Workplace Scenarios
Click a scenario that interests you
AI awareness briefing for a mixed team
AI experimentation clinic
Applying AI policy in everyday work
Applying organisational AI rules before use
Assessing a new AI use case
Assessing AI competence through real work
Avoiding overconfidence in polished outputs
Building a peer learning community
Building an explanatory dashboard story
Challenging assumptions in AI analysis
Challenging shadow AI use
Checking a biased recommendation
Checking copyright in generated content
Checking representation in generated content
Choosing between AI tool types
Classifying operational information
Cleaning messy survey responses
Closing the loop on AI adoption
Coaching a cautious colleague
Connecting AI through an API
Converting a task into a prompt pattern
Creating a reusable team prompt
Creating a role-based AI learning pathway
Creating a standard team prompt workflow
Creating an accessible staff update
Creating safe synthetic test data
Defining accountability for AI governance
Designing a retrieval-augmented prototype
Designing a team workflow
Designing stakeholder communications for adoption
Developing a content campaign brief
Developing decision options
Documenting an AI system for handover
Documenting verification for auditability
Drafting a standard operating procedure
Editing AI-generated web content
End-to-end AI procurement assurance
End-to-end productivity workflow redesign
Escalating a safeguarding concern
Evaluating build-versus-buy architecture
Explaining AI use to a customer
Explaining uncertainty in an AI-assisted report
Fact-checking an AI-generated briefing
Finding safe automation opportunities
First-pass AI readiness conversation
Generating analysis questions
Generating multimedia concepts responsibly
Guiding outputs with a rubric
Handling employee data safely
Human accountability in AI-assisted decisions
Identifying AI support in routine work
Improving a customer-facing email
Inclusive AI-assisted service design
Interpreting a performance dashboard
Introducing AI to non-specialists
Lightweight agent with human approval
Maintaining assurance evidence
Making sense of vendor AI claims
Managing long context prompts
Managing reputational risk
Managing resistance after a failed pilot
Measuring productivity gains
Monitoring model performance
Narrating evidence for a board paper
Planning a complex week of work
Post-implementation benefit and risk review
Preparing for a client meeting
Preparing multilingual support material
Prompt quality improvement session
Prompting with documents and images
Quality gate for AI-assisted work
Quality-assuring high-stakes communication
Redacting sensitive information before using AI
Refining an unsatisfactory first draft
Responding to an AI near miss
Responsible AI decision checkpoint
Responsible decision-support review
Reviewing a report for unsupported claims
Reviewing generated code after an incident
Role framing for expert review
Running an AI adoption workshop
Selecting the right AI opportunity
Setting organisational AI guardrails
Simplifying technical information
Spotting data quality problems
Summarising a long meeting thread
Supporting managers as AI role models
Technical assurance before launch
Testing an AI agent workflow
Testing edge cases before use
Updating an SOP after lessons learned
Using a coding assistant on a feature
Using clarifying questions to scope work
Verifying a cited source pack
Writing a structured prompt for a report
Writing procurement requirements
Writing stakeholder messages during change
