YOUR OBJECTIVE COMES FIRST
AI use across locations
Make AI use understandable, reviewable and accountable.
Montana Commerce identifies manufacturing, agriculture and ag technology, B2B technology, life sciences, back-office operations and logistics among its key industries. A useful scoping example is distributed field-service scheduling. Follow a site reference, travel requirement and task-readiness checklist through the work with field coordination, service specialists and site contacts. A scheduled visit can fail if equipment access or required parts are not confirmed before travel. Which readiness checks must be complete before a field visit is scheduled?
Montana Department of Commerce: industry context ↗01Inventory intended use and authority
Identify tools, users, inputs, outputs and any external actions. Distinguish experimentation from a workflow staff already rely on. Record the business owner and the decisions the system is permitted to support or perform.
02Set practical information boundaries
Define approved sources, sensitive information, access and retention expectations with the relevant owners. Check how those expectations apply in the chosen tool and integrations. A written rule should not assume technical controls exist without verification. Working example: A version register and location review checklist.
03Match review to the consequences
Decide when a person must inspect evidence, approve an action or make a professional determination. Establish escalation for missing support, disagreement or unexpected behavior. Review requirements should reflect the task rather than treat every AI output as the same risk. For distributed field-service scheduling, agree how field coordination, service specialists and site contacts contribute where those functions are involved.
04Maintain evidence as the workflow changes
Keep use-case records, representative evaluation results and change decisions. Assign responsibility for prompt, source and permission updates. Give staff a way to report incidents and corrections so lessons reach the people who can change the workflow. Review check: Release evidence covers material local variations before expansion.