Course Objective & Scope
In many organisations AI ideas are either too vague or built around a single tool. This course gives business teams a pattern library of what AI actually does well (classification, summarisation, information extraction, content generation, forecasting, recommendation and agent-based task execution) and teaches systematic methods for finding opportunities.
Ideas generated through value-chain scans, pain-point interviews and industry examples are structured with a use case canvas. The programme runs as hands-on workshops using examples from the organisation's own units, and each team leaves with a first-screened use case backlog.
Who Should Attend?
- Business unit managers tasked with identifying AI opportunities
- Digital transformation, strategy and innovation teams
- Process owners and operational excellence specialists
- AI champions and product managers coordinating AI initiatives
- No technical prerequisites; basic AI literacy is helpful
Key Takeaways
- Map AI capabilities to concrete business patterns
- Plan and run discovery sessions based on the value chain and pain points
- Structure ideas with a use case canvas covering problem, user, data and value
- Perform a first screening using quick value and feasibility signals
- Build a shareable use case backlog per business unit
Curriculum
AI Capabilities and Use Case Patterns
- Differences between generative AI, predictive machine learning and agents
- Summarisation, extraction, classification, recommendation and generation patterns
- Building a pattern library from industry examples
Discovery Techniques: Value Chain and Pain Point Analysis
- Scanning for opportunities along the value chain
- Customer and employee pain-point interviews
- Drawing inspiration from benchmarks and competitor practices
Structuring Ideas with a Use Case Canvas
- Problem, user, input data, output and value fields
- Defining human oversight and usage context
- Team feedback round on the canvas
Quick Screening: Value and Feasibility Signals
- Volume, repetition frequency and cost-of-error indicators
- Checking data access and availability of off-the-shelf solutions
- Red flags: unclear ownership, high regulatory risk
Use Case Backlog and Next Steps
- Backlog format and idea ownership
- Handing over to prioritisation and readiness work
- Preparing a short summary for management
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