Exploring what’s top of mind for B2B buyers

Every week, another headline lands with the same breathless conclusion: AI is coming for your job. A CEO cuts 10% of their workforce, drops the word "AI" in the announcement memo, and the financial media runs with it. Wall Street cheers. The stock pops. The narrative writes itself.

There's just one problem. The data doesn't support it — at least not in the way the headlines suggest.

At Gong, we have an unusual vantage point on this question. The Gong Revenue AI OS captures and analyzes millions of B2B sales conversations every quarter, giving us a real-time read on what business decision-makers are actually talking about before the PR team gets involved, before the earnings call, and before the narrative gets cleaned up for investors. What we're seeing in that data tells a more nuanced and ultimately more optimistic story than the one dominating the business press right now.

According to Challenger, Gray & Christmas, over 1.2 million layoffs were tracked in 2025. Less than 5% were primarily attributable to AI-driven efficiency gains. And even that figure likely overstates the impact.

The narrative has been blurred by companies themselves, eager to pitch a forward-looking AI story to shareholders rather than acknowledging past overhiring mistakes — a strategy that's been dubbed "AI-washing."

The AI-replaces-jobs story is not fabricated. It is, however, significantly overstated as a macro phenomenon and in many of the highest-profile cases, it is being used to dress up a balance sheet correction as strategic vision.

So what does the data look like when you strip away the press releases and look at what business decision-makers are saying in real conversations?

Gong Labs Trends analyzes the occurrence rate of topics and themes across millions of customer conversations captured and analyzed by the Gong Revenue AI OS — giving us a ground-level view of what's truly top of mind in the market at any given moment. This dataset gives us real-time insight into the priorities, challenges, buying triggers, and emerging concerns of B2B decision makers.

Here's what we found by analyzing 33.5 million deals worked since February of 2024.

AI conversation volume is up sharply across deals — but hiring conversation volume remains unchanged.

Since 2024, deals where AI is discussed have increased 85%. That's a meaningful signal, as AI is genuinely top of mind for buyers and sellers across virtually every industry. But here's the counterintuitive finding: deals where hiring is discussed haven’t declined, remaining flat over the same period.

If AI were truly displacing human workers at the scale the headlines suggest, you'd expect hiring to crater as AI mention volume spiked. That's not what's happening. The 85% AI surge versus the +1% hiring increase tells a different story — that while AI is increasing productivity and changing how work gets done, it is not yet functioning as a one-for-one replacement for human workers in most business contexts.

The conversation around AI agents is exploding — but that's a sign of ambition, not replacement.

We're seeing 13x the number of conversations mentioning AI agents compared to two years ago. Agents represent the most advanced AI capabilities currently available. These systems can reason, plan, and execute multi-step tasks in ways that more closely approximate how a human works. The surge in agent mentions reflects genuine excitement about what's coming, not evidence that humans have already been replaced.

Importantly, this also reflects where organizations are in their AI journey. According to Deloitte's 2026 State of AI in the Enterprise report, only 25% of companies have moved 40% or more of their AI pilots into production. Most organizations are still in the experimentation phase. The gap between excitement about agents and actual deployment at scale remains significant.

Mentions of AI replacing human work are rising — but look at who's doing the talking.

We've seen a 237% increase in calls where AI replacing human work is explicitly mentioned. That sounds alarming. But context matters enormously here. In sales conversations, this topic tends to surface in two ways: as a concern buyers are raising about their own industries, and as a value proposition sellers are using to make their case. Both reflect market awareness of AI's potential, not evidence that mass displacement is already underway.

The Federal Reserve's own research, combining job postings data with the Census Bureau's Business Trends and Outlook Survey, finds no evidence so far that AI adoption is reducing hiring. Firms and industries with higher AI uptake aren't posting fewer jobs.

Here's the data point from our research that we think gets closest to the truth.

Our State of Revenue AI 2026, uncovered the priorities of more than 3,000 revenue leaders.

When we look at revenue organizations with the most mature and deepest AI deployments, those companies report the most aggressive hiring plans compared to their peers.

Read that again. The organizations that have gone furthest with AI — not the ones dabbling, but the ones with real, operational AI systems running across their revenue motion — are the ones planning to hire the most.

This is the signal that cuts through the noise. AI, when deployed properly at the system level rather than just handed to individual reps as a tool, does not shrink the addressable opportunity. It expands it. It raises the ceiling on what a revenue organization can achieve, which in turn creates demand for more people to pursue that larger opportunity.

This finding is consistent with what PwC found in their 2025 Global AI Jobs Barometer. Revenue growth in industries best positioned to use AI has nearly quadrupled since 2022. Wages are rising twice as quickly in AI-exposed industries compared to those least exposed — even in the most highly automatable roles. AI is making workers more valuable, not less.

The AI-kills-jobs narrative is, at its core, a story about two very different things being conflated.

The first is real: AI is changing the nature of work. Tasks that were once performed by humans — drafting, summarizing, logging, routing, researching — are increasingly handled by AI systems. For individuals whose job consisted primarily of those tasks, the disruption is genuine and the adjustment is difficult. That's a real phenomenon that deserves serious attention.

The second is largely manufactured: the idea that the current wave of corporate layoffs is primarily driven by AI replacing workers at scale. What's actually driving the majority of layoffs is far less interesting to write about: companies correcting for years of over-hiring during a zero-interest-rate environment, CEOs rationalizing difficult decisions to investors using the most compelling vocabulary available, and finance teams using the moment to streamline operations they should have streamlined years earlier.

AI is the narrative. The balance sheet is the reality.

The more useful question for business leaders — and the one our data is positioned to help answer — is not "will AI take my job?" It's "what do the organizations deploying AI most effectively actually look like, and what are they doing differently?"

What we're finding is that the answer isn't smaller, leaner teams doing the same work more efficiently. It's larger, more ambitious teams doing more than they could have done before. The ceiling goes up. The opportunity expands. And the humans in those organizations shift their time away from the work AI can do toward the work only humans can do: judgment, relationships, creativity, and the kind of complex navigation that closes a deal, retains a customer, or builds a partnership.

That's not a comforting story manufactured to make people feel better. It's what the data — both ours and the broader economic research — actually shows.

The headlines will keep coming. But the next time a CEO drops the word "AI" in a layoff memo and the stock pops, it's worth asking: what did their headcount look like in 2021?

Want to go deeper on what this means for your team? Join us for our June webinar, AI Is Rewriting the Revenue Role—Here's What Comes Next, where we'll unpack how the most AI-mature organizations are redesigning roles to chase bigger opportunities, not smaller teams.

Gong Labs Trends analyzes aggregated and anonymized topic-level signals derived from millions of B2B sales interactions processed through the Gong Revenue AI OS to identify broad market trends. This analysis is based on aggregated and anonymized topic-level data across participating Gong customers. Findings are reported only in aggregate and are designed to reflect broad market trends rather than any individual company, conversation, deal, or transaction.