Generative AI has demonstrated an ability to match and surpass human performance in creating new content in areas as disparate as literature, music, visual arts, and programming. It has the potential to radically change the workforce structure and increase productivity. Recently developed quantitative estimates for the AI exposure for different occupations and work activities/tasks point toward a broad and significant impact. However, (generative) AI adoption is in an early stage and is a complex general-purpose technology, which typically has an extended first implementation phase. For an early assessment of the trends toward adoption we explore a data set of Lightcast job postings in the analytics and data science area over the 2014—2024 period. We analyze the changing demand as evidenced by the number of listings, the educational requirements, and the salary levels with respect to other non-farm occupations and within four levels of work experience within the analytics/data science set. We then focus on the entry- and junior-level segment that requires zero or three years of experience, including the software and specialized skills prioritized in the job listings. Our analysis of the trends emerging from the data broadly agrees with the predictions for the changing nature of work as demonstrated by substantive changes in job skills requirements that all point toward increasing demand for AI and generative AI-related knowledge and skills, such as data science, machine learning, visualization, cloud computing, processing and managing large data sets.