Use AI without losing sight of responsibility
AI is tried out quickly. Clean use in everyday work is harder. Which data is allowed? Who checks results? What needs approval? I create orientation before uncertainty or shadow processes appear.
What it is about
Safe use means creating responsible room to act, instead of blocking everything. Teams need clear answers: which tools are allowed, which data may go in, who checks, and where the human stays responsible.
Typical starting situations
People use AI, but rules are missing.
Leaders want to enable use and limit risk.
Data protection and departments do not yet speak the same language.
Results are adopted without enough checking.
Sensitive data is raised too late.
How it works
Capture usage scenarios. What AI should be used for today and in future.
Classify data and risk. From harmless exercises through anonymised examples to sensitive data.
Clarify roles and checking. Who owns inputs, who checks results, when is approval needed?
Write everyday rules. Abstract requirements become understandable guardrails.
Outcome
Understandable guardrails for AI use
Clarity on data and approvals
Check criteria for AI results
Recommendations for safe practice tasks
A basis for responsible rollout in the team
Suitable formats
Start safely: for teams that want to use AI but first need to understand rules and limits. Duration: 60 to 120 minutes.
Guardrails workshop: for departments, leaders, data protection, or project teams. Duration: half a day.
Check framework for AI results: for everyone working with AI texts, research, or assistants. Duration: 2 to 4 hours.
Method
A real task, visible proof, clear anchoring. I start with a concrete task, check the difference in everyday work, and secure the result so it can keep being used.
Next steps
A good fit after this: AI training or Orientation and strategy.
Other formats