IL 101 | Industry AI Project & Value Design
Turn an already-prioritized AI use case into a project charter, value hypothesis, measurable success criteria, and a pilot scope: a decision-ready Industry AI Project Charter. Does not repeat AD 101-103's use-case discovery, pain-point understanding, or portfolio prioritization.
Your next step
IL 101 · Module 1: From Use Case to Project Charter
Curriculum
- Module 1From Use Case to Project CharterWalk through every field of the Industry AI Project Charter, and the boundary between IL 101 and AD 101-103.
- Module 2Process and BaselineMap the current-state process, marking queueing, processing, review, and rework, and build a verifiable baseline log.
- Module 3Value and MeasurementCalculate released capacity and cost, and distinguish estimates from evidence, using a metric-card example with a deliberate error and its correction.
- Module 4Scope and ResponsibilityDefine in/out scope, dependencies, the AI/human split, and an initial data check.
- Module 5Charter WorkshopFill in Project Charter v1 from the template, exchange peer review, and complete a revision log.
- Module 6Simulated Gate ReviewAnswer sponsor-style questions and practice a proceed, reframe, hold, or stop recommendation.
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Practice and assessment
- PracticeWith guidance from cross-domain advisors and a sponsor, draft the Industry AI Project Charter for your own project.
- AssessThe charter is scored against the rubric weights; passing earns the skill certificate.
- ApplyCarry the approved project charter into IL 201, the Proof-of-Value Co-creation Lab.
About this course
Outcomes
- Bound the scope of an industry AI project
- Define a current-state baseline
- Identify strategic, business, and user value
- Define measurable success metrics
- Distinguish workflow redesign from the AI capability itself
- Define AI and human responsibilities
- Identify data, technology, governance, and organizational dependencies
- Define Go/No-Go criteria
- Produce an executive-ready project charter
Prerequisites
- AI 101L and AD 101 recommended first; AD 102 and AD 103 strongly recommended
- Equivalent professional experience may be accepted
Who it is for
- Business managers and transformation leads who need to turn a candidate use case into an investable project
- Product owners, consultants, and AI/data leads
- Project managers and industry professionals who need to lead project-chartering discussions
Certificate
Earns a capability certificate (L2).
Requirements to earn it
- Submit a project artifact and pass review
Why this course
The Industry AI Co-creation Lab brings learning outcomes into real industry problems. IL 101 is the first step: it turns one already-prioritized use case from AD 101-103 into a project charter a sponsor can read and use to decide whether to invest.
Learning and project time planning
| Formal guided hours | 6 hours |
| Estimated independent/applied project time | Not yet determined |
| Suggested real-world project span | Not yet determined |
Industry AI Project Charter
- Project title / industry-domain
- Executive sponsor / business-process owner
- Problem statement / current workflow / baseline
- Target outcome / users
- AI role / human role
- Data-context requirements / systems-integration
- Constraints / risks
- Success metrics / pilot scope
- Estimated effort
- Go/No-Go criteria
Assessment rubric weights
| Problem/scope quality | 20% |
| Value logic | 20% |
| KPI/evidence design | 20% |
| Feasibility/readiness | 15% |
| Human/AI responsibility | 15% |
| Executive communication | 10% |
Completing IL 101 moves the project to Gate 1 (the Value Gate): PROCEED TO POV, REFRAME, HOLD, or STOP.
Certificate
AI Skill Certificate: Industry AI Project & Value Design. Suggested passing score is 70/100 with all required critical controls passed; attendance alone does not earn the certificate.
Roles
- Industry sponsor: confirms the business problem, target, and success metrics, and joins key decisions
- Business/process owner: owns the affected workflow
- Cross-domain advisor: helps with framing, evidence quality, and academic standards
- AI/data advisor: assesses technical feasibility, data, and risk
- Project team: 3-5 learners
Data and privacy requirements
A charter draft may include process and data summaries provided by the enterprise. Treat it as sensitive: store it only in managed locations, share it only with authorized people, and follow the project data-retention policy. Never enter company secrets, client personal data, or unauthorized sensitive information.
Related courses and next step
Follows AD 101 (candidate use-case discovery), AD 102 (process/pain-point understanding), and AD 103 (portfolio prioritization); completion leads into IL 201.
Carry the approved project charter into IL 201, the Industry AI Proof-of-Value Co-creation Lab.
Course feedback
It takes 2 to 3 minutes and is used to improve the course.