Generative AI is most useful when paired with an organisation's own knowledge and a clear review process.
Where teams start
The most common — and lowest-risk — starting points share one thing: a person still reviews the output before it is used.
- Summarising long documents and reports
- Drafting emails, letters and announcements
- Translating and adapting content between languages
- Assisting developers with code and documentation
Grounding answers in your knowledge
General-purpose models know a lot about the world but nothing about your policies or products. Retrieval — searching your own documents and giving the model the relevant passages — lets it answer with your information and cite its sources.
Guardrails that make it dependable
Impressive demos become dependable tools when a few safeguards are designed in from the start:
- Source citations so users can verify answers
- Human review for anything public or high-stakes
- Access controls so people only see what they're allowed to
- An evaluation set to test quality before every change
Measuring success
Define what good looks like before you build: time saved per task, accuracy on a test set, or user satisfaction. Measuring from day one turns opinions into evidence.
Key takeaways
- 01Start with tasks where a person reviews the output
- 02Ground answers in your own documents
- 03Design guardrails and evaluation in from day one
