Purpose The rapid advancement of artificial intelligence (AI) is profoundly reshaping the labor market, intensifying competition for specialized talent. This study investigates the evolving structure of AI-related employment by identifying key occupational categories and skill sets, with a particular focus on the strategic role of social media platforms in talent acquisition and workforce intelligence. Design/methodology/approach Drawing on 18,947 unique AI-related job postings collected from LinkedIn during the first three quarters of 2024, the study leverages the platform's dual function as a professional social network and recruitment tool. Using data science techniques, it classifies AI job roles and maps their associated skill requirements, offering a real-time, data-driven perspective on employer demand. Findings The analysis reveals that roles in data and analytics dominate the AI job landscape, followed by strong demand in business and operations. Notably, AI-related positions are expanding into non-technical domains such as education, customer service and the creative industries. Frequently required skills include communication, Python and machine learning. Cosine similarity analysis uncovers distinct clusters of competencies, underscoring the growing importance of hybrid profiles that integrate technical expertise with socio-emotional capabilities. The findings also highlight how employers strategically use LinkedIn to signal evolving talent needs, shape employer branding and engage with potential candidates in a competitive digital labor market. Originality/value By harnessing LinkedIn job advertisements as a lens into the social media-enabled labor market, this study contributes to emerging scholarship on digital talent acquisition and workforce transformation. It offers actionable insights for job seekers, educators and policymakers navigating the AI-driven employment landscape.
Nakash et al. (Sat,) studied this question.