By Markus Kopko
August 28, 2025
This series at a glance:
- The Shift Begins
- Strategic AI in Portfolio Management
- Operational AI in Portfolio Management
- Strategic AI in Program Management
- Operational AI in Program Management – you are here
- Strategic AI in Project Management
- Operational AI in Project Management
- Human plus AI Partnership – ethics, maturity and next horizons
At the heart of every successful program lies one powerful but fragile asset: alignment.
Alignment across projects. Alignment across stakeholders. Alignment between intent and execution. Such alignment is constantly under pressure—from shifting priorities, competing interests, resource conflicts, and unforeseen risks. Operational AI earns its keep—not by enforcing order, but by enabling clarity in complexity.
The Problem: Too Much Signal, Too Little Insight
Program managers juggle more noise than almost any role in the organization: dozens of stakeholders, parallel project updates with inconsistent granularity, and a flood of emails, chats, and meeting notes. Delays and issues ripple unpredictably across interdependencies.
Traditionally, program operations rely on instinct, memory, and relentless manual coordination. AI changes the game by offering contextual intelligence at scale.
What Operational AI Can Do
AI doesn’t replace the program manager. It’s their personal radar system — sensing, highlighting, and clarifying across the entire program landscape. Here’s what Operational AI in Program Management looks like in practice:
- Stakeholder Sentiment Analysis. NLP (Natural Language Processing) tools parse communication channels across the program (with appropriate privacy controls) to identify early signs of stakeholder disengagement, escalation, or misalignment. Trends are visualized as “engagement health” scores, flagging risks before they derail a key workstream.
- Use Case: A key sponsor’s tone turns increasingly critical over three sprints. The AI flags a drop in sentiment, allowing the program lead to engage proactively—before tensions explode.
- Cross-Project Risk Synthesis. AI ingests risk logs, progress updates, and change requests from all constituent projects. It then identifies systemic patterns: recurring vendor delays impacting multiple teams, cross-cutting resource shortages, or emerging architectural dependencies that no single project manager can see.
- Use Case: Three teams report seemingly unrelated blockers. AI recognizes they all stem from the same upstream platform change—and escalates it as a significant, program-level risk.
- Meeting & Action Item Intelligence. AI captures unstructured notes from program-level meetings like steering committees or architectural reviews and extracts follow-ups, owners, and deadlines. It cross-references these with project boards to track execution.
- Use Case: A discussion in a steering committee leads to four action items affecting different teams. One is silently dropped. AI flags it a week later when no corresponding activity is detected.
- Dependency Mapping & Visualization. AI analyzes tasks, milestones, and deliverables across project teams to surface hidden or under-documented dependencies between them. It builds dynamic maps of who relies on what—and when—instantly updating risk and timeline implications for the entire program when one stream changes.
The Human Role in Operational AI
AI doesn’t manage relationships. It highlights where attention is needed. For program managers, this means shifting from:
- Coordination → to prioritization
- Information gathering → to intervention timing
- Status management → to systemic foresight
To fully benefit, program managers must trust the AI’s signal—but verify the meaning, balance objective insights with human nuance, and translate complex dynamics into actionable communication.
What to Watch Out For
Operational AI is only as good as the system it observes. Be aware of shadow workflows, where unofficial tools make team activities invisible to AI. Tune systems carefully to avoid “over-alerting” which leads to signal fatigue.
Most important, ensure stakeholders feel supported, not watched. It shouldn’t feel like surveillance. It should feel like support.
Your 'Pain-to-Prompt' Converter
Take your biggest coordination challenge and run it through this 3-step converter:
- Pinpoint the Pain. Name your #1 recurring coordination headache (e.g., “I never know if Team A’s delays will impact Team B’s critical path until it’s too late”).
- Quantify the Cost. What’s the real cost of this friction—in rework, missed deadlines, or eroded stakeholder trust?
- Formulate the AI Prompt. Now, translate the pain into a precise question for an AI co-pilot. Instead of a vague wish for “better tracking,” the prompt becomes: “Continuously scan the boards of Project A and Project B. Alert me the moment a task in A is flagged as ‘at risk’ AND is a dependency for a key milestone in B scheduled within the next 14 days.”
This act of precise formulation is the first step toward intelligent automation.
Up Next: Strategic AI in Project Management: Reimagining Planning, Governance, and Decision-Making
Coach, Speaker & Trusted Guide for Human-Centered PM Excellence
Markus Kopko is a seasoned expert in project, program, and portfolio management with over two decades of experience in shaping strategic transformation across industries. As Principal Consultant, founder of „MP4PM – Method Power for Project Management“ – (www.mp4pm.club ) – and content creator, he has supported countless professionals on their journey toward PMI certification (e.g. PMP, PgMP) and practical excellence in applying global standards (e.g. PMBoK Guide, ITIL etc.) in their daily work.
A trusted advisor and international speaker, Markus served on the PMI Review Team for the PMBOK® Guide – 7th Edition, contributes to the Core Development Team of the upcoming PMI Standard on AI in Project, Program, and Portfolio Management, and regularly publishes thought leadership content on integrating modern methodologies with real-world delivery.
Markus specializes in strategic program management, lifecycle governance, stakeholder alignment, and benefits realization. He is widely recognized for translating complex frameworks into actionable practices, helping organizations align execution with strategic intent – especially in AI-driven environments.
He holds certifications including PMP®, PgMP®, and is also a Certified AI Transformation Lead (C-AITL by USAII). Markus shares his expertise through global PMI communities, keynote contributions, and coaching – always with one core principle: Lead with empathy. Empower with trust. Show up human — every single day.“
