AI Is Changing the AE Job. Here's Which Parts Are Worth Worrying About

In 2024, Jared Sires was a startup account executive with somewhere between 600 and 700 accounts and a calendar that ran from morning calls straight through to emails he was still answering at 9 or 10 at night. "It was almost impossible to manage my inbox," he said. "And doing outbound on top of that — you don't really know where to focus." Nothing about that description is unusual. It is just what a busy AE looks like.

What happened next is what this article is about. Jared, who had never written a line of code in his life, built a tool that drafted his customer emails in his own voice and saved him two to three hours a day. Within 24 hours of sharing it with colleagues, others in his sales organization were using it too. Eventually, about 80% of Anthropic's sales team adopted the system. Jared now works as a product manager building AI tools for sellers — a role that didn't exist when he started.

His story is not a warning that AI will replace you. It is not a promise that AI will save you either. It is something more useful than either: an honest map of which parts of the AE job are changing, which parts are becoming more valuable, and what the people who are advancing are actually doing differently.

Before getting to what Jared did — and what it means for you — it helps to see exactly which parts of the AE job are already changing, and which parts are quietly becoming harder to replace.

What AI Is Already Doing in Your Workday

The changes are happening at the task level, not the title level. And they're measurable.

Michelle Forte, an Agentforce Specialist AE at Salesforce, describes account research that used to consume her week. She'd spend two to three hours per prospect digging through LinkedIn profiles, company news, and recent funding rounds. Now, with AI integrated into her daily workflow, she gets insights before she's even asked a system to run a report. "When I can complete comprehensive account research in 15 minutes instead of three hours," she said, "I'm not staying late to prepare for tomorrow's calls — and I get home to have dinner with my son." That's not a productivity story. That's a different life.

The changes go further than writing tasks. During a three-week pilot, Notion's commercial AE team used AI dialing tools and saw dial volume increase 260%. Reps who had been booking roughly one cold-call meeting per month started booking five or six per week. The work didn't disappear — it compressed. The AEs covered more ground in less time, not because they got better at cold calling, but because the tool handled the mechanical friction of the process.

AI doesn't diminish the need for soft skills, instead it amplifies them exponentially.
— Michelle Forte, Agentforce Specialist AE, Salesforce

Then there's what Anthropic built on its inbound side. The company's AI buying agent now holds thousands of conversations per day, around the clock. Leads that come through it convert to sales opportunities more than twice as often as the old contact form and close about five days faster. The agent doesn't replace the rep — but it fundamentally changes what's waiting for the rep when they show up.

Greg Hessong, Senior Director Analyst in Gartner's Sales practice, cuts through what this means for how organizations should respond: "Sales leaders who win with AI will not ask sellers to do everything they did before, just faster. They will build AI-augmented roles that give sellers more capacity to help customers realize value."

Research, cold outreach volume, inbound filtering — these aren't future risks. They're current changes affecting AE calendars right now. These examples come from SaaS and tech, but the underlying tasks exist across industries. Whether you sell logistics software, financial services, or enterprise hardware, the same hours are being compressed by the same category of tools.

Knowing which tasks are shrinking is only half the picture. The more useful question — especially if you're deciding where to invest your next six months — is which parts of the AE job AI is making harder to replace, not easier.

Where Human AEs Are Becoming Harder to Replace

Here's what the buyer data actually shows, and it's more specific than "soft skills matter."

Gartner surveyed 645 B2B buyers and found that 69% prefer to validate AI-generated insights with a sales rep. That alone is striking. But the gap that follows is more useful: buyers are 32 percentage points more likely to say a rep made them feel confident in their purchase decision than GenAI, and 39 points more likely to say a rep understood their needs. Those aren't vague preferences for human interaction. They're specific moments — confidence at commitment, being understood — where a machine consistently falls short.

Stevie Griffiths, an AE at Cognism, lives on both sides of this divide. After every call, she uses Gong's AI assistant to identify where she didn't dig deep enough into metrics or the decision process. "It's like having an extra layer of quality control," she said. But when AI-generated voice notes land in her own LinkedIn inbox, she clicks off immediately. "The second you hit play, you can tell it's robotic with no personality. I don't even finish them anymore." Her distinction is precise: AI to strengthen real selling, never to simulate it.

It's not about letting AI coach you. It's about using it to spot gaps faster, then doing the real work yourself.
— Stevie Griffiths, Account Executive, Cognism

Jared's inbox tool fits the same pattern. It handled the administrative work so he could do what he actually wanted to do — which is sales. The automation freed the human judgment; it didn't replace it.

The AEs who are advancing aren't simply using more tools. They're using AI to handle information work while staying personally accountable for the moments that require a person: confidence at commitment, organizational alignment, contextual judgment under uncertainty. That combination shows up in fields far outside SaaS. Wherever a buyer is about to commit real budget to something consequential, the 32-point gap between human and AI confidence exists. It's not a technology industry finding. It's a buyer behavior finding.

Here's the Part Most AI Optimism Quietly Skips

The threat is real, measurable, and unevenly distributed.

Employers cited AI in nearly a quarter of all announced job cuts in 2026 through June — 101,743 announced cuts attributed to AI, according to Challenger, Gray & Christmas. These aren't predictions. They're announcements that have already happened.

And the gains aren't landing evenly either. Gartner reports that AI saves sellers an average of 4.8 hours per week — but 72% of sales organizations report low reinvestment of those savings into high-value selling. The time is freed and then effectively wasted. Meanwhile, 20% of organizations report a 50% or higher negative return on AI investment, while 25% report a 50% or higher positive return. The same technology, very different outcomes.

The risk is real. The outcome is not fixed.

What determines which side of that divide an AE lands on isn't whether they use AI tools — it's whether their value lives primarily in the tasks those tools handle best. An AE whose contribution is mostly research, first-draft outreach, call summaries, and basic qualification faces a different exposure profile than one who has moved toward judgment, validation, and organizational influence. The technology doesn't determine the outcome. The skill mix does.

Which means the practical question is not "Will AI affect my job?" It already is. The question is: what specifically should you do differently, starting this week?

What the AEs Who Are Advancing Actually Do

Return for a moment to Jared. He didn't wait to understand everything before acting. He identified one specific friction point — the inbox — and treated it as a workflow question rather than a personal failing. The sellers in his organization who joined him within 24 hours of him sharing the tool weren't AI enthusiasts. They were people who recognized the same friction in their own day.

The Gartner finding that sticks: sellers who partner with AI tools are 3.7 times more likely to meet quota. But "partnering" is not the same as delegating. The AEs capturing that advantage are using AI to handle information work while staying personally accountable for the moments that require judgment — confidence, validation, organizational alignment, the decision itself.

The concrete action is a task audit. This week, write down every hour you spend on research, note-taking, follow-up drafting, and call prep documentation. That list is your starting point — not because all of it should be automated, but because it tells you exactly which parts of your day are most exposed and which hours you could redirect toward the work buyers actually can't get from a chatbot. Start with the task that costs you the most time and delivers the least judgment. That is where you begin.

The AEs who advance from here won't be the ones who used the most AI tools. They'll be the ones who were honest about which parts of their job a machine does better — and then made sure the rest was unmistakably human.

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