Reports show revenue teams still face AI limitations

Execs might harbor ambitions of winnowing sales staff and automating the entire deals pipeline with AI. But the reality inside revenue teams doesn’t quite measure up.

That was a theme of two reports this month from sales tech companies. In one, revenue platform Gong analyzed B2B sales conversations and 33.5 million deals between February 2024 and February 2026, and concluded that the data doesn’t support the narrative that AI is replacing human jobs. Another survey by Conga of 250 senior leaders across legal, revenue, compliance, and procurement found that most (62%) didn’t characterize the maturity of AI in their contract lifecycle management (CLM) as “integrated,” and 67% said their companies didn’t have a formal policy governing AI use.

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While myriad recent layoff announcements blamed AI for the downsizing, many experts say the technology is often a cover story for other business problems.

Gong said its analysis of B2B sales conversations on its platform backs up the “scapegoat” theory. While conversation around agents has risen sharply (85% since early 2024), deals where hiring is discussed increased 1%.

Gong’s research team claimed that the second number would decrease if AI were truly replacing jobs. The data also lines up with another recent Gong survey showing that companies with mature AI revenue operations had bigger hiring ambitions.

“For now, agents are very good at taking work off the seller’s plate: updating CRM records, summarizing calls, surfacing risks, drafting follow-ups, and pulling context from across the account,” Gong co-founder and CEO Amit Bendov told Morning Brew in an email. “But that is not the same as selling. Selling still requires trust, judgment, creativity, and accountability. It requires understanding the buyer’s business, reading the room, navigating risk, and building confidence in a decision.”

Bendov said companies pinning mass layoffs on AI efficiencies “overhired when capital was cheap and demand seemed endless.”

“Now it is easier to say, ‘We are becoming more efficient with AI,’ than to say, ‘We hired too much and growth did not keep up,’” Bendov said. “So I would look at two things: how much a company hired in 2021, and how much revenue growth it has delivered since.”

Contractual obligations

While AI agents are finding plenty of work on revenue teams, one area where the tech might not have a formalized role is CLM, or the processes around managing a company’s revenue contracts, per Conga’s report. The company’s survey found that 95% of respondents used AI for these processes, and 49% trusted it without much oversight.

But 67% said they didn’t have a formalized policy governing this use, and only 38% said their CLM AI maturity was fully “integrated.”

Geoff Webb, Conga’s VP of product and portfolio marketing, told us that it’s difficult to train models on the nuances and interconnected nature of sales contracts.

“The real challenges come around a couple of different areas: One is, the data that you train any model on must be very carefully curated when you’re training around contracts,” Webb said. “The second is that contracts are complex. There’s a lot of interrelations between contracts that you need to capture the nuances.”

Webb said companies need to take a comprehensive approach to building AI across different aspects of revenue operations.

“You’re seeing AI essentially optimizing within these silos of operation, and actually therefore reinforcing the silos of operation,” Webb said. “When you optimize any individual function with AI…you must spend at least as much time optimizing the connections between that function and the functions around it, or you’re going to have a real problem in two, three years’ time.”