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Module · Whether AI helps your sellers or writes fiction

The Sales Team AI Check

AI can draft the follow-up, summarise the call, and score the deal, which either sharpens your sellers or quietly corrupts the one asset the whole company forecasts against: the CRM. A confident AI note that nobody checked becomes a fact the pipeline is built on. This module checks the five habits that keep AI a help rather than a hazard: CRM entry discipline, verification of AI notes, personalisation that is not spam, transparent forecast overrides, and coaching drawn from what the calls actually reveal.

Question 1 of 5 · CRM stays clean

Does AI keep your CRM cleaner, or is it filling it with plausible noise?

AI can auto-populate fields and log activities at scale, which is a gift if the entries are right and a disaster if they are confident guesses. The CRM is what everyone forecasts against, so a field filled by an unchecked model is a decision built on fiction. Discipline means AI drafts, a human confirms.

Question 2 of 5 · AI notes get verified

Do your reps check AI call summaries before they become the record?

An AI notetaker can mishear a maybe as a yes, invent a commitment, or miss the objection that killed the deal. Once that summary is saved, it is what the next rep, the manager, and the forecast believe. Verification means the human on the call corrects the summary before it becomes truth.

Question 3 of 5 · Outreach is personal

Is your AI-assisted outreach genuinely personalised, or scaled spam?

AI makes it trivial to send a thousand messages that each claim to have read the prospect's profile. Prospects recognise the pattern instantly, and it burns the brand and the domain both. Real personalisation earns a reply; volume that only looks personalised trains everyone to ignore you.

Question 4 of 5 · Forecast overrides show

When someone overrides an AI deal score, is that visible and explained?

AI deal scoring is only useful if the humans and the model stay honest with each other. A rep who quietly overrides every low score to protect commission, or a manager who ignores the model entirely, hides signal the forecast needs. Transparency means overrides are logged with a reason, so the disagreements can be learned from.

Question 5 of 5 · Calls drive coaching

Does call analysis actually improve how your reps sell, or just get recorded?

AI can analyse every call for talk ratio, objections handled, next steps set, which is a coaching goldmine or a surveillance archive depending on what you do with it. The value is in the feedback loop: patterns spotted, reps coached, behaviour changed. Analysis nobody acts on is just storage.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

How many sellers are on your team?

1 to 3
4 to 10
11 to 25
Over 25

Where does AI touch your sales process today?

Nowhere yet
Call notes and summaries
Outreach and drafting
Deal scoring and forecasting
Across most of the process

How much does your team trust what is in the CRM right now?

We trust it
Mostly, with caveats
We double-check it
We barely trust it
Hard to say

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.

What the five levels look like

Every dimension in this assessment is scored 1 to 5. This is what the levels mean, dimension by dimension. The graded report diagnoses where your own answers land and what to do about it.

CRM stays clean

  1. 1Auto-fills unchecked
  2. 2Noise accumulating
  3. 3Cleaned occasionally
  4. 4AI drafts, human confirms
  5. 5Confirmed and audited

At the low end: AI auto-filling your CRM unchecked is polluting the one dataset the whole company plans against. Require a human to confirm AI-entered fields before they count. What good looks like: AI drafting and a human confirming keeps the CRM an asset instead of a liability. Audit a sample regularly; confirmation habits slip quietly when quotas are tight.

AI notes get verified

  1. 1Saved unread
  2. 2Trusted blindly
  3. 3Skimmed sometimes
  4. 4Verified before saving
  5. 5Verified and corrected

At the low end: Unread AI summaries become the official memory of calls nobody actually recorded accurately. Have the rep who was on the call read and fix the summary before it saves. What good looks like: Verified and corrected summaries mean your call record reflects what happened, not what the model guessed. Keep the habit as volume grows; the temptation to trust a good-looking summary rises with the call count.

Outreach is personal

  1. 1Mass-blasted
  2. 2Fake personalisation
  3. 3Lightly tailored
  4. 4Genuinely personalised
  5. 5Personalised and quality-gated

At the low end: Mass-blasting AI messages torches your domain reputation and your brand at the same time. Slow down and tailor outreach to something real about the prospect. What good looks like: Genuinely personalised, quality-gated outreach is the version of AI leverage that earns replies instead of blocks. Keep watching reply and complaint rates; the line between tailored and templated moves as prospects wise up.

Forecast overrides show

  1. 1Overridden silently
  2. 2No one tracks it
  3. 3Sometimes noted
  4. 4Overrides logged
  5. 5Logged with reasons, reviewed

At the low end: Silent overrides of AI scores hide exactly the disagreements the forecast should surface. Log every override so the gap between rep judgement and model gets seen. What good looks like: Logged overrides with reasons, reviewed, turn every disagreement into a lesson for both the reps and the model. Watch for reflexive overriding; a rep who overrides everything is telling you they do not trust the score.

Calls drive coaching

  1. 1Not analysed
  2. 2Analysed, unused
  3. 3Reviewed occasionally
  4. 4Feeds coaching
  5. 5Drives measurable improvement

At the low end: Call analysis you never act on is a recording nobody learns from. Pull one pattern from it this month and coach a rep on it to start the loop. What good looks like: Analysis that drives measurable improvement is the difference between a coaching tool and a surveillance tape. Keep the focus on developing reps, not just monitoring them; the trust that makes coaching land is easy to lose.