Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 7 hours
Course Outline
Discovery Prior to Development
- Understanding why most AI projects fail at the scoping stage.
- Viewing discovery as a core engineering activity.
- Defining time boundaries and exit criteria for the discovery phase.
Analyzing Workflows
- Observing work in its actual operational context.
- Documenting process maps, handoffs, and exception handling paths.
- Conducting interviews with users, managers, and compliance functions.
Validating Use Cases
- Applying filters for feasibility, value, and readiness.
- Scoring an entire portfolio rather than focusing on a single idea.
- Using evidence to reject non-viable use cases.
Value Architecture and Business Justification
- Establishing baselines, defining benefits, and analyzing cost to serve.
- Selecting metrics accepted by finance and audit teams.
- Maintaining a register of risks, compliance issues, and dependencies.
Commitments, Milestones, and Transition
- Defining scope statements, assumptions, and exclusions.
- Establishing stage gates and specific kill criteria.
- Preparing a handover brief for the development team.
Requirements
- Experience in customer-facing technical or delivery positions.
- Knowledge of business processes in at least one industry sector.
- Proficiency with spreadsheets and document creation for modeling and reporting.
Target Audience
- Forward deployed engineers and solution consultants.
- Presales specialists and solution architects.
- Product owners and delivery leads involved in AI projects.
- Transformation leaders evaluating AI portfolios.
