Lesson 3.1: Planning and Execution

1. Lesson Snapshot

Theme: Learn how to structure, schedule, and govern your AI initiatives for successful delivery
Duration: 60 minutes
Format: Mix of mini-lecture, planning poker, timeline sprint, and accountability mapping

2. Learning Objectives

By the end of this session, participants will be able to:

Define the core phases of an AI project lifecycle (planning, execution, monitoring).
Build a high-level project timeline with milestones, deliverables, and dependencies.
Apply estimation techniques (e.g., planning poker) to size tasks and allocate resources.
Map roles and responsibilities using a RACI matrix.
Identify key risks and propose mitigation strategies for each.

3. Key Concepts & Definitions

Term	Definition
Milestone	A significant point or event in the project schedule—often marking the completion of a phase.
Planning Poker	A consensus-based technique to estimate effort or complexity of tasks using numbered cards.
Gantt Chart	A bar-chart visualization of a project schedule showing start/end dates and dependencies.
RACI Matrix	A responsibility assignment chart outlining who is Responsible, Accountable, Consulted, and Informed.
Risk Register	A log of identified risks, their likelihood, impact, and planned responses.

4. Lesson Flow

Time	Activity	Format
0–10′	Kickoff Quiz: Project Phases	Quick poll on AI project steps
10–25′	Mini-Lecture: Roadmaps & Roles	Slide deck + real-world examples
25–35′	Planning Poker Sprint	Small-group estimation game
35–50′	Timeline & RACI Challenge	Teams draft Gantt + RACI chart
50–60′	Risk Radar & Wrap-Up	Dot-voting on top risks + debrief

4.1 Kickoff Quiz: Project Phases

Tool: Slido/Mentimeter or show of hands
Prompt: Sequence these phases in an AI project: Data Prep, Monitoring, Piloting, Deployment, Planning.

4.2 Mini-Lecture: Roadmaps & Roles

Content Highlights:
- Breaking a use case into workstreams (data, modeling, integration, change management)
- Examples of milestone definitions (e.g., “Data ingestion complete,” “Model validated at 85% accuracy”)
- Overview of RACI for a chatbot rollout (who trains, who signs off, who tests, who communicates)

4.3 Planning Poker Sprint

Setup:
- Each team receives 5–7 user stories/tasks (e.g., “Clean transactional data,” “Design API for model inference,” “Develop UI mockups”).
- Use numbered cards (1, 2, 3, 5, 8, 13) to estimate relative effort.
Process:
1. Read a task aloud.
2. Each member secretly selects a card.
3. Reveal simultaneously; discuss differences; converge on consensus.

4.4 Timeline & RACI Challenge

Teams of 3–4:
1. Plot the estimated tasks on a simple Gantt chart (start/end dates, dependencies).
2. Create a RACI matrix assigning roles for each major deliverable.
Deliverable: A one-page visual timeline and RACI chart.

4.5 Risk Radar & Wrap-Up

Activity:
- Each team lists the top 3 risks (e.g., “Data quality issues,” “Stakeholder buy-in delays,” “Infrastructure constraints”).
- Post risks on a shared board; use dot-voting to surface the class’s top 3.
- Quick debrief: proposed mitigation for the leading risk.

5. Reflection & Next Steps

Solo Reflection (2 mins):
- “Which phase of planning felt most challenging, and how might I overcome it?”
Peer Share (3 mins):
- Swap answers and suggest one tool or practice to ease that challenge.

6. Homework

Project Roadmap Draft:
- Using your AI Opportunity Brief (from Lesson 2.1), create:
  - A 6–8-week Gantt chart with at least five milestones and dependencies.
  - A RACI matrix for those milestones.
  - A brief risk register (3–5 risks with mitigation ideas).
- Submission: Upload to the course portal before Lesson 3.2.