Protect your data
Which tools are approved, what can and cannot go into them, why personal accounts are a risk, and how company accounts keep data out of model training.
Workshop · For everyone who uses AI at work
A practical session that turns occasional users into confident ones: what you can and cannot put into AI, how to get answers you can rely on, and the techniques power users use every day.

Most AI risk and most wasted effort come from the same few habits. Fix those and adoption takes care of itself.
Which tools are approved, what can and cannot go into them, why personal accounts are a risk, and how company accounts keep data out of model training.
A six-step way to brief AI, reusable instructions, projects and skills, and how to turn a one-off success into something the whole team can use.
Why AI gets things wrong, how to ask for sources and check them, when to keep a human in the loop, and how to spot a confident wrong answer.
The agenda
Real examples of AI saving days of work, and real examples of it inventing facts, leaking data and producing off-brand content.
Approved tools and accounts; customer, employee and financial data; confidential documents; and a simple traffic-light test for what goes in.
The six-step prompt (role, task, context, examples, format, checks), then hands-on practice on each person's own work. Saving what works as reusable instructions, projects and skills.
Asking for sources and following them, cross-checking numbers, working from your own documents rather than the model's memory, and when a human must sign off.
How to share good tools with colleagues, champions and lunchtime sessions, the company AI policy in six points, and questions.
The six-step prompt
The single habit that most improves results. Everyone leaves with a one-page guide and their own examples.