What makes AI sales feedback trustworthy?

Tell a seller they've scored 54 for discovery and see where the conversation goes. They'll ask which moment cost them marks, who decided the criteria and whether the system understood what the buyer was trying to do. Fair questions. If you can't show the evidence, the coaching session becomes an argument about the number.

I'd be sceptical too. A transcript doesn't contain everything a manager knows about the account, the relationship or what happened before the recording began. It may miss why a seller chose to pause or why a short check-in didn't include a full discovery sequence. Treating that limited view as an unquestionable verdict is asking for trouble.

The AI spots the patterns. Your managers bring the context and make the call.

When I look at AI-generated coaching feedback, I want three things. I want to hear the relevant moment, understand the standard being applied and know who can challenge the judgement. Without those, you're asking sellers to trust a score they can't inspect.

1. 01It shows the evidence. Every point links back to the part of the conversation it is based on, so the seller and manager can listen to the moment and judge it for themselves.
2. 02It explains the standard. The criteria are written in plain words, agreed with your managers and grounded in how your team actually sells, instead of borrowed from a generic model of a good call.
3. 03It leaves room to disagree. A manager can overrule the AI with context it could not have known, and that disagreement is recorded and used to improve the standard instead of hidden.

The criteria need to reflect the actual sale. A generic framework can be a starting point, but it shouldn't become gospel. Your managers should be able to explain why a behaviour matters for your buyers and recognise it in a real conversation.

Disagreement is useful. If a manager has context the system didn't, record it and learn from it. That's how you improve the framework rather than letting everyone quietly ignore it.

AI can reduce the time managers spend hunting through recordings. That's valuable. It can highlight the calls and moments worth discussing. But the manager still has to understand the person, ask the right questions and help them practise something better.

I'd focus coaching on one specific behaviour at a time. Show the evidence, discuss the impact and agree what to try on the next relevant call. Then come back to it. That's much more useful than presenting somebody with a page of scores and hoping they work it out.

Be careful how you introduce the system. If people think it's a surveillance tool or a shortcut to performance management, they'll become defensive. Explain what is reviewed, who sees it and how the information will be used.

• Scores with no link back to the moment in the conversation they are based on.
• Criteria that nobody on your team helped to write or can explain.
• Feedback used to rank or performance-manage people before anyone has coached them.
• A single overall number that claims to capture everything about a call.
• Claims that a change in conversation scores caused a change in revenue.
• Sellers who stop recording calls because they feel watched instead of supported.

The real test is whether conversations improve, not whether the software produces a sophisticated report. If the team understands the standard, trusts the process and gets better coaching, the technology is doing its job.