Abstract
The dynamic nature of skill requirements poses challenges for educators, job seekers, policymakers, and employers. Advancements in AI hinder the timely tracking of skill needs and the forecasting of future trends. This study analyzes the evolution of skill demands using job advertisements from 2021 onward for data science, analytics, and AI roles in Poland. For AI roles, the findings indicate a rapid rise in LLM and Generative AI skills, along with a shift from model-centric work to system-level AI integration, architectures, APIs, and workflows within organizational information systems. Across data and analytics professions, the persistence of core competencies such as Python and data infrastructure suggests that foundational technical skills remain stable, with AI complementing existing capabilities. The decreasing emphasis on GDPR, security, and data quality in some professions raises concerns. The study provides insights and skill-frequency data to support curriculum development, workforce planning, and future research on AI-driven labor-market transformation.
Paper Type
Poster
DOI
10.62036/ISD.2026.140
Longitudinal Trend Analysis of Data Science, Analytics and AI Skills in Job Ads
The dynamic nature of skill requirements poses challenges for educators, job seekers, policymakers, and employers. Advancements in AI hinder the timely tracking of skill needs and the forecasting of future trends. This study analyzes the evolution of skill demands using job advertisements from 2021 onward for data science, analytics, and AI roles in Poland. For AI roles, the findings indicate a rapid rise in LLM and Generative AI skills, along with a shift from model-centric work to system-level AI integration, architectures, APIs, and workflows within organizational information systems. Across data and analytics professions, the persistence of core competencies such as Python and data infrastructure suggests that foundational technical skills remain stable, with AI complementing existing capabilities. The decreasing emphasis on GDPR, security, and data quality in some professions raises concerns. The study provides insights and skill-frequency data to support curriculum development, workforce planning, and future research on AI-driven labor-market transformation.
Recommended Citation
Musazade, N.(2026). Longitudinal Trend Analysis of Data Science, Analytics and AI Skills in Job Ads. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.140