A clip from our AI Safe Sandbox webinar (September 2025), which we also ran as the Responsible AI Roadmap webinar. Recorded in 2025: AI tools’ settings and features have changed since.
A short clip on why AI gets better with context, and why that’s the moment data safety starts to matter.
Key takeaways
- Experiment with AI and it quickly becomes obvious it lacks context, like an intern on their first day.
- Giving it data makes it more useful. The more context, the better it gets.
- People often start out unimpressed. The tool starts to shine once it has context, and that’s when you need to decide what data is safe to give it.
Try this with your team
List the three kinds of information your team most often wants to give AI for context. Which of them would you be comfortable seeing in a public chat log?
Going further
Practise the judgment call with Risky Prompt → Safer Prompt, or check a specific task with Can I Use AI for This Workflow?
More from this series
- AI Safe Sandbox Webinar, Part 1 (September 2025)
- AI Safe Sandbox Webinar, Part 2 (September 2025)
- Responsible AI Roadmap Seminar: Stoplight System
- Responsible AI Roadmap Webinar: Responsible AI Policy Language
- Responsible AI Roadmap Webinar: Good Preparation
- Responsible AI Roadmap Seminar: The Nonprofit Use Case Moment
Transcript
Lightly edited from YouTube’s automatic captions for readability. Wording and order are the speakers’ own.
As you experiment with an AI system, it quickly becomes obvious that it lacks context. I think of it as an intern on their first day. The way to make it more useful is to give it data, and the more data for context, the better it gets.
A lot of times when somebody first starts out, they’re thinking, well, what’s the big deal? When you start giving it more context is when it starts shining.