By Markus Kopko, PgMP®, PMP®, PMI-CPMAI™
May 13, 2026
PMI’s forthcoming The Standard for Artificial Intelligence in Portfolio, Program, and Project Management marks an important step toward defining practical guidance and governance of the profession. The ANSI-mandated public comment period has closed, and the Standard is now moving toward publication.
As a member of PMI’s Core Development Team for the Standard, I cannot share specific content before publication. What I can share is why the Standard matters, what it signals about the future direction of the profession, and how project professionals can prepare for the key themes and changes it is expected to address.
This article offers a practitioner’s perspective on what the development of the Standard reveals about the future of AI in project, program, and portfolio management.
Why a Standard, And Why Now
PMI publishes standards when a practice area has matured enough to require shared vocabulary, common principles, and professional accountability. The decision to create an AI Standard for PPPM is itself a signal: AI in project management is no longer experimental. It has reached the threshold where the profession needs a framework for responsible, effective adoption.
Consider the progression. Three years ago, AI in PM was a conference topic. Two years ago, it became a tool conversation. Today, McKinsey’s 2025 global AI survey reports that 88% of organizations use AI regularly in at least one business function (McKinsey & Company, The State of AI, 2025). MIT Sloan and BCG found that agentic AI reached 35% organizational adoption in just two years (MIT Sloan/BCG, 2025). The adoption rate is no longer the issue. The governance, competence, and integration gaps are. A standard addresses exactly those gaps.
The PMBOK® Guide—Eighth Edition, already treats AI as a critical topic that impact every performance domain. The AI Standard builds on that foundation by providing a dedicated framework to guide the responsible and effective use of AI in project, program, and portfolio management.
Five Themes That Define the Direction
Without disclosing the Standard’s specific content, I can highlight five themes emerging from PMI’s public communications, the composition of the development team, and the questions being raised across the profession. These themes are grounded in real gaps and challenges already explored in the first six articles in my series.
1. AI Governance is Professional Responsibility
Article 1 in this series, AI Governance for Project Teams, argued that governance at the team level is where AI adoption succeeds or fails. The PMBOK® Guide—Eighth Edition, already includes a dedicated governance performance domain. The AI Standard confirms that AI-specific governance is not optional, not informal, or merely a best practice recommendation. It is becoming a professional expectation.
For project professionals, this means AI governance is something they are expected to understand, apply, and maintain.
2. Human Oversight is Structural, Not Aspirational
The Human-in-the-Loop principle from Article 2 is a practical requirement that the Standard must codify. As AI agents take on coordination and monitoring tasks (AI Agents in Program Management: From Coordination Tool to Decision Partner, Article 5), determining when human judgment must intervene becomes a governance design question.
A standard that addresses AI in PPPM must define the boundaries of AI autonomy and the points where human oversight is required. The profession needs this clarity because without it, accountability becomes ambiguous.
3. AI Competence Spans All Three Domains
The Standard’s scope is portfolio, program, and project management. Most AI-in-PM content focuses on project-level tasks: scheduling, risk registers, status reports. The Standard’s scope signals that AI competence must extend to portfolio prioritization, program coordination, and benefits realization—the strategic layer where AI’s optimization and forecasting patterns () have the highest-value application. These strategic layers are discussed in Article 4, The 7 AI Patterns Every Project Manager Should Know.
For practitioners holding PgMP or PfMP credentials, this is a direct signal: AI literacy is becoming a core competency across all three PPPM domains.
4. Data Readiness Underpins Everything
Every AI pattern depends on data quality. The readiness checklist in Article 6, The PM’s AI Readiness Checklist: 5 Questions Before Your First AI Integration, starts with data consistency for this reason. A professional standard that addresses AI in PPPM must address the data foundation that makes AI effective. Without it, the Standard would be describing capabilities that most organizations cannot use.
This theme connects directly to what Info-Tech’s 2024 PPM transformation framework describes: most organizations score Ad Hoc or Initial on the readiness scales that AI requires. The Standard’s treatment of data readiness will define the minimum threshold that organizations must meet before AI produces reliable value.
5. Ethics and Trustworthiness Are Not Appendix Material
The CPMAI methodology (described in Article 4) includes ethical and trustworthy AI as a dedicated module. PMI’s broader commitment to responsible AI is visible across its publications and platforms. A Standard that addresses AI in PPPM must integrate ethical considerations, from bias detection to transparency to privacy, into the core framework, not as supplementary guidance.
In the development process, ethical considerations proved more complex than anticipated, not because the principles are unclear, but because their application varies significantly across industries, organizational maturity levels, and cultural contexts. The Standard addresses this complexity. For project professionals, this means ethical AI is not an IT department responsibility. It is a delivery responsibility. The project manager who deploys an AI tool without evaluating its bias characteristics or transparency mechanisms is operating below the professional standard.
What This Means for Your Career
PMI’s Standard on AI in PPPM changes the professional baseline. Before the Standard, AI competence was a competitive advantage. Now, AI in PPPM becomes an expected competency.
A similar shift occurred with Agile practices. Once the Agile Practice Guide was published, agile literacy was no longer optional for project professionals. Organizations began expecting it. Job descriptions started requiring it. Certification exams began assessing it.
The AI Standard for PPPM will follow this pattern. Based on PMI’s historical pattern with the Agile Practice Guide, practitioners can expect AI-related questions in PMI certification exams, AI competency expectations in PM job descriptions, and organizational governance audits that reference the Standard’s framework within 12 to 18 months of publication. Practitioners who wait for publication to begin learning will find themselves catching up to a baseline that early adopters have already internalized.
The following three actions can help practitioners prepare.
First, build pattern literacy now. Review The 7 AI Patterns Every Project Professionals Should Know (Article 4) as the conceptual foundation. The CRISP framework from Prompting for Project Managers: How to Get Useful AI Output for Real PM Work (Article 3), is the operational starting point. Once you know which pattern fits the problem, CRISP gives you the prompting structure to use it. If you understand which pattern fits which problem, you are already ahead of 80% of the profession (PMI, Shaping the Future of Project Management with AI, 2023).
Second, assess your readiness. The five questions from The PM’s AI Readiness Checklist: 5 Questions Before Your First AI Integration (Article 6) map to the gaps the Standard will expect practitioners to follow. Answer them now, while addressing the gaps is a proactive career move rather than a reactive compliance requirement.
Third, follow the Standard’s publication. When it releases, read it as a practitioner, not as an academic exercise. Map it to your current projects. Identify the specific guidance that applies to your role. Practitioners who integrate the Standard into their work early will help shape how their organizations adopt AI. This follows a consistent pattern seen with Agile, earned value management, and other PMI standards, where early adopters shaped the practice.
Key Takeaways
- PMI is developing The Standard for AI in Portfolio, Program, and Project Management. The ANSI public comment period has closed.
- The Standard’s existence signals that AI in PPPM has moved from experimental to professional. Governance, human oversight, data readiness, cross-domain competence, and ethics are defining themes.
- AI competence is becoming an expected professional capability, not an optional specialization. The progression mirrors what happened with agile practices after the Agile Practice Guide.
- Prepare nowbybuilding pattern literacy. Understand The 7 AI Patterns Every Project Professionals Should Know (Article 4), and assess your readiness (Article 6). Doing so with help you follow the Standard when it is released.
- Five themes — governance, human oversight, cross-domain competence, data readiness, and ethics—will define the AI competency baseline the profession expects from certified project professionals.
This article is part of a series leading up to the IIL webcast “5 Steps to Integrate AI into Your PPM Practices: A Tactical Blueprint” on June 24, 2026. Register at: https://www.iil.com/your-ai-advantage-practice-habit-strategy/
Markus Kopko is a strategic project and AI transformation expert with over 25 years of experience in project, program, and portfolio management. He contributes to the Core Development Team of the PMI Standard on AI in Project, Program, and Portfolio Management and served on the PMI Review Team for the PMBOK® Guide — 7th Edition. Markus holds PMP®, PgMP®, and PMI-CPMAI™ certifications and is a trainer and content creator for IIL. He delivers the course, Generative AI for Project Management, on IIL’s learning platform.
PMP®, PgMP®, and PMBOK® are registered marks of the Project Management Institute, Inc. PMI-CPMAI™ is a trademark of the Project Management Institute, Inc.
