AI sales coaching software is a tool that listens to every sales call, scores it against a rubric, shows the rep what to say when a known objection comes up, and generates practice scenarios from real calls. The point is coverage: a manager hears 2% of calls, the model hears 100%. Here is what it does, how it works under the hood, and where it actually changes the numbers for an SDR team.

A definition in one paragraph

AI sales coaching software turns call audio into coaching. It transcribes the call, compares what happened with a set of behaviours you have defined as "great", and returns three things: a score with evidence, a suggestion for the rep, and a signal for the manager about who needs help on what. Some tools also act during the call, with a short prompt on screen, and before the call, with roleplay. The manager stays in the loop. The software decides what the manager looks at.

The three jobs it does

1. Score every call

Post-call scoring is the base layer. Each call gets a grade per criterion: did the rep open with a trigger, ask before answering the objection, ask an open question, propose a concrete next step. The score is useless alone. The evidence line ("prospect said 'send me an email' at 0:42, rep answered 'sure' and ended the call") is what a rep can act on.

2. Prompt the rep live

During the call, the model watches the transcript for triggers: a specific objection, a competitor name, a pricing question. When it finds one, it shows one line. Not a battlecard, not a paragraph. A good live prompt arrives within two seconds and is read in one. Anything longer is ignored, because the rep is talking.

3. Drill the gap

Roleplay is the practice layer. The useful version takes last week's real objections from your transcripts and lets a rep rehearse them against a simulated buyer before the 10am block. The generic version offers a "skeptical CFO" persona from a library. The first shortens ramp. The second entertains.

How it works under the hood

Four components, in order.

1. Speech-to-text. The call is transcribed in near real time. This is where most tools fail for European teams: accuracy on French, Spanish or German cold calls over a mobile line is noticeably lower than on an English demo recorded on a headset. Test it on your own calls before anything else.
2. Rubric. A list of criteria with rating levels and examples. The model is only as good as the rubric, and the rubric should come from your top reps' calls, not from a template.
3. Scoring model. A language model reads the transcript against the rubric and returns a score and evidence per criterion. It should disagree with a human manager on fewer than one call in five; if it disagrees more, rewrite the criterion.
4. Write-back and routing. Score, summary and next step go to the CRM. The lowest-scoring criterion per rep goes to the manager's weekly list. The best call per criterion goes to the team. The winning objection answer goes into next week's prompts and roleplay.

AI coaching vs conversation intelligence vs call recording

These get sold as one thing. They are three.

• Call recording stores audio. Useful for compliance and the occasional dispute. Nobody listens to a library.
• Conversation intelligence reads recorded meetings to tell leadership about deal risk and forecast. It serves the VP. It is built around 45-minute calls with a calendar invite, and often does not see a 90-second cold call made from a dialer.
• AI sales coaching exists to change what the rep does on the next call. It serves the rep and the first-line manager. For SDR teams it has to live in the dialer, because that is where the calls are.

Some platforms do two of the three. Ask which call types they were built for before asking about features.

Where it changes the numbers

Coaching software does not raise connect rate. In our benchmark of 1,000,000 B2B cold calls in France the average is 11.3%, and it is driven by list quality, caller ID reputation and time slot (4pm connects at 15.8%, 8am at 9.8%). No prompt fixes that.

What it moves is conversation-to-meeting, and the levers are known. 65% of reps open by explaining what they sell; trigger-based openers reach a 7-10% meeting rate versus 2-3% for pitch-first ones. Discovery questions starting with "how" lift conversion by 190%. Asking "What do you mean?" before answering an objection lifts it by 197%. A scorecard that grades those four behaviours, and a prompt that reminds a rep of the third one at the right second, is where the software earns its seat price.

The public data points the same way. In the State of Sales Coaching survey by Aircall and MySalesCoach, only 27% of reps hit quota, 38% say they are rarely or never coached, and reps who rate their coaching as excellent are about 50% more likely to hit target. Coverage is the problem the software solves.

How Sonik approaches AI sales coaching

Sonik builds the three jobs into the dialer rather than into a separate tool. Every call is transcribed in French or English, scored against a rubric that defaults to the four behaviours from our benchmark, and summarised in three lines written to the CRM.

During the call, a one-line prompt appears when a known objection is detected. The prompt text comes from answers that scored well on your own team's calls, so it changes as your top reps find better responses. Managers get a weekly list of calls to open, by criterion and by rep, instead of a dashboard.

What Sonik does not do is replace the one-to-one. In our experience, the teams that improve fastest use the score to pick the call, and the manager to explain the why.

Conclusion

AI sales coaching software is coverage: every call scored, the rep prompted at the moment that matters, and practice built from what prospects actually said last week. It will not fix a 6% connect rate, and it will not replace your managers. This week, take three of your team's French cold calls with an objection and run them through any tool you are considering. If the transcript is right and the score matches your own judgement, the rest is workflow.