Strategy
Workflows
How to add approvals, escalation paths, and safeguards without slowing the entire workflow down.
Human review is often treated as a temporary safeguard that will eventually disappear. In practice, it is a core part of many reliable AI-assisted workflows. The challenge is deciding where review adds value without requiring people to check every action the system performs.
Define What Requires Approval
Start by identifying decisions that carry meaningful risk. These may include sending external communications, changing customer records, approving financial actions, handling sensitive data, or making recommendations that affect people.
Low-risk tasks, such as formatting information or generating an internal draft, may not require the same level of oversight. Review should be based on the consequence of an error rather than applied equally to every output.
Create Clear Review Points
Human review works best when it is built into the workflow rather than added as a separate manual process. Reviewers should receive the proposed result, the relevant source information, and a clear set of available actions.
For example, they may approve the output, edit it, return it for additional processing, or escalate it to another team. The system should make the reason for review immediately understandable.
Use Confidence and Exceptions
Not every item needs to be reviewed. A system can route uncertain, incomplete, unusual, or high-impact cases to a person while allowing routine cases to continue automatically.
This approach helps teams focus their attention where it is most valuable. It also prevents review queues from becoming another operational bottleneck.
Learn from Reviewer Actions
Human corrections provide useful information about where the system is failing or where workflow rules remain unclear. Track common edits, repeated rejections, and frequently escalated cases.
These patterns can reveal missing context, weak instructions, poor data quality, or a need to redesign the process itself.
Human review should not feel like a safety layer placed on top of automation. It should be a deliberate part of the system, with clear ownership, useful context, and defined decision boundaries.
