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Duration 7 hours
Course Outline
Discovery Prior to Development
- Addressing the failure of AI implementations during the scoping phase
- Defining discovery as a structured engineering discipline
- Establishing time boundaries and specific exit criteria for discovery
Workflow Analysis
- Observing operations in their operational context
- Documenting process flows, handoffs, and exception handling
- Conducting interviews with end-users, management, and control functions
Use Case Validation
- Applying filters for feasibility, value, and organizational readiness
- Evaluating a portfolio of solutions rather than isolated ideas
- Formally declining use cases based on documented evidence
Value Architecture and Business Justification
- Establishing baselines, benefits, and service costs
- Defining metrics acceptable to finance and audit teams
- Maintaining registers for risk, compliance, and dependencies
Commitments, Decision Gates, and Transition
- Drafting scope statements, assumptions, and exclusions
- Implementing stage gates and termination criteria
- Preparing a handover package for the build team
Requirements
- Experience in a customer-facing technical or delivery role
- Familiarity with business processes in at least one industry
- Basic spreadsheet and document skills for modeling and write-ups
Audience
- Forward-deployed engineers and solution consultants
- Presales and solution architects
- Product owners and delivery leads on AI engagements
- Transformation leads assessing an AI portfolio
