The State of AI in Sales in 2025

The strange thing about revolutions is that you often don't notice when you're in the middle of them. 

Consider the iPhone. 

When it first came out, I was in 7th grade and I distinctly remember thinking it wasn’t that big of a deal. (Even investors felt the same — one even called it “dead on arrival”.) 

But within weeks, my classmates started showing up with them. Then my mom. Then me. At some point, that sleek little gadget stopped being a novelty and became a default. Most of us now think in “iOS” — calendars, maps, messages, ideas — all neatly organized in our pockets.

Tech movements don’t always start with fireworks. They unfold, one small shift at a time, until suddenly everything feels different.

AI in sales is going through the same transformation. And, for you — as business owners and people leaders and commission-earners — the stakes are much higher than middle school peer pressure. Because, we’re far past the “release of the iPhone” stage of AI. 

Sales teams using AI are 25% more likely to see revenue growth than those who aren’t. The once-blurry picture of AI’s potential is coming into focus; the money is following. 

“AI is going to be critical to humanity,” says the tech analyst who saw the iPhone wave coming before most.

Those paying attention early are the ones who get ahead, and you’re one of them.

So what exactly is AI doing in sales today? And where can you best leverage it?

The 3 truths about AI in sales today

Truth #1: If it sounds too good to be true — it probably is

Growing up, my siblings and I would stake our claim on communal treats by licking the ones we wanted to save for later. Gross? Definitely. But it proved to be effective at preventing anyone else from snatching our germy cookies before we could.

I noticed that tech companies are doing something equally immature with AI.

They hastily embed some version of OpenAI into their product, rush it to market, and slap a big, fat “[Company Name] AI” sticker on it; all for the sake of shouting, “This is ours! Look at us! We’re in the club!”

But, our team ran a survey, and found that half of all sales leaders aren’t satisfied with any of the AI tools on the market — it’s just a whole lot of soggy cookies. 

Which puts the pressure on sales leaders to make an AI investment that’s:

1. Broadly adoptable and scaleable within their current process
2. Offers clear ROI
3. And has a measurable impact

Truth #2: Generative AI is a leveler of performance

A study from a group of scholars at Harvard, MIT, and Wharton flips the entire “Human vs. Robot” argument on its head. 

Essentially, it found that the use of generative AI has two major effects on the workforce:

1. It improves performance. 90% of participants, irrespective of their baseline proficiency, produced better results when using GPT-4 for creative or product-related tasks.
2. The gap between top and lower performers is reduced. A higher share of participants performed at or very close to the average level. AI pulls these averages up across the board.

Gen AI is creating brand new opportunities for human talent.

This has incredible implications for sales, an industry that's been historically hampered by big experience gaps and steep learning curves for fledgling SDRs. 

“I think there is a lot of value added in what we can do as humans,” one study participant was quoted as saying, “[Now] you need a human to adapt an answer to a business’s context; that process cannot be replaced by AI.”

Truth #3: AI excels in some areas — but not all

In 2025, AI is assisting in life-saving surgeries. 

It’s reimagining the way we grow our food and tracking your teeth brushing habits. It's even ”resurrecting” your loved ones with text and voice language models.

The creative applications of AI are endless, beyond sales, but within it, too. 

65% of organizations are regularly using gen AI — nearly double the percentage from their previous survey just ten months ago.

But are they applying it in the right place? 

The same research article out of Harvard summarized its findings like this: 

“The job of the leader is to help people use the new technology in the right way, for the right tasks and to continually adjust and adapt in the face of GenAI’s ever-expanding frontier.”

So, what are these “right” sales tasks, and how do we define them in the context of generative AI?

What is generative AI in sales?

When people refer to "generative AI" in sales, they're talking about using artificial intelligence tools to autonomously create content, insights, and solutions that enhance sales processes and drive better outcomes. That includes everything from writing prospecting emails to forecasting deals and prioritizing leads.

Generative AI is incredible at some of these things — but it has its limits.

Man vs. Machine: What's AI's job and what's yours?

Look closely and you’ll find a common thread.

Segmentation, lead scoring, research, and copywriting; right now, artificial intelligence is ripe for outbound sales.

This shift means we need to rethink where humans add the most value, not with fear but with curiosity. The focus is moving from brute-force execution to strategy, testing, and orchestration. In short: less doing, more designing.

So, what does this new dance between human and machine actually look like in practice?

Before I explain the "how", here’s a cheatsheet.

Prospecting

Targeting your ICP

Figuring out who your ideal customer is the first step of selling anything. It demands an intimate and involved understanding of your business that a machine can’t replicate.

Using your deep contextual knowledge around what you sell and who you help, build out your buying personas and determine the best search filters to apply to your contact database.

As you start to perform prospecting activities (in a modern sales tool that tracks that kind of thing), AI can help you analyze huge datasets on what type of person engaging, converting, and ultimately buying. This means that now, your targeting is actively improving the more you sell. 

It becomes a feedback loop that helps you continuously refine your personas, adjust your filters, and double down on the segments that show traction.

List building

Pulling the leads you find into a workable list requires some minimal human action, but, once you have your ICPs built out with all your filters, you can save and subscribe to your searches. 

Apollo will run in the background to help you auto-populate your lists with new leads that fit your criteria. 

Lead prioritization

According to the Pareto Principle, 80% of your revenue comes from the top 20% of your accounts. 

AI is capable of weeding through entire lead lists to help you identify which prospects mirror these “top 20%” accounts, when they are most likely to buy, and if that time is now.

In Apollo, for example, this is called Scores. It works right out of the box (AI automatically generates scores based on your account and prospecting activity. The more you do, the more it learns) and it essentially takes the entire task of lead prioritization off of the human SDR’s plate. 

Contact and company research

Research is the crème de la crème. The zenith. The apex of AI’s brilliance!

With the right prompt, AI can comb company websites, LinkedIn activity, press releases, portfolios, social media posts, YouTube — everything available on the world wide web! — to give you insights that would previously take hours to gather in a matter of minutes.

Today, sales systems and tools that have built-in AI prompting help salespeople in two key ways.

1. Lead segmentation. For example, if you sell apparel to fashion distributors, you can ask AI to find and filter out companies who sell multiple brands on their website to give you a more refined list.

2. Messaging personalization. You can funnel research insights directly into your email that personalizes it for each individual account or person: "Hi [Prospect Name], I see that your website currently features multiple brands like [Brand 1], [Brand 2], and [Brand 3].“

Engagement

Building your outbound strategies

When you should email, what you should say, when to hop on a call, and to whom, is decided by you — to an extent.

If you’re starting from scratch, it’s a matter of choosing a specific ICP, building a sales sequence, adjusting, testing, and seeing what works. But this isn’t to say you’re shooting in the dark.

The content of your emails can be auto-personalized and populated with snippets and the results of AI prompting. And the data that flows into these sequences can be auto-enriched and auto-prospected on a schedule determined by you.  

Executing the touchpoints

After you build your outbound structure, all the work can flow…like…in a Workflow.

Workflows are the end-to-end automations that execute the sequence enrollments, email sends, LinkedIn touchpoints, manual task assignments, follow-ups, triggers, and notifications — it’s the orchestrator of your outbound.

It’s the most powerful (and profitable) use case for automation across the entire sales funnel.

Deal Management

Scheduling meetings

When I think of stellar automation at the bottom-of-the-funnel, the sales team at Cyera comes to mind. They used a combination of tools, including Apollo Meetings, to cut their BDRs’ manual work in half.

It’s possible for you, too, with a bit of initial setup. 

Connect your calendar, set your default availability, add relevant stakeholders from your team, and send out the link. From here, Apollo handles automatic email reminders, notes, and even the good, insightful stuff like auto-generated reports after the meeting is done.

Analyzing sales calls

AI-powered dialers are one of the longest-standing use cases of AI in the space — and for good reason.

Industry research from Gong shows that you can increase win rates by more than 26% if you use AI to pull key takeaways and next steps from your sales calls.

You can play and share your recordings, create video clips, and take action on tasks with automatic transcripts and AI-written summaries. And as a team leader, you have everything in front of you, instantly, to coach, train, and lead teams to increase call conversions.

👉 Watch this free course on Apollo Conversations to learn best practices for AI-powered calling in 2025

Closing

Negotiation

Yeah, you’re not getting out of this one…

But that’s the beauty of AI and automation; it gives you the time, ability, and insights to do the real people work of meeting prospects where they are at, addressing their concerns, and leading conversations that close.

Reporting and analytics

We’re at a point where compiling reports by hand is not only time consuming, but less accurate.

AI can make recommendations and adjustments for you that are based on your sales activities, data, and results. 

• Machine learning algorithms analyze large datasets to identify patterns and correlations between customer data and sales outcomes
• Natural Language Processing (NLP) interprets customer feedback and pulls insights from text for you
• And predictive modeling can look at historical data to predict future customer behavior and potential opportunities

If you made it this far, it's safe to assume you're interested in improving the whole of your outbound process.

Last year, my team and I wrote the book on Outbound Sales. It gives you data-backed practices for literally building your outbound process from the ground up.

👉 You can read it on the Apollo Academy for free. Or, if you’re more of a pages person, you can order a copy on Amazon and Amazon Kindle.

Embrace the change: The next step in AI-powered sales

The sales teams who win won’t be the ones who do more; they’ll be the ones who design better.

In our next article, we’ll break down the core building block of AI: prompting. With tips and examples from AI expert Samuel Thomas Elliot, you’ll learn how to speak the language of AI to create prompts that do your research and personalize your messaging for you.

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Or, if you want to start applying what you’ve learned right now — check out Apollo’s AI-powered templates for instant opportunities to embed AI directly into your sales workflow.

More to come!