AI agents and copilots are now part of many project teams. This 60-minute working session on AI in project management helps project managers and team leads bring them into project execution without losing control of scope, quality or accountability.
The session treats AI as a non-human team member with real strengths and real failure modes. You'll work through the decisions a PM must own: what to delegate, what to verify, and what an agent should never decide. It stays grounded in current practice and draws on the EPM Doctrine's view of human judgment as the center of project work.
You'll leave with a simple framework for deciding, project by project, where AI belongs on your team.
WHY SHOULD YOU ATTEND?
Your team is probably already using AI on your projects. If you aren't deliberately managing what it touches, who owns its output and where human judgment is required, the AI is effectively running the project, and your name is still on the charter.
The session suits project, program and portfolio managers, Scrum Masters, agile coaches, team and technical leads, PMO leaders and business analysts on AI-augmented teams.
AREA COVERED
- What AI agents and copilots do well on projects and where they consistently fail
- The new PM role: orchestrating human and machine contributors
- Delegation decisions: agent tasks, human-judgment tasks and the gray zone between
- Verification habits: reviewing AI output without rubber-stamping or rewriting it all
- Accountability and traceability when an agent produces work product
- Status, risk and stakeholder communication with non-human team members
- Common failure patterns: over-trust, under-trust, scope drift from agent suggestions and silent rework
- A simple framework for deciding where AI belongs on each project
LEARNING OBJECTIVES
- Describe where AI agents and copilots help projects and where they fail
- Decide which tasks to delegate to agents and which need human judgment
- Review AI output with effective verification habits
- Maintain accountability and traceability for agent-produced work
- Communicate status, risk and progress when part of the team is AI
- Recognize failure patterns such as over-trust and scope drift
- Apply a framework to place AI on each project
WHO WILL BENEFIT?
- Project Managers and Senior Project Managers
- Program Managers and Portfolio Managers
- Scrum Masters and Agile Coaches
- Team Leads and Technical Leads adopting AI tooling
- PMO Directors and Project Operations Managers
- Business Analysts working on AI-augmented teams
Your team is probably already using AI on your projects. If you aren't deliberately managing what it touches, who owns its output and where human judgment is required, the AI is effectively running the project, and your name is still on the charter.
The session suits project, program and portfolio managers, Scrum Masters, agile coaches, team and technical leads, PMO leaders and business analysts on AI-augmented teams.
- What AI agents and copilots do well on projects and where they consistently fail
- The new PM role: orchestrating human and machine contributors
- Delegation decisions: agent tasks, human-judgment tasks and the gray zone between
- Verification habits: reviewing AI output without rubber-stamping or rewriting it all
- Accountability and traceability when an agent produces work product
- Status, risk and stakeholder communication with non-human team members
- Common failure patterns: over-trust, under-trust, scope drift from agent suggestions and silent rework
- A simple framework for deciding where AI belongs on each project
- Describe where AI agents and copilots help projects and where they fail
- Decide which tasks to delegate to agents and which need human judgment
- Review AI output with effective verification habits
- Maintain accountability and traceability for agent-produced work
- Communicate status, risk and progress when part of the team is AI
- Recognize failure patterns such as over-trust and scope drift
- Apply a framework to place AI on each project
- Project Managers and Senior Project Managers
- Program Managers and Portfolio Managers
- Scrum Masters and Agile Coaches
- Team Leads and Technical Leads adopting AI tooling
- PMO Directors and Project Operations Managers
- Business Analysts working on AI-augmented teams
