AI in Sales: the UK Lags the US, But opportunity Abounds – A Deep Dive into Gong‘s Latest Findings
The integration of Artificial Intelligence (AI) into sales processes is rapidly reshaping the revenue landscape. While the United States currently leads the charge, new data from Gong, a leading revenue intelligence platform, reveals a meaningful gap in AI adoption between the US and the United Kingdom. This analysis delves into Gong’s findings, explores the reasons behind the transatlantic divide, and examines the potential future of AI in sales – including whether it will expand or disrupt the profession. We’ll also explore how Gong is positioning itself amidst growing competition from tech giants like Salesforce and Microsoft.
(Image: db569646b242847d0a674be%2FUK_adoption.png%3Fw%3D1000%26q%3D100&w=3840&q=75 – caption: The United Kingdom trails the United States in A.I. adoption for sales, with 30 percent of U.K. organizations yet to implement the technology or planning to do so. (Credit: Gong))
The Transatlantic AI Adoption Divide: Why the UK is Behind
Gong’s recent report highlights that 70% of US organizations have already adopted AI for sales, compared to just 60% in the UK. A substantial 30% of UK businesses are still either not implementing AI or are only in the planning stages. This disparity isn’t necessarily surprising, according to Gong co-founder Amit Bendov.He points to a ancient pattern of enterprise technology trends originating in the US before gaining traction in Europe.
“It’s always like that,” Bendov explains. “Even when the internet was taking off in the U.S., Europe was a step behind.” While Europe has occasionally led in specific tech areas – mobile payments and messaging apps like WhatsApp being prime examples – the momentum in AI currently resides firmly in the American market. This lag isn’t a sign of resistance, but rather a reflection of differing adoption speeds and possibly, varying levels of investment and infrastructure readiness.
Gong’s Competitive Edge: A Decade of Dedicated AI Development
As AI becomes increasingly mainstream, Gong faces growing competition from established enterprise software powerhouses like Salesforce and Microsoft, both aggressively integrating AI capabilities into their existing platforms. Though, Gong is confident in its position, attributing its strength to a decade of focused AI development.
The company’s architecture isn’t built as an add-on feature, but is fundamentally rooted in AI, structured around three core layers:
* Revenue Graph: This layer aggregates extensive customer data from various sources - CRM systems, email interactions, call recordings, video meetings, and website activity - providing a holistic view of the customer journey.
* Intelligence Layer: This is where Gong’s expertise shines. It combines the power of Large Language Models (LLMs) with approximately 40 proprietary Small Language Models (SLMs),allowing for nuanced and highly accurate insights.
* Workflow Applications: built on top of the first two layers, these applications deliver actionable intelligence directly to sales teams, automating tasks and improving performance.
“Anybody that would want to build something like that – it’s not a small feature, it’s 10 years in development - would need first to build the revenue graph,” Bendov emphasizes. This deep investment in foundational infrastructure creates a significant barrier to entry for competitors.
furthermore,Gong isn’t viewing Salesforce and Microsoft solely as rivals. Bendov characterizes them as potential partners, citing their participation in Gong’s recent user conference to discuss agent interoperability. The emergence of the Model Context Protocol (MCP) and consumption-based pricing models are fostering a more open ecosystem, allowing customers to leverage AI agents from multiple vendors, rather than being locked into a single platform.
Beyond Sales Departments: The Broader Implications of AI
the impact of AI extends far beyond simply improving sales performance. If AI can fundamentally transform revenue operations – traditionally a relationship-driven, human-centric function – it begs the question: which other business processes are ripe for disruption?
Bendov believes the future holds expansion, not contraction. He draws a compelling parallel to the evolution of photography. While traditional camera manufacturers faced challenges with the rise of smartphone cameras, the total number of photos taken exploded.
“If AI makes selling simple, I could see a world [with] maybe ten times more jobs than we have now,” Bendov predicts. “It’s expensive and inefficient today, but if it becomes as
Related reading