The following is an AI summary of the event.
You can download the slide deck for this presentation at the bottom of the summary.
Overview
This webinar, part of the Agile for Project Managers MiniCon, focused on how project managers can use AI effectively without losing the human judgment, collaboration, and team engagement that make Agile work. Led by Mike Griffiths, the session examined both the promise and the risks of generative AI in project environments, especially when it is used to create plans, documents, and other delivery artifacts too quickly or too uncritically.
AI’s Promise and Its Limits
Griffiths explained that AI can be extremely useful for producing drafts, summaries, and other artifacts at high speed. He showed how generative AI can create convincing-looking project plans, schedules, and deliverables in seconds. At the same time, he stressed that these outputs are often based on incomplete assumptions, simplified training data, and generic patterns rather than the specifics of a real team, product, or delivery context. The result is that AI can create documents that look polished but may not be practical, realistic, or trustworthy without human scrutiny.
Why Team Buy-In Still Matters
A central point of the session was that the value of planning is not just the finished plan. It is the process of building the plan together. Griffiths argued that when teams are not involved in shaping ideas, debating tradeoffs, and contributing their own knowledge, they are far less likely to feel ownership or commitment. AI can generate an answer instantly, but it skips the conversation that helps a team align, challenge assumptions, and build confidence in the path forward. In Agile settings, that missing involvement can weaken execution.
Planning as a Collaborative Process
The session emphasized that planning is useful because it creates shared understanding, not because a static plan will remain accurate. Griffiths connected this idea to workshop and facilitation practices, particularly the importance of divergence and convergence: generating options, exploring concerns, narrowing choices, and agreeing on a direction together. AI can provide a fast output, but it does not replace the learning, negotiation, and resilience that come from collaborative planning.
What Research Says About AI and Thinking
Griffiths also discussed research on how generative AI affects human cognition. He cited studies suggesting that people who rely heavily on AI may remember less, contribute fewer original ideas, and become more likely to anchor on AI-generated suggestions instead of thinking independently. He described this as a form of cognitive debt: the convenience of AI can come at the cost of reduced retention, weaker creative contribution, and diminished skill if people stop exercising their own judgment.
Where AI Helps and Where Caution Is Needed
The session did not argue against AI. Instead, it drew a distinction between safer, lower-consequence uses and higher-risk uses. AI can help with things like summarizing meeting notes, overcoming blank-page syndrome, translating content, or offering prompts to expand a stalled discussion. But Griffiths warned against leaning on it too heavily for estimates, budgets, contracts, compliance decisions, backlog creation, or anything else where accuracy, accountability, and context matter deeply. In those cases, AI may support the work, but it should not drive it.
Human-First, AI-Enhanced
The practical recommendation from the session was to use a human-first approach. Start with the team’s ideas, experience, and discussion. Then use AI to test for gaps, suggest alternatives, or add perspective. This keeps the real expertise and ownership with the people doing the work, while still benefiting from AI’s speed. The goal is not to reject AI, but to use it in a way that strengthens rather than replaces collaborative project leadership.
Final Takeaways
- AI can accelerate project work, but speed is not the same as sound judgment.
- Project artifacts created without team involvement may look polished while lacking realism and commitment.
- The planning process matters because it builds alignment, ownership, and resilience.
- The safest approach is human-first, AI-enhanced: let teams think together first, then use AI to extend the conversation.
