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Duration 7 hours
Course Outline
Discovery Prior to Development
- Understanding why most AI projects fail during the scoping phase
- Viewing discovery as a core engineering activity
- Establishing time limits and exit criteria for the discovery process
Analyzing the Workflow
- Observing processes in their actual operational environment
- Mapping processes, handoffs, and exception handling paths
- Conducting interviews with end-users, managers, and control functions
Assessing Use Cases
- Applying filters for feasibility, value, and readiness
- Scoring a portfolio of ideas rather than focusing on a single concept
- Declining use cases with supporting evidence
Value Architecture and Business Case
- Establishing baselines, identifying benefits, and analyzing cost-to-serve
- Selecting metrics acceptable to finance and audit departments
- Maintaining a register for risks, compliance issues, and dependencies
Commitments, Gates, and Handover
- Defining scope statements, assumptions, and exclusions
- Implementing stage gates and kill criteria
- Preparing a handover brief for the development team
Requirements
- Practical experience in customer-facing technical or delivery positions
- Working knowledge of business processes within at least one industry vertical
- Proficiency in basic spreadsheet and document creation for modeling and documentation
Target Audience
- Forward deployed engineers and solution consultants
- Presales engineers and solution architects
- Product owners and delivery leads involved in AI projects
- Transformation leads responsible for evaluating AI portfolios
