AI is improving sales efficiency, but it’s also flooding channels with low-quality communication. Learn how to use AI without eroding trust or weakening conversations.
I’m genuinely excited about what AI is doing for sales right now. It can audit calls, refine conversations, and improve close rates in real time.
But at the same time, AI-enabled outreach is flooding every channel with low-quality communication. Response rates are dropping, trust is eroding, and teams are optimizing activity instead of improving conversations.
The companies getting the most out of AI will use it to strengthen human communication, not replace it.
I had a moment a few months ago that changed how I think about all of this.
I built an AI prompt to audit sales calls, something I’ve done manually for years across thousands of calls, using a framework I’ve refined over decades.
I took that framework, broke it down into a few simple prompts that told the AI what to look for, and ran a real call through it.
It was better than me.
It was faster, more consistent, and in some cases more accurate. It picked up gaps in discovery, flagged weak qualification, and rewrote parts of the conversation in a way that would have improved the outcome, all in seconds instead of the twenty minutes it would normally take me to audit a six-minute call.
I stopped for a minute and thought about what that implies.
In professional services, a lot of what we’ve historically been paid for, experience, analysis and structured thinking, can now be replicated very quickly.
But that’s only part of the issue.
Most teams are underestimating how quickly this is happening.
It’s never been easier to generate personalized emails, LinkedIn messages, and follow-ups. With very little effort, anyone can produce a constant stream of communication in many formats.
There was a time I would respond to almost every LinkedIn message I received. Now I pause, because it’s usually obvious when something has been AI-generated instead of thought through, and those aren’t worth responding to.
The point is, buyers have adapted to AI-generated sales outreach. As more AI-generated messages show up, people become more selective about what they engage with, which means response rates drop; trust becomes harder to build, and channels that used to work don’t work the same way anymore.
We’re sending more messages than ever, but the quality of communication is getting worse.
Most teams are putting their effort into improving what happens around the conversation instead of the conversation itself.
AI is being used to audit calls, score performance, and highlight what was missed. It can rewrite recaps, tighten follow-ups, and make everything look more polished. I’m using it for exactly that, and it works.
But the quality still depends on how that conversation actually went.
Communication is now getting cleaned up after the fact, while the skill behind it stays the same.
And that skill is not trivial.
Good sales conversations require listening, judgment, timing, and the ability to ask the right question in the moment. That’s not something you outsource to a tool.
As AI becomes more capable, the question shifts to how it should be used across the sales process.
When you look at where deals are actually won, it almost always comes down to what happened in the conversations.
That’s where trust is built, where you understand what the buyer actually needs, and where decisions take shape. It requires judgment, timing, and the ability to adjust in real time, and those are the parts that don’t improve just because everything around them becomes more efficient.
If that part isn’t strong, you’re just sending messages without anything real behind them.
And buyers are tuning that out.
The opportunity is to use AI to strengthen how your team operates.
The AI model I built to audit sales calls is a good example of that. A rep can run a call through it, get immediate feedback, and adjust their recap to address what they missed, which tightens execution and reinforces better habits.
But it only works when the conversation itself is strong. When the questions are clear, the thinking is sharp, and the rep is engaging with what the buyer is saying.
AI can enhance a good process. It cannot fix a fundamentally weak one.
Sales leaders need to shift what they measure and what they coach.
If the focus stays on activity, more emails, more calls, more touches, AI will simply accelerate what’s already happening. Teams will move faster, but the quality of engagement won’t improve, and the results will reflect that.
The focus has to move to execution. That means looking closely at how conversations are handled and how deals are actually being progressed.
That shows up in:
AI can support this by tightening feedback loops and reinforcing standards across the team. It allows leaders to coach more consistently and improve performance in real time.
This is the same principle behind a strong go-to-market system. The system creates structure, visibility, and consistency, but performance still comes down to how well the team executes inside it.
AI strengthens the system. It doesn’t replace the work happening within it.
As AI takes on more of the structured and repeatable work, the gap between average and top performers becomes easier to see.
A lot of what used to take time, analysis, basic coaching, standard outputs, can now be done quickly and consistently. That shift is already happening.
What stands out now is how someone handles the conversation.
The people who perform at a higher level are the ones who can:
These aren’t new skills, but they carry more weight now because everything around them is easier to automate.
They’re also harder to develop, and easier to avoid, especially when tools can fill in the gaps and make performance look better than it actually is.
AI is quickly becoming part of how sales teams operate.
You can use it to produce more messages, or you can use it to have better conversations.
You can let it do the thinking for you, or you can use it to sharpen how you think.
AI will make you faster, more efficient, and in many cases better at executing the work around the process.
But trust isn’t built there.
It’s built in the conversation, in how well you understand what’s being said, how clearly you respond, and how effectively you move things forward.
AI can support that, but it doesn’t replace it.
That part is still on you.
Explore the research and tools designed to help you understand where your go-to-market system stands and where to focus to support growth.
Roadmap developed the Go-To-Market Readiness Index to give B2B leaders a clear, objective view of how well their go-to-market systems support growth. Through a structured diagnostic, companies can benchmark performance, identify gaps across strategy, metrics, and execution, and define where to focus next.
The 2025 GTM Readiness Benchmark Report brings together data from Canadian B2B companies to show how go-to-market systems are structured and where gaps most often appear. It gives leaders a clear view of how peers are performing, highlights common constraints, and shows where systems tend to fall short.
