FreezePoints eMagazine

On Tuesday, August 12, 2025, Chris Leonard, Owner and Principal Coach & Consultant at No Impediments,  ran a clear, no-nonsense webinar for PMI Orange County called “Landscape of AI Tools.” It was practical, fast, and focused on what project managers can actually do with AI today: cut busywork, improve estimates, and amplify impact.

Below are the straight-forward takeaways.

Play with the tools
AI is changing quickly. There are lots of competing products “like Coke and Pepsi,” so the fastest way to learn is to try a few yourself. Don’t chase every shiny thing. Pick one small task you already do (summarize meeting notes, draft a slide outline, run a quick risk scenario) and spend 30–60 minutes testing a tool. Build muscle memory.

Protect your data
Don’t paste sensitive or proprietary information into tools unless they’re set up to protect it and IT has signed off. Companies are embedding AI into products to increase profits. It’s important to know how your tools handle data before you feed them anything confidential.

Prompt engineering — basics that work
Good prompts aren’t magic. Leonard’s checklist:

• Be clear and specific — tell the model exactly what you want.
• Give context — background matters.
• Use structured formats — ask for lists, tables, templates.
• Experiment and iterate — tweak the prompt until it works.
• Set constraints — word counts, tone, formatting rules.
• Ask for multiple options — don’t settle for the first draft.

Find patterns that work and reuse them as your internal playbook.

Three practical roles for AI
Leonard grouped AI use cases into three roles you can start using today.

1) Project planner

• Photo-to-text and document ingestion: turn scanned docs into usable data.
• Charter writing: use a stable format, give a strong example + why it’s good, then feed in your data.
• Risk monitoring: have the tool scan docs and surface potential issues.

2) Co-facilitator

• Use AI to pick the right workshop format based on outcomes, audience, and constraints.
• Generate agendas, slide drafts, presenter notes, even suggested anecdotes.
• Combine AI with Miro/Mural to speed ideation.
  Leonard showed how to turn an “amazing idea” into a deck: outline → slide text → presenter notes → anecdotes → bundle into a mega-prompt and let the tool produce a first draft.

3) Problem-solver

• Risk mitigation: feed the AI the risks and milestones (yes, the “dirty laundry”) and ask for mitigations.
• Time & budget: use historic spend data to summarize performance, spot trends, and propose mitigations.
• Date forecasting: model delivery using past velocity, cycle time, throughput, feature breakdowns, past estimates, and team size.
  AI helps most when it’s grounded in your past data and you validate its outputs — it’s a tool, not a crystal ball.

Transcription and meeting automation
Transcription is a low-risk, high-reward win: searchable, shareable meeting records, better accuracy, and multi-language support. It saves time and makes meetings more accessible.

Watch for hallucinations — verify
AI can invent answers. Fact-check outputs against source docs or subject matter experts. Ask models to show assumptions, cite sources, or walk through logic step-by-step to make verification easier.

Final note
Use AI to offload tedious work so you can focus on the human, high-value parts of project leadership. As Leonard put it: help people do big things,  then let the tools make your life easier and amplify your impact.

Remember, start small: pick one project task, try a tool, and see what it saves you.