How to apply human checkpoints across AI agent workflows
By Shiva Varma, Sr Director Analyst at Gartner
As organisations deploy AI agents capable of taking actions across systems, the question is no longer whether human oversight is needed, but where and when it should be applied. Human involvement remains essential for managing risk, ensuring accountability and meeting growing regulatory expectations. However, applied without discipline, oversight can quickly become a costly review exercise that slows operations without significantly improving outcomes.
The challenge for software engineering leaders is determining how human checkpoints should be integrated across AI agent workflows. Decisions about where checkpoints belong, what should trigger involvement and what actions reviewers can take have a direct impact on productivity, risk management and trust in agentic systems. Organisations that get this balance right can enable meaningful autonomy while maintaining appropriate control.
Human-in-the-loop Checkpoint Placements
A placement is where a human checkpoint sits relative to the agent’s action: before it acts, during...
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