What are the risks of using AI for customer calls?
The main risks of using AI for customer calls are wrong or made-up answers, mishearing callers on noisy lines or with strong accents, annoying people who did not want a call, compliance mistakes around DND and consent, and over-reliance that leaves no human to catch problems. Each is manageable with a tight script, a narrow knowledge base, DND screening and someone reviewing calls every week.
The risks, and how to reduce them
| Risk | What it looks like | How to reduce it |
|---|---|---|
| Wrong answers | Agent quotes an old price or invents a policy | Keep the knowledge base short and current; tell it to say it will check rather than guess |
| Mishearing | Misses a name, number or a 'no' on a bad line | Have it confirm key details back; review low-sentiment calls |
| Unwanted calls | Calling people who never enquired or are on DND | Call only consented leads; use DND screening on bulk lists |
| Tone mismatch | Cheerful script on a payment-overdue call | Write separate scripts for sensitive situations |
| No human backstop | Complaints go unanswered because 'the AI handles it' | Have a person call back negative-sentiment calls the same day |
| Data handling | Recordings and transcripts shared too widely | Limit dashboard access; follow DPDP Act 2023 practices |
Risks people overrate
The fear that an AI will say something wildly offensive is mostly misplaced for a well-scoped business agent, which runs on a script and a defined task. The common failures are mundane: a slightly wrong answer delivered confidently, or a polite agent that cannot handle a question it was never given information about.
Risks people underrate
Scale. A telecaller who makes a mistake makes it on a few calls. An agent with a bad line in its script repeats it on every call in the campaign, as many at a time as you have channels. That is why the first day of any new campaign should be watched closely, and why script changes deserve the same care as a change to your pricing page.
Dependency is the other one. If the only record of what customers say lives in a dashboard nobody reads, you lose touch with your market. Someone senior should listen to a sample of calls every week, including incoming calls the AI employee answers on your business number.
Give the agent jobs where a mistake is cheap and recoverable, such as a missed reminder or a rescheduled visit, before jobs where a mistake costs money or trust.
Want to hear an AI voice agent handle this on a real call?
Follow-up questions
Who should review AI calls, and how often?
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Someone who knows the customers, usually a sales lead or the owner, should review a sample every week and every call flagged with negative sentiment. In the first week of any new campaign, review daily. The point is not to catch the AI out; it is to find the questions it was not prepared for and add the answers to the script.