Making Sense of AI as a Sales Leader by Ivelin Kozarev

Everyone in sales is talking about AI these days. Every product claims to be "AI-powered." Every headline says AI is changing everything. But if you’re like most sales leaders I talk to, you’re still not sure what AI actually does—or where it really helps.

The problem is that "AI" has become such a broad term that it's hard to get specific about how to use it. People throw the word around so much that it's lost its meaning.

I want to cut through all that noise. Let's look at AI from a sales leader's point of view. Not the hype, but what you can actually do with it.

What AI Is Actually Good At?

There are three main things AI can do well right now:

1. Digesting Information

AI can go through mountains of messy data—text, videos, calls, images—way faster than humans can. This isn't totally new. Computers have always been good at processing numbers quickly. But now they can handle all kinds of information.

For example, at my company, we interviewed over 100 sales leaders and then had AI find the common pain points in those conversations. A person could have done this too, maybe even a bit better. But it would have taken weeks. ChatGPT did it in 30 minutes.

2. Being an Expert When You Don't Have One

AI can do things you'd normally need a specialist for—like analysing data, setting up a complex piece of software, or forecasting—especially in areas where your team lacks the expertise.

Many sales teams don't have their own data analysts or operations support. Here’s where you can get real leverage—AI is like an expert on tap.

One of our clients used AI to analyse product usage data and flag customers who were likely to slip. No data team. No fancy dashboard. But a clear table they could act on.

Something I've noticed is that people often test AI in areas where they're already skilled, like writing important emails. That's a mistake and you will be disappointed. AI isn't going to outperform you in things you're already an expert at. Maybe it can do a first draft. But the magic happens when you use it for things you're not good at.

3. Doing the Work You Never Have Time For

AI doesn't need breaks. It doesn't get distracted or busy with other things. It's always available to work - and as team members go, it's remarkably cheap.

In sales, high-impact activities like researching prospects before a call, building detailed account plans, or tracking competitive moves often fall by the wayside. Not because they aren’t important, but because they take too much time. AI removes that limit. Ask Gemini to scan the news about your prospect before a call and give you a short summary of what's relevant. You'll walk in prepared, ready to have a deeper conversation.

At my company, we built a training platform that uses AI to create targeted role-plays based on what each rep actually struggles with. In the past, companies might do role-play with trainers once or twice a year because people were too busy. With AI you can now have the perfect practice partner available 24/7.

What People Are Using AI For In Sales

Now let's look at how these capabilities translate into actual uses. There are three main types:

1. Creating New Information

AI is great at processing huge amounts of information and extracting the important bits.

Tools like Clay let you enrich your lead data with insights from across the web. One example: summarise an annual report and pull out the perfect quote to use in your outreach—automatically, for every account on your list.

This means your team can do more personalised outreach, better meeting prep, and smarter account planning.

2. Making Sense of Your Data

You can finally unlock the value of the data your organisation generates. That means speeding up post-call work, creating a clean CRM, and spotting important signals.

A rep can feed a call transcript into Claude and ask for next steps, key objections, or deal risks—tailored to that specific conversation. They can even ask it to draft CRM updates.

Take it further. Drop in all your calls from one part of the deal cycle and ask what keeps going wrong. You’ll need a dedicated tool for the best insights, but even ChatGPT can spot patterns you’d not know.

3. Taking Real Actions (AI Agents)

The newest trend is AI that actually takes actions. These are often called "AI agents."

Examples include:

AI SDRs that handle cold outreach and follow-ups (11x, Artisian, AI SDR)

Agents that analyse your conversations and build training (Skylar)

Customer service AI agents (like Sierra, Pylon)

Many of these agents are still new, and results vary (hello, AI SDRs?). But the direction is clear, and this is only going to get better.

AI agents means execution at scale—especially for tasks where human time was the limiting factor.

What This Means For You

You don't need to become an AI expert. But understanding these two layers—what AI is good at, and what it's being used for—helps you make smart decisions about where to apply it.

The best approach is simple:

Start with a real problem you have

Instead of your usual approach, see if AI can help

Bring in a human when AI hits its limits

Don't start with the technology and try to find a use for it.

The sales teams winning with AI aren't chasing every shiny new tool. They're the ones clearly identifying their bottlenecks first, then applying AI where it actually removes them.

AI isn't reinventing sales. It's just taking care of the stuff that gets in the way. And we can get back to what we know makes us successful: connecting with people.