AI for Project Managers: Plan, Report, Stay Accountable

What's inside

1. Level 1: What AI Can and Cannot Do for a Project ManagerFree
   Learners sort project management tasks into those AI assistants handle well, those they handle badly and those that must stay human, using dated evidence from published surveys of how the profession is using AI.
2. Level 2: Choosing Approved Tools Under Workplace PolicyFree
   Learners find out which AI tools their organisation permits, and tell consumer chat tools apart from enterprise versions such as Microsoft 365 Copilot, ChatGPT, Gemini and Claude business plans by how each handles data, retention and training.
3. Level 3: UK GDPR, Confidentiality and What Never to Paste
   Learners apply UK GDPR principles and client and commercial confidentiality duties to decide what project information may go into an AI tool, and how to anonymise or summarise content that may not.
4. Level 4: PMI and APM Guidance: Accountability Stays Human
   Learners review what PMI and APM currently say about AI in project management, ethics and professional conduct, and turn that guidance into a personal rule: AI may draft and analyse, but the project manager owns every decision and deliverable.
5. Level 5: From Rough Requirements to Scope and WBS
   Learners use a structured prompt to turn messy requirements notes into a draft scope statement and work breakdown structure, then check both for gaps, gold-plating and assumptions the AI invented.
6. Level 6: Drafting Schedules and Sanity-Checking Estimates
   Learners use AI to propose activity sequences, dependencies and draft durations from a WBS, then challenge the estimates against historical data, team capacity and three-point reasoning instead of accepting them.
7. Level 7: Risk and Issue Logs and AI-Assisted Pre-Mortems
   Learners use AI to widen risk identification and run a pre-mortem, then write well-formed risk statements and keep probability, impact and ownership decisions with people.
8. Level 8: Stakeholder Maps and Communication Plans
   Learners use AI to draft a stakeholder map and communication plan from anonymised inputs, and keep sensitive judgements about influence, attitude and politics out of the tool.
9. Level 9: Meeting Notes, Decisions and Actions
   Learners use AI transcription and summarisation, such as meeting recap features in their approved tools, to capture decisions and actions, then check the record against what was actually agreed before circulating it.
10. Level 10: Status Reports and Dashboards That Tell the Truth
    Learners use AI to draft status reports and dashboard commentary from verified project data, while guarding against optimistic spin and making sure each RAG rating rests on evidence.
11. Level 11: Change Requests and Impact Analysis
    Learners use AI to structure a change request and draft its impact analysis on scope, schedule, cost, risk and benefits, then check it against the baseline and leave approval to the change authority.
12. Level 12: Lessons Learned That Change Behaviour
    Learners use AI to group retrospective and lessons-learned inputs into themes and turn them into specific, actionable recommendations, while keeping individuals' feedback anonymised.
13. Level 13: AI Features in Jira, Asana, Monday, Planner and Project
    Learners survey, in outline and checked against current vendor help pages, the AI features built into major project tools, and judge when built-in AI suits a task better than a general-purpose assistant.
14. Level 14: Checking Accuracy, Bias and Made-Up Facts
    Learners apply a repeatable verification routine to any AI-assisted project artefact, catching invented facts, faulty calculations, missing context and biased framing before the artefact is shared.
15. Level 15: Disclosure and Honesty About AI Use
    Learners decide when and how to say they used AI in project work, in line with organisational policy, client contracts and professional codes, and write clear, proportionate disclosure wording.
16. Level 16: Governing AI Use in Regulated Projects
    Learners set up proportionate controls for AI use on projects in regulated or high-assurance settings, such as public sector, financial services, healthcare and defence, covering audit trails, approvals and record-keeping.
17. Level 17: Using AI to Deepen Your Own Expertise
    Learners use AI as a tutor and sparring partner (explaining methods, quizzing them and critiquing their own drafts) so that their professional judgement grows instead of being handed off to the tool.
18. Level 18: Final Challenge: Your Role, Your 30-Day Plan Exam
    Learners bring the whole course together by running one project scenario safely from scope to status report with AI. They also prepare a conversation with their manager and colleagues, give an honest view of how the role may change, stating the uncertainty, and commit to a personal 30-day plan.

Access

The first 2 levels are free with a free account. Every level, the podcast edition and the AI tutor come with All Access at £4.99/month or any Creator plan — see pricing.

Start free →