The debate over whether artificial intelligence belongs in the corporate boardroom ends — at least for those responsible for generating revenue.
According to , seven out of ten enterprise revenue leaders now rely on AI to regularly inform their business decisions. A clean study released by Gong on ThursdayRevenue Intelligence Company. The finding marks a dramatic shift from just two years ago, when most organizations saw AI as an experimental technology tied to pilot programs and individual productivity hacks.
The research, based on an analysis of 7.1 million sales opportunities across more than 3,600 companies and a survey of more than 3,000 global revenue leaders spanning the United States, United Kingdom, Australia and Germany, paints a picture of an industry in rapid change. Organizations that have incorporated AI into their core go-to-market strategies are 65 percent more likely to increase their win rates than those that still consider the technology optional.
"I don’t think people give decisions to AI, but they rely on AI in the decision-making process," Gong co-founder and chief executive, Amit Bandov said in an exclusive interview with VentureBeat. "Humans are making the decisions, but they are greatly assisted."
Discrimination is important. Rather than replacing human judgment, AI has become what Bandoff defines as one "Second opinion" – Data-driven examination of the intuition and guesswork that has traditionally ruled sales forecasting and strategy.
Slowing growth is forcing sales teams to squeeze more out of each rep
The timing of the rise of AI in revenue organizations is no coincidence. The study reveals a sobering fact: After rebounding in 2024, average annual revenue growth among the companies surveyed slowed to 16 percent in 2025, a decline of three percentage points over the course of the year. During the same period, sales rep quota attainment fell from 52 percent to 46 percent.
According to Gong’s analysis, the culprit isn’t that salespeople are performing worse on individual deals. The win rate and contract duration remained constant. The problem is that representatives are working on fewer opportunities. It’s a finding that suggests operational inefficiencies are eating into sales time.
This helps explain why productivity is at the top of executive priorities. For the first time in the study’s history, increasing the productivity of existing teams is listed as the number one win-win strategy for 2026, up from fourth place last year.
"The focus is on increasing sales productivity," Bandoff said. "How many dollars of output per dollar of input."
The number is instantly backed up. Teams where salespeople regularly use AI tools generate 77 percent more revenue per rep than those that do.
Companies are moving beyond basic AI automation to strategic decision-making
The nature of AI adoption in sales has evolved significantly over the past year. In 2024, most revenue teams use AI for basic automation: transcribing calls, drafting emails, updating CRM records. These use cases continue to increase, but 2025 marks what the report calls a turning point. "From Automation to Intelligence."
The number of US companies using AI to predict and measure strategic initiatives grew by 50% year over year. These more sophisticated applications—predicting deal outcomes, identifying at-risk accounts, measuring how well value propositions resonate with different buyers—are associated with dramatically better results.
According to the study, organizations in the 95th percentile of business impact from AI were two to four times more likely to have deployed these strategic use cases.
Bandoff provides a concrete example of how this works in practice. "Companies have thousands of deals that they include in their forecasts," He said. "It used to be purely based on human emotions – believe it or not. That’s why a lot of companies lose their numbers: because people say, ‘Oh, he told me he’d buy it,’ or ‘I think I might get it.’"
AI makes changes that are calculus by examining evidence rather than optimism. "Companies now get a second opinion from AI on their forecast, and that dramatically improves forecast accuracy—10 (or) 15 percent better accuracy simply because it’s based on evidence, not just human emotion." Bandoff said.
Revenue-related AI tools are dramatically improving alternatives to general-purpose alternatives
Another provocative finding of this study concerns the type of AI that delivers the results. Teams using revenue-specific AI solutions—tools designed expressly for sales workflows rather than general-purpose platforms like ChatGPT—reported 13 percent higher revenue growth and 85 percent greater commercial impact than those relying on generic tools.
This special system also had the potential to double for forecasting and predictive modeling, the report noted.
This finding has clear implications for Gong, who sells this type of domain-specific platform in particular. But the data suggest a real difference in outcomes. General purpose AI, while more general, often creates what the report describes as A "Blind spot" For organizations — especially when employees adopt consumer AI tools without company oversight.
MIT research shows that while only 59 percent of survey respondents said their teams use personal AI tools like ChatGPT at work, the actual figure is closer to 90 percent. This use of shadow AI poses security risks and creates fragmented technology stacks that undermine the potential for organizational-level intelligence.
Most sales leaders believe that AI will reshape their jobs rather than eliminate them.
Perhaps the most closely watched question in any AI study is employment. Gong research paints a more nuanced picture than the apocalyptic predictions that often dominate the headlines.
When asked about the impact of AI on revenue headcount three years out, 43 percent of respondents said they expect it to change jobs without reducing headcount—the most common response. Only 28 percent expect job elimination, while 21 percent actually predict that AI will create new roles. Only 8 percent predict minimal impact.
Bandoff frames this opportunity in terms of reclaiming lost time. He referred Forrester Research Pointing it out 77 percent A sales representative’s time is spent on activities that do not involve customers.
"AI can, ideally, eliminate all 77 percent." Bandoff said. "I don’t think it necessarily eliminates jobs. People are only half productive right now. Let’s make them fully productive, and whatever you’re paying them will translate into a lot more income."
The change is already visible in the stability of the character. Over the past decade, sales organizations have exploded into hyper-specialized functions: one person qualifies leads, another sets appointments, a third closes deals, a fourth handles onboarding. The result was that consumers were interacting with five or six different people in their shopping journey.
"Which is not a great buyer experience, because every time I meet someone new who doesn’t have the full context, and it’s very inefficient for companies," Bandoff said. "Now with AI, you can have one person do all of this, or most of it."
At Gong He, salespeople now generate 80 percent of their appointments because AI handles the prospecting legwork, Bandoff said.
American companies are adopting AI 18 months faster than their European counterparts
The study revealed a notable divide in AI adoption between the United States and Europe. While 87 percent of US companies now use AI in their revenue operations, the UK trails by 12 to 18 months, with a further 9 percent planning to adopt within a year. Just 70% of UK companies currently use AI, with 22% planning near-term adoption.
Bandoff said the pattern reflects a broader historical tendency for enterprise technology trends to cross the Atlantic with delays. "It’s always like this," He said. "Even as the Internet was taking off in America, Europe was a step behind."
The gap is not permanent, he said, and Europe sometimes moves to adopt technology. Mobile payment and messaging apps like WhatsApp gained traction there before the US — but for AI in particular, the US market is ahead.
A decade of AI development gives it an edge over Salesforce and Microsoft, Gong says
These results come as Gong navigates an increasingly crowded market. The company, which recently crossed 300 million In annual recurring revenue, it faces potential competition such as enterprise software giants Sales force And Microsoftboth of them are embedding AI capabilities into their platforms.
Bandoff argued that Gong’s decade of Ai’s development creates a substantial barrier to entry. A company’s architecture includes three layers: a "Product graph" which collects customer data from CRM systems, emails, calls, videos, and web signals. An intelligence layer combining large language models with about 40 proprietary small language models. And workflow applications are done above.
"Anyone who wants to build something like this – it’s not a small feature, it’s been 10 years in development." Bandoff said.
Rather than viewing Salesforce and Microsoft as threats, Bandoff portrays them as partners, pointing to the two companies’ participation in Gong’s recent user conference to discuss agent collaboration. Rise of MCP (Model context protocol) support and consumption-based pricing model means users can get AI agents from multiple vendors rather than committing to a single platform.
The real question is whether AI will enhance or undermine the sales profession
The implications of this report extend beyond sales departments. If AI can transform revenue operations—long considered a relationship-driven, human-centric function—it raises questions about what other business processes are about.
Bandoff sees possibilities for expansion rather than contraction. Drawing the analogy of digital photography, he noted that when faced with camera manufacturers, the total number of images exploded once smartphones made photography easy.
"If AI makes selling easier, I can see a world – I don’t know what it looks like right now – but why not?" Bandoff said. "We might have ten times as many jobs as we do now. Today it is expensive and inefficient, but if it becomes as simple as taking a picture, the industry can actually grow and create opportunities for people of different abilities from different places."
For Bandoff, who co-founded Gong in 2015 when AI was still a tough sell to non-technical business users, the current moment represents what he’s waited a decade to see. Back then, the mention of AI was like science fiction to sales executives. The company struggled to raise money because the underlying technology barely existed.
"When we started the company, we were born as an AI company, but we almost had to hide the AI," Bando recalled. "It was intimidating."
Now, seven out of ten of those executives say they trust AI to help run their businesses. Technology that once had to be hidden has become something that no one can afford to ignore.