Tom Ridley has spent two decades in sales leadership and now coaches B2B sales teams through AI adoption at MySalesCoach. His view, formed across dozens of organisations in the last two years, is that most teams are not failing at AI because they chose the wrong tools. They are failing because they never decided what the tools were for.
According to MySalesCoach's 2026 State of Sales Coaching research, reps coached weekly hit quota at 76% versus 47% for those coached quarterly. The manager's job is to protect that frequency and quality. AI can help — but only when it is deployed in the right four places.
AI in sales coaching works best in four specific roles: spotting coaching opportunities in call transcripts and communications, tailoring the dynamic between coach and rep, connecting sales teams to cross-functional data from marketing and customer success, and triggering in-the-moment coaching when deal signals demand it. It does not replace the human coaching relationship. It gives coaches better information so the conversations that matter can be more targeted and more effective.
Tom Ridley, who specialises in AI-enabled sales performance and GTM transformation at MySalesCoach, sets the frame clearly:
"The managers who are handling AI well are the ones who've decided what it's for and what it isn't. The ones who are struggling are trying to use it for everything, or avoiding it entirely. Neither extreme serves the team."
AI works best as a force multiplier, a pattern spotter, and a preparation tool. It does not belong in situations that require emotional intelligence, nuanced human judgement, or the kind of trust that can only be built through genuine human connection.
Where AI Does Not Belong in Coaching
Before covering where AI helps, it is worth being precise about where it does not.
AI is strong at processing and analysing language. It cannot understand emotion, tone, internal experience, or the human context that shapes a coaching conversation. Coaching lives in nuance: the hesitation before a rep answers, the pattern of what they choose to say versus what they don't, the signal that something harder is going on beneath the surface performance issue. These things require a human in the room.
AI should not:
- Make judgements in emotionally complex situations
- Interpret a rep's motivation, identity, or personal meaning
- Decide which questions to ask in the moment of a real coaching conversation
- Replace the trust and genuine human connection that makes coaching land
The shorthand that holds up in practice: AI shows you where to look. The human coach does the work.
Want to understand more about how to measure the ROI of sales coaching? Find out more here.
The AI Coaching Stack: Four Ways to Use It Well
AI supports sales coaching in four distinct roles. Each is practical and immediately applicable. None requires replacing how coaching works — only improving the information coaches work with.
- Opportunity Spotter — AI reviews calls, proposals, and communications to surface capability gaps the manager would otherwise miss
- Relationship Dynamic Tailoring — AI reads coach-coachee patterns over time and helps both parties stay accountable to output, not just conversation quality
- Cross-Functional Data Connector — AI pulls signals from marketing, CS, and product to give reps and their coaches a fuller picture of the market they're selling into
- In-the-Moment Coaching Trigger — AI flags live deal issues so coaching happens when it has commercial impact, not just when a session happens to be scheduled
1. Opportunity Spotter
The most widely used application — and the one with the highest ceiling.
AI reviews call transcripts, proposals, slide decks, and communications to surface coaching opportunities a manager would otherwise miss. The distinction that matters most is between process compliance and capability gaps.
AI that flags "rep didn't ask about budget" is checking process. AI that identifies "this rep consistently loses momentum after the demo — the issue is in how they handle the transition to next steps" is surfacing a capability pattern. The second type is coaching data. Process checks are useful. Capability patterns are what sales coaching sessions are actually for.
"Most people think about AI as checking against sales process — which is still a good use case," says Tom Ridley. "But the real opportunity is when it starts identifying raw coaching and capability gaps, not just process compliance."
2. Relationship Dynamic Tailoring
Less obvious than transcript review, and more powerful.
Every coach-coachee relationship has its own dynamic, shaped by the temperament, style, and communication preferences of both people. AI can read those tendencies over time and help coaches work within them more effectively.
A common failure mode in coaching: conversations that feel productive but produce nothing tangible. "A coachee and coach might have really great conversations that don't always come back to a tangible output," says Tom Ridley. "AI can pick up on that tendency and hold both parties to account — making sure the conversations are still driving specific ROI, not just being enjoyable."
The same logic applies to format. A detail-oriented rep gets more from precise, systematic follow-up notes than a generic summary. A rep who just wants to run with the conversation wants bullet points, not a structured document. AI that adapts follow-ups to those preferences means the coaching actually lands — not just in the session, but in the week after it.
3. Cross-Functional Data Connector
This is where most sales organisations are leaving the most value unrealised.
Sales and marketing generate data about the same buyers, the same market, and the same conversations — from different angles. Customer success holds renewal conversations that surface objections sales teams keep hitting. Product knows what is being built and why. Historically, pulling these signals together required hours of cross-functional meetings. AI makes it accessible inside a coaching conversation.
"Sales and marketing have to work really closely together, and historically that's not always been the case," says Tom Ridley. "But why wouldn't we be hooking into what marketing is seeing and doing in the marketplace? Why wouldn't we be hooking into CS conversations with existing customers?"
The coaching implication is direct: reps who understand the broader picture sell differently.
They handle objections earlier, position more accurately, and navigate complex buying committees with more confidence. AI makes that broader picture available without requiring a cross-functional stand-up every week.
4. In-the-Moment Coaching Trigger
The traditional coaching model runs on scheduled sessions. AI changes the tempo.
The most underused capability is not what AI surfaces in a weekly session review — it is what AI flags in the middle of a live deal. An AI system that spots a particular AE is consistently missing 10 to 20% of deal value because they are not aligning value correctly inside the sales cycle has identified a right-now problem. A scheduled session three weeks from now is too late.
"I would be looking at ways that AI triggers the opportunity for me to provide coaching in the moment," says Tom Ridley. "More so than I would have done historically."
The two modes work together. In-the-moment coaching handles the tactical issue on the live deal. The scheduled session addresses the underlying behaviour — why the pattern keeps recurring and what needs to change for good. AI creates the trigger for both.
"We've never as leaders been in such a good position to have that insight on what our people are doing and how they're working than we are now," says Tom Ridley. "Coaching in the flow of work, but also spotting the opportunities for the bigger conversations — the things that will move the needle to a greater extent."
The Biggest Mistakes Sales Leaders Make With AI
The most common mistake by a wide margin: buying the licence and assuming the work is done.
Every major AI sales tool — Copilot, Breeze within HubSpot, Salesforce AgentForce, Gong transcripts — requires a culture and mindset shift to deliver value. Without it, a predictable split emerges: the people excited about AI run with it, the people who are uneasy fall behind, and the gap between them widens. The technology did not cause that gap. The absence of cultural leadership did.
"Getting the licence isn't the end of the journey," says Tom Ridley. "There is a culture and mindset shift that needs to happen within an individual, within a team, and within an organisation. The managers are the ones that need to facilitate that change."
The second most common mistake: investing in AI before diagnosing the actual bottleneck.
A question Tom Ridley hears regularly is whether sales leaders should replace their SDRs with AI-driven outreach.
The question before that question is always: what problem is this solving? What is the specific challenge in the business that this investment is addressing? AI is not the answer in itself. It may be part of the answer, once the problem is clearly defined.
Other mistakes that compound quickly:
- Delegating AI instead of learning it. The manager who does not understand the tools cannot guide how they are used across the team.
- Forcing it into every conversation. Using AI analysis for brief in-the-moment check-ins creates overhead that kills the naturalness coaching requires.
- Assuming it handles human problems. The rep who is struggling but not saying so. The emotionally complex situation. These need a human.
Keeping the Human at the Centre
The clearest signal that the human is still coaching: direct human contact.
Phone calls. Video calls with the camera on. Being fully present rather than half-focused on AI-generated notes. Asking questions that come from actually listening rather than from a pre-prepared framework. These things do not become less important because AI is in the stack — they become more important, because the rep needs to know the difference between being monitored and being coached.
A practical self-check: am I adding insight, perspective, and challenge beyond what this rep could get from a well-prompted AI? If yes, you are coaching. If everything you are offering could have been produced by anyone with access to the same transcript, that is worth sitting with.
AI is another tool in sales coaching for teams. Like a CRM or a call recorder, it serves the goal of better human conversation. It does not replace it.
Frequently Asked Questions About AI in Sales Coaching
How do I combine AI coaching with human sales coaching?
Use AI for the preparation and pattern-spotting work: reviewing call transcripts, surfacing coaching opportunities, and connecting cross-functional data. Keep the human coach in every conversation that requires emotional intelligence, trust-building, or genuine developmental dialogue. The rule of thumb is that AI shows you where to look; the human coach does the work.
Will AI replace sales coaches?
No. AI can process language and identify patterns in data, but it cannot replicate the human judgement, emotional intelligence, and trust-building that make coaching effective. What changes is how coaches spend their preparation time — not whether a human coach is needed. The coach who uses AI well will have more impact, because they spend more time on the parts of coaching only a human can do.
What is the most practical way to start using AI in sales coaching?
Start with call recording and transcript review. Use AI to surface recurring patterns — common objections handled inconsistently, stages where conversations consistently stall. Use those patterns to make coaching conversations more specific. It is a low-effort, high-signal starting point that does not require changing how your coaching currently works.
How do I use AI to prepare for a coaching session?
Review the rep's recent calls, CRM notes, and performance data before the session. Use AI to summarise what is changing and what keeps recurring. Walking in informed means you can ask better questions faster. The session itself should still follow the rep's agenda — the AI preparation makes sure you are not starting from scratch.
What should I tell my reps about how I am using AI in coaching?
Be transparent. Tell reps specifically what data AI has access to and what you are using it for. Some reps welcome AI-generated session summaries. Others are uneasy with transcription. The rep's comfort level should shape how AI is used in their coaching — surveillance and support are not the same thing, and reps know the difference.
How do I know if AI is helping or hurting the coaching relationship?
The signal AI is helping: sessions are more focused and the rep feels understood. The signal it is hurting: the rep becomes more guarded or coaching starts to feel scripted. If a rep is sharing less than they used to, check whether AI involvement has shifted the dynamic from support to monitoring.
