The adoption of Artificial Intelligence (AI) in Social Customer Relationship Management (SCRM) is transforming the way companies understand customer sentiment and translates their insights into strategic behaviours. Although the study of SCRM has reached maturity in the last decade, the body of knowledge on AI-based S-CRM is still divided among marketing publications, information systems and data science platforms. The bibliometric analysis of peer-reviewed publications (2010, 2025) on AI-based SCRM presented in this paper was performed using Google Scholar (via Publish or Perish) as the main source. Based on VOSviewer, we investigate performance metrics (publications, citations, sources, countries), and science mapping (cocitation, cooccurrence, thematic evolution) to pinpoint intellectual underpinnings and research frontiers of AI-based SCRM. Emerging studies indicate that early S-CRM research focused on sentiment analysis and social listening (e.g., He et al., 2013), whereas current groups focus on predictive analytics, chatbots, agentic AI systems and trust/privacy in AI adoption (Del Vecchio et al., 2020; Mohammed et al., 2024). Thematic evolution has moved to a scenario of monitoring customer opinions to strategic orchestration of customer engagement through AI. This is one of the first bibliometric mappings of AI-driven S-CRM. It synthesises scattered studies, outlines the most urgent gaps (ethics, explainability, SME adoption), and suggests a further agenda based on believable, strategic, and contextual AI-SCRM ecosystems