<p>Disruptive innovations, particularly artificial intelligence (AI), are revolutionizing marketing. The alignment between employees and AI is a critical issue in current marketing research. This study uses job embeddedness theory to explore this alignment. By employing the BERTopic model and comparing different clustering algorithms through topic coherence, we model themes in existing AI marketing research. Analysis through the dimensions of job embeddedness—links, fit, and sacrifice—reveals that hierarchical clustering in BERTopic provides superior data fitting. Intertopic visualization identifies three themes: “financial and marketing operations”, “marketing tactics and innovations”, and “data analytics and VR innovations”. This study extends job embeddedness theory, defining its dimensions in the AI era and guiding future research directions.</p>