YOUR OBJECTIVE COMES FIRST
Field note preparation
Move a selected AI use case into work people can manage.
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 ↗01Define an operating boundary
Document which input starts the workflow, what output it creates and where human judgment remains necessary. Name the actions it is allowed to perform. A draft suggestion, a saved record and a customer-facing decision need different approval and recovery arrangements.
02Test quality with representative work
Use accepted examples, incomplete inputs and difficult exceptions to evaluate the selected capability. Review factual support, required-field accuracy and appropriate escalation. Keep evaluation examples and release decisions so a model or prompt change can be assessed against the same expectations. Working example: A structured draft beside the original notes.
03Connect failure handling to an owner
Record processing states, meaningful error details and an accountable support route. Set bounded retries for temporary failures and protect against duplicate submissions. Staff need to distinguish work that has completed from work still waiting for review or recovery. For distributed field-service scheduling, agree how field coordination, service specialists and site contacts contribute where those functions are involved.
04Make adoption part of the release
Introduce the workflow to a defined user group with role-based guidance and a way to report corrections. Measure use alongside review effort and output quality. Training should show when to challenge the result, not simply where to click. Review check: Reviewers can see omissions and approve the final record.