An AI agent inherits everything about the process you give it: the data, the gaps and the unclear approvals.
Before any agent goes live, three operational questions need clear answers.
1. Is the data it reads clean, current and trusted?
An agent is only as reliable as the records it reads. Duplicate customers, stale prices and conflicting reference data don't disappear when an agent arrives. They turn into confident, wrong actions.
Check: name the source of truth for every field the agent reads, and how fresh it must be.
2. Who owns each decision it makes, by name?
Auditors, regulators and customers will expect more than "the AI decided". Every automated decision needs a named person who answers for it.
Check: a RACI for the agent's decisions, the same as you would write for a new team member.
3. What may it do alone, and what always needs a human?
Define the boundary before go-live, not after the first incident. Typical splits:
- Alone: draft, classify, summarise, route.
- With approval: send to a customer, change a record, commit spend.
- Not delegated: anything that could not be clearly explained afterwards.
Check: write the approval rules as policy the platform enforces, not as guidance in a prompt.
Get these right first
With these foundations in place, agents can scale safely. Without them, existing issues tend to be automated along with the work.
Dr. Yogesh Gupta is COO of 2SD Technologies. This is part two of our leadership series on AI agents.
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