The role of artificial intelligence (AI) in corporate revenue generation has reached a pivotal moment as a new study from Gong reveals that sales teams leveraging AI generate 77% more revenue per representative compared to those that do not. This significant finding underscores a rapid transformation in how AI is integrated into core business processes.
Widespread Trust in AI Among Revenue Leaders
According to Gong’s extensive research, which analyzed 7.1 million sales opportunities across over 3,600 companies and surveyed more than 3,000 revenue leaders across the United States, United Kingdom, Australia, and Germany, seven out of ten enterprise revenue leaders now regularly rely on AI to inform business decisions. This marks a dramatic shift from just two years ago when AI was largely confined to pilot projects and productivity hacks.
Amit Bendov, Gong’s co-founder and CEO, emphasizes that AI acts as an assistive “second opinion” rather than replacing human judgment. “Humans are making the decision, but they’re largely assisted,” Bendov stated, highlighting AI’s role in providing data-driven checks on traditional sales forecasting and strategy methods.
Addressing Slowing Revenue Growth by Increasing Sales Productivity
The study also points to a slowdown in average annual revenue growth, which declined from 19% in 2024 to 16% in 2025, alongside a drop in sales rep quota attainment from 52% to 46%. Importantly, this decline is attributed not to poorer deal performance but to sales representatives working fewer opportunities due to operational inefficiencies.
This context explains why boosting sales productivity has surged to the top of executive priorities. For the first time in Gong’s study history, increasing the productivity of existing sales teams is the top growth strategy for 2026, moving up from fourth place the previous year. Data shows sales teams regularly using AI tools generate a six-figure difference in revenue per salesperson annually.
From Automation to Strategic Intelligence
AI usage in sales has evolved beyond basic automation such as call transcription and CRM updates. The report highlights a transition from automation to intelligence, with a 50% increase in U.S. companies applying AI to forecasting and strategic initiatives like predicting deal outcomes and identifying at-risk accounts.
Companies in the top 5% for AI commercial impact are two to four times more likely to use these advanced AI applications. Bendov explains that AI enhances forecasting accuracy by providing an evidence-based “second opinion,” improving accuracy by 10 to 15% compared to human sentiment alone.
Specialized AI Tools Outperform General-Purpose Platforms
The study reveals that teams using revenue-specific AI solutions tailored for sales workflows outperform those relying on general-purpose AI tools like ChatGPT. These specialized platforms yield 13% higher revenue growth and 85% greater commercial impact and are twice as likely to be used for forecasting and predictive analytics.
The research also warns of risks associated with “shadow AI”—the unregulated use of personal AI tools within companies—posing security threats and fragmenting technology ecosystems, as highlighted by MIT research indicating actual AI tool usage in workplaces may be as high as 90% despite lower reported figures.
AI’s Impact on Sales Jobs: Transformation Over Elimination
Regarding employment, the majority of sales leaders foresee AI reshaping roles rather than eliminating them. Forty-three percent expect job transformation without headcount reduction, 28% anticipate job cuts, and 21% predict AI will create new roles.
Bendov notes that AI can reclaim the 77% of sales representatives’ time currently spent on non-customer-facing activities such as administrative tasks and forecasting. “AI can eliminate, ideally, all 77 percent—all the drudgery work that they’re doing,” he said, underscoring the potential for significant productivity gains.
This shift also facilitates role consolidation in sales teams, allowing a single salesperson to manage multiple functions previously divided among several specialists, thereby improving buyer experience and operational efficiency.
Regional Disparities in AI Adoption
The study identifies a notable gap between the United States and Europe in AI adoption within revenue operations. While 87% of U.S. companies currently use AI, with 9% planning adoption soon, the United Kingdom lags by 12 to 18 months, with 70% adoption and 22% planning to adopt AI in the near term. This delay aligns with historical trends where enterprise technology adoption in Europe trails the U.S.
Gong’s AI Development Provides Competitive Advantage
As Gong surpasses $300 million in annual recurring revenue, it faces competition from tech giants like Salesforce and Microsoft embedding AI into their platforms. However, Bendov asserts Gong’s decade-long AI development, including a proprietary “revenue graph” combining diverse customer data and multiple language models, constitutes a significant barrier to entry for competitors.
Rather than competitors, Bendov views these companies as partners, highlighting initiatives such as the Model Context Protocol (MCP) enabling customers to use AI agents from multiple vendors simultaneously.
Future Outlook: AI Could Expand Sales Opportunities
Bendov envisions AI potentially expanding the sales profession rather than diminishing it, likening the transformation to the digital photography revolution where ease of use led to exponential growth in activity despite industry disruptions.
Reflecting on Gong’s early days, when AI was a challenging concept for sales executives, Bendov remarks, “Now, seven out of ten of those same executives say they trust AI to help run their business. The technology that once had to be disguised has become the one thing nobody can afford to ignore.”
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