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 an audit trail

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

Localising campaign copy

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

Reviewing vendor claims

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

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