• AI beyond chat: embedding into work
• Productivity vs quality trade-offs
• Where AI fits in business processes
• Examples of AI-enabled workflows across departments

Outcome:
Participants think in workflows, not prompts

• AI for:
  • Meeting notes and action items
  • Reports and executive summaries
  • Proposals and business cases
  • SOPs and internal documentation
• Structuring prompts for repeatable outputs
• Human-in-the-loop best practices

Hands-On:
Create AI-assisted meeting notes and reports

• Working with PDFs and long documents
• Extracting key insights and comparisons
• Cross-document Q&A
• Policy, contract, and guideline analysis
• Using NotebookLM for document-based intelligence

Hands-On:
Q&A and summarisation over multiple documents

• Prompt patterns for business tasks
• Creating reusable prompt templates
• Building a personal and team prompt library
• Versioning and prompt improvement

Hands-On:
Create a reusable prompt template for team use

• Using Excel with Copilot:
  • Natural language queries
  • Formula generation
  • Trend and insight detection
• Google Sheets with Gemini:
  • Data exploration
  • Charts and summaries
• Interpreting AI-generated insights responsibly

Hands-On:
Analyze a business dataset using AI-assisted spreadsheets

• Shared knowledge bases and document repositories
• Consistency and quality control
• Review loops and approval workflows
• Avoiding “AI silos” within teams

Hands-On:
Design a shared team AI workflow

• Understanding automation logic (trigger → action)
• Example flow:
  • Form → Sheet → AI processing → Email → Dashboard
• Where AI fits in automation
• When to automate vs when not to

Demo:
Simple end-to-end automation workflow

• Measuring time saved and quality improvement
• Defining success metrics
• Scaling workflows across teams

Roadmap from AI Practitioner → Automation → AI Builder