AI Vendor Says Fire Your Sales Team. EliseAI Is Doubling Its Own

EliseAI plans to double its sales team over the next 12 months, even as parts of the AI industry advertise that companies should fire theirs. The company, which sells AI to housing and health care businesses, reports its sales headcount has already grown 74% over the past year.

Every one of its salespeople uses AI, according to Ben Rey, vice president of enterprise sales. EliseAI even builds some of its own tools because, in his words, outside vendors can't keep up. "We've tripled the productivity of our AEs, and many of them now close $5 million to $15 million per quarter each," Rey says. "That productivity has us hiring faster than ever."

Why does this cut against the industry's pitch?

Attention, an AI company building tools for sales teams, is one of EliseAI's vendors — and its perspective, laid out in a Fortune commentary, challenges its own industry's marketing. For years, sales software vendors have sold the idea that tools let companies stop paying salespeople. One vendor currently advertises: "Replace your $90k SDR with our AI Sales Agent."

The pitch is easy to picture: a salary is a large expense, and a software subscription looks small beside it. But a salesperson also brings in business. If AI helps that person win more of it, a company with room to grow has a reason to hire another one. That's EliseAI's calculation — its salespeople became more productive, so it sees an opportunity to put more of them to work.

One caveat: these are company-reported results. They don't show how much of the improvement came from AI rather than a strong product, a growing market, or the sales team itself. They do undercut the assumption behind the replacement pitch — that the best use of a productivity gain is removing the person who achieved it.

What does the research say?

The hiring question gets empirical support from a study of 5,172 customer-support agents by economists Erik Brynjolfsson, Danielle Li, and Lindsey Raymond. An AI assistant increased issues resolved per hour by 15% on average. Less experienced and lower-skilled agents gained the most, improving both speed and quality. Agents with two months on the job and AI assistance performed as well as agents with more than six months of experience without it.

The system trained on successful work, including top performers' behavior, offered suggestions during conversations, and let agents edit or ignore them. The strongest agents saw little benefit and small declines in quality — a result the author says deserves serious weight. The researchers couldn't measure the effect on hiring, but they showed less experienced people could become effective much sooner.

Doesn't AI destroy entry-level jobs?

The counterargument is real. Stanford's latest analysis of U.S. payroll data found employment for workers ages 22 to 25 in AI-exposed occupations ran 19% below where it would have been had it kept pace with less-exposed peers. The gap operated mainly through reduced hiring. The authors call these descriptive findings, not causal estimates — but they are a serious warning. Young people can become better at a job with AI and still never get the chance to prove it.

Attention itself tries to automate work before hiring someone to do it. If there's a fixed amount of work and software handles it reliably, a smaller team may make sense. But when there are customers still to win, improving the team can create an opportunity to expand it.

What should employers measure?

Not email counts. Employers should track whether new hires reach competence sooner, whether their work needs less repair, and whether customers get the answers they need, the author argues. A new rep costs money to recruit, train, and pay before anyone knows whether they'll produce. If AI helps that person become effective sooner and handle more opportunities, the investment becomes easier to justify.

The limits are real: you still need a product people want and enough profitable business to pursue. AI cannot supply those by filling in your CRM.

EliseAI says its salespeople are so productive that it wants twice as many as it has today — and that decision, not headcount cuts, may be the AI story worth watching.