AI Adoption High, But Impact Lags: LeadG2 Study

RADIO ONLINE | Tuesday, April 7, 2026 | 3:58pm CT

LeadG2

LeadG2 has released a new research report examining how revenue teams are using artificial intelligence, finding widespread adoption but limited impact due to gaps in integration, training, and execution. The report, "Revenue Enablement in the AI Era," is based on a survey of 154 revenue leaders across industries and highlights what it describes as a disconnect between AI usage and meaningful business transformation.

According to the findings, 100% of respondents report using or piloting AI, yet only 12% say it is deeply integrated into daily workflows. While 90% of teams report efficiency gains, most describe those improvements as incremental rather than transformative.

Messaging inconsistency emerged as the top challenge, cited by 64% of respondents, particularly among frontline sales and marketing contributors. The report also identifies training-not budget-as the biggest barrier to AI adoption, with 63% pointing to a lack of internal expertise.

The research further reveals gaps in data confidence and system integration. Only 27% of respondents say they are very confident in their CRM and AI data, and just 23% report fully integrated systems across sales and marketing functions.

LeadG2 notes a perception divide between leadership and frontline teams. While 74% of executives believe their organizations are aligned around revenue enablement, only 31% of individual contributors agree, suggesting strategy is not consistently translating into execution.

The report also highlights uneven application of AI tools. Leadership tends to focus on areas such as content creation and analytics, while frontline teams are less likely to use AI in higher-impact functions like sales coaching and personalization.

LeadG2 VP and Senior Director Emily Hartzell said that while AI is already embedded in daily operations, adoption alone is not enough. She noted that without consistent messaging, integrated systems, and structured enablement, AI can amplify existing inefficiencies.

The company concludes that organizations seeing the greatest return from AI will be those that prioritize structured enablement, improved data quality, stronger system integration, and expanded use cases beyond top-of-funnel activities, while also measuring buyer experience alongside pipeline metrics.