governance, manage risk and support value delivery as AI becomes more central to how work gets done.

Technology-agnostic by design, it is built to remain relevant as AI tools, platforms and capabilities continue to evolve.

It includes:

  • Eight guiding principles that shape responsible AI behaviors and decisions
  • Five performance domains that define key areas of practice for AI-enabled work 
  • Human-in-the-loop practices for reviewing and acting on AI outputs
  • Ethical and legal guardrails, including considerations for regulations, IP, audits and contractual obligations
  • Lifecycle and tailoring considerations for AI-driven initiatives
  • Applied use cases across portfolio, program and project management

 

 

Product Specifications

Pages

275

Publisher

Project Management Institute

What You'll Learn
Apply AI with greater structure and confidence
Understand how AI can support planning, analysis, decision-making, delivery and oversight across project-based work.
Use guiding principles to shape better decisions
Learn how eight principles can help teams consider strategic value, risk, governance, people, ethics, stakeholders, optimization and data quality when applying AI.
Work across five performance domains
Explore how the performance domains help structure work across stakeholder expectations, scope, architecture, strategy execution and risk.
Keep people at the center of AI-supported decisions
Learn how human-in-the-loop practices help teams review AI outputs, determine what requires escalation and decide when to accept or override recommendations.
Navigate ethical and legal considerations
Understand how to account for ethics oversight, regulations, accountability, intellectual property, audits and contractual obligations when applying AI.
Tailor AI practices to your environment
Apply lifecycle and tailoring considerations across predictive, adaptive and hybrid environments based on your organization, team and context.
Connect the standard to real-world applications
Explore applied examples across portfolio, program and project work, including prioritization, change management and performance evaluation.

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