Data boundaries
Define what instance data can be read, what context can leave the platform, and which information should never enter an external AI workflow.
// GOVERNANCE FOR SERVICENOW DEVELOPMENTAI
AI governance for
ServiceNow development.
AI-assisted development needs more than a usage policy. ServiceNow teams need explicit data boundaries, approved access paths, review gates, and evidence of what happened before AI work can become normal delivery practice.
01Bound data
control what leaves
02Bound access
choose approved paths
03Bound action
review before change
AI POLICY / SDK CHANGE ENFORCED
REQUEST: prepare scoped application change
01EnvironmentSUB-PROD
02Data boundaryAPPROVED
03Execution pathSDK / GIT
04Human reviewREQUIRED
policy decision: allow with review
// THE CONTROL LAYER01
Policy before access.
Evidence after action.
Governance should shape how the workflow runs, not live in a document nobody checks during delivery.
Allowed execution paths
Choose approved connection modes for the task, environment, and risk level instead of giving every agent broad access.
Review before change
Keep durable application work in source control and require a human decision before sensitive or production-impacting actions.
Evidence and validation
Record what was requested, what path was chosen, what changed, and how the result was checked.
// A WORKING GOVERNANCE MODEL02
Request. Policy.
Review.
Start with a small number of rules the delivery workflow can actually enforce, then expand them as approved use cases grow.
Bound the task
Name the intended work, environment, and permitted outcome.
Choose allow, warn, or block
Apply rules before context or execution moves through the workflow.
Verify the result
Keep approval and validation with the ServiceNow team.
// GOVERN THE FIRST REAL WORKFLOW03
Set the boundary
before scaling access.
The free AI assessment identifies the most important use case, data boundary, access decision, and review point before broader AI rollout.
Take the free assessment