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A customer-facing AI agent can sound natural and adapt its tone without reliably representing the company. To test whether it does, keep the business situation constant, change the person or conversational pressure, and compare what the agent decides and promises—not just how it speaks.
Why a convincing conversation is not enough
In one exchange, an agent may sound informed, personal, and on-brand. That does not show whether it will make the same business decision in a comparable exchange. A single conversation can hide shifting commitments: different follow-up dates, unapproved flexibility on terms, or a promise that depends more on how forcefully someone asked than on company policy.
Olga Belkovich, CEO and co-founder of U (in) AI, describes the distinction this way: “We’ve taught agents to sound like the company. Now we need to check whether they decide like it.” The relevant question is not only whether the answer feels appropriate. It is: “What decision did the agent make here?”
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Use a repeatable scenario review rather than relying on isolated demonstrations. Keep the facts that should govern the outcome unchanged, then vary the interlocutor or the conversational pressure. The goal is to find out whether the agent applies the company’s business rules consistently, not to make every response use identical wording.
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- Choose a realistic business situation. Define the material facts—for example, the customer’s request, relevant terms, and current stage of the interaction. Preserve those facts across versions.
- Vary how the request is made. Try a direct question, a negotiation, a mention of a competitor, or a customer who says they are ready to act immediately. Belkovich says she runs a scenario eight to ten times; that is her practice, not a validated sample-size rule.
- Compare commitments, not just phrasing. Check the decisions that matter under your company’s authority rules, such as follow-up timing, discounts, terms, and other promises. Record what changed and whether the changed facts justify it.
- Have the accountable decision owner review the outcomes. Ask the relevant founder, sales leader, commercial director, or other responsible person whether each decision was acceptable. A reviewer should distinguish justified contextual differences from a boundary that moved under pressure.
- Write down the authority rules and resolve disagreements. Define what the agent may answer directly, where it may exercise discretion, and when it must defer to a person. If company stakeholders disagree about an exception or who can approve a commitment, settle that interpretation before treating the rule as established.
What should stay stable—and what may change
Personalization can legitimately change wording, emphasis, or the explanation an agent gives. A decision may also change when a material business fact changes or an authorized rule permits different treatment. But persistence, urgency, or a competitor mention should not silently expand the company’s offer when those factors do not confer authority.
As Belkovich puts it, “What should stay stable is the company’s position, and if it shifts, there should be a business reason.” The practical standard is therefore not identical answers; it is explainable differences within explicit limits. If the agent lacks authority or the situation is unclear, a handoff is a valid outcome: “Sometimes the correct move is simply: I need to check this with a person.”
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Use the review to audit the business rules, too
In Belkovich’s example, a recruitment-agency agent sounded knowledgeable and appropriately personal, but comparisons showed it giving different follow-up timelines in similar situations and implying flexibility on terms the company had not authorized. Either response might have looked ordinary on its own. The inconsistency became visible only when similar conversations were compared.
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That review can reveal a company-process problem as well as an agent problem. If people responsible for the business disagree about exceptions, commitments, or approval authority, the agent is exposing ambiguity that already exists. Resolve those differences with the business owners; changing prompts alone cannot make an unsettled rule reliable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What this test can—and cannot—establish
Scenario comparison is a practical way to surface inconsistent decisions and unclear authority boundaries. The method described by Belkovich does not, by itself, establish a statistically validated sample size or prove a particular level of performance improvement. Treat the runs as a structured review of behavior, not as a universal statistical test.
Audience simulation is a different kind of exercise. Ask Rally describes custom AI personas and polling to compare reactions to content variations across audience segments; its page characterizes results as directional and recommends validating important findings with behavioral methods such as A/B tests or sales data. That may help explore audience responses to messaging, but it does not establish whether a deployed customer-facing agent consistently honors real-world commitments. The two approaches answer different questions: simulated reactions to variations versus an agent’s decisions and authority boundaries in comparable situations.
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