Agent Knowledge Gap Detection

A major North American telecommunications provider with over 60,000 call center agents and approximately 170 million calls per year deployed generative AI in partnership with a cloud technology provider to address agent knowledge gaps at scale. According to reporting by Sprinklr in 2025, the AI models now accurately determine the reason for a customer's call 80% of the time, enabling precise matching of inquiries to agents with the relevant expertise. As reported by Econsultancy in 2025, the deployment enabled customer service representatives to comprehensively answer 95% of queries, and sales at the organization rose by 40% as the technology freed agents to shift from reactive support to proactive selling.

A leading European media and telecommunications company, documented in a 2024 McKinsey case study, deployed a generative AI copilot designed to equip customer service agents with faster and more effective knowledge retrieval during calls. The organization hosted weekly working groups to gather qualitative feedback on usability and collected quantitative feedback through agent ratings of AI-generated responses, establishing a continuous improvement loop between gap detection and content creation. Separately, a customer engagement platform vendor reported that 40% of escalations in its client deployments are caused by missing knowledge, and its AI-powered gap detection feature categorizes escalation-causing topics, counts their frequency, and generates ready-to-use content suggestions based on how human agents resolved similar tickets.