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 Duration 7 hours

Course Outline

Discovery Prior to Development

  • Understanding why most AI initiatives fail at the scoping stage
  • Viewing discovery as a core engineering activity
  • Applying time-boxing and establishing exit criteria for discovery

Analyzing the Workflow

  • Observing work in its natural environment
  • Mapping processes, handoffs and exception handling paths
  • Interviewing end-users, managers and control functions

Evaluating Use Cases

  • Applying filters for feasibility, value and readiness
  • Scoring a portfolio of ideas rather than isolated concepts
  • Justifying the rejection of use cases with supporting evidence

Value Architecture and Business Rationale

  • Establishing baselines, quantifying benefits and calculating cost to serve
  • Selecting metrics that meet finance and audit standards
  • Maintaining registers for risk, compliance and dependencies

Commitments, Gates and Transition

  • Defining scope statements, assumptions and exclusions
  • Implementing stage gates and kill criteria
  • Preparing a handover brief for the development team

Requirements

  • Professional experience in a client-facing technical or delivery position
  • Working knowledge of business processes within at least one industry sector
  • Foundational skills in spreadsheets and document creation for modelling and reporting

Target Audience

  • Forward-deployed engineers and solution consultants
  • Pre-sales specialists and solution architects
  • Product owners and delivery leads involved in AI projects
  • Transformation leaders evaluating AI portfolios

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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