Why ownership matters in AI
Why ownership matters in AI
For this course, control means understanding what you are sharing, what you can export, who can act and how you can stop or change a workflow.
No tool or business process is automatically risk-free, dependency-free or guaranteed to pay for itself. Provider terms, costs, data access and migration effort need to be checked for your situation.
List the information it needs and the actions it can take. Start with the smallest access scope that supports the task. Keep private information out of a public prompt or form unless you have permission and an appropriate way to handle it.
Keep the source material, requirements, decisions and review results where you can retrieve them. Check the export options for the services you use. Having an export is helpful, but it does not mean moving to another service will be immediate or cost-free.
Drafting a message is different from sending it. Proposing a change is different from publishing it. Decide who approves consequential actions and what evidence they need before approving.
Name who receives an error, how an action can be retried safely and what the team does while a service is unavailable. Test a small workflow before depending on it for customer commitments.
Pick one tool in your workflow. Write down its purpose, access, recurring cost, export path and fallback. Mark anything you have not checked as an open question. Resolve the most consequential gap before expanding the workflow.