Define your AI agent’s decision boundary first
The choice: design one decision boundary per workflow
For each workflow, explicitly decide whether the agent only gathers information, prepares a proposal, or performs an action. This distinction is necessary because NIST describes agents as systems that can plan multi-step tasks and autonomously take actions, for example using tools and databases. The same passage points out that complex multi-step workflows can be hidden behind a simple interface. Therefore, do not make the entire agent “autonomous”; instead, specify for each action which permissions apply, what outcome is acceptable, and when the task stops or is handed over to a human. The source does not state which level of autonomy is appropriate for your organization. The editorial recommendation is therefore limited: start with a task whose consequences are reversible and that has a clear checkpoint; expand only when outcomes in that workflow can demonstrably be assessed.
Make human oversight an assigned task
Human oversight is not a general final responsibility, but a specific role in a specific decision. NIST states that human roles and responsibilities in decision-making and oversight of AI systems must be clearly defined and differentiated. That source also mentions configurations ranging from fully autonomous to fully manual. Therefore, specify who reviews the output, who may approve an exception, and who may change the setup. For applications covered by the rules for high-risk AI, the European Commission further states that deployers must monitor operation, act on risks or serious incidents, and assign human oversight to one or more people in the organization. This article does not determine whether your application is high-risk; use that passage only as scope for such systems.
Use a decision card before the agent may act
Practical tool: create a decision card for one agent workflow with six fields: task, permitted autonomy level, required evaluation, supervisor, escalation trigger, and authoritative system for customer, product, or process data. Also add where the agent reads, where it writes, and which record remains the source of truth. This prevents a temporary summary or agent memory from inadvertently receiving the same status as operational data. Example: an agent may summarize a support ticket and prepare a response draft; an employee approves sending it; the evaluation checks source attribution, the correct customer context, and escalation when uncertainty arises; the ticketing system remains authoritative. Review the card when the agent receives new tools or write permissions. For each workflow, create a decision card with the task, autonomy level, required evaluation, supervisor, escalation trigger, and authoritative data system. This decision card is a design and control tool, not proof that an agent is reliable, compliant, or suitable for a specific legal, financial, or professional application. The supplied passages describe general obligations concerning agentic AI, human oversight, and high-risk systems; they do not assess any individual system, model, or data landscape.
