A systematic review of Artificial Intelligence and Automation in Employment

AI and automation are reshaping labor markets by displacing repetitive, intermediate-skilled occupations, primarily in manufacturing, logistics, and administration, while expanding highskilled work that includes knowledge-based roles in healthcare, finance, and education. Lowskilled occupations will see declines in demand, while demand for analytical and interactive work is growing - potentially leading to new occupations and hybrid jobs. Routine and repetitive tasks will go away, while knowledge-driven functions will increase. There is still little systematic measurement of AI adoption, mostly based on patents, surveys, words that cooccur, or qualitative approaches. However, newer and more promising approaches include job postings, developer platforms, and task mapping, but they aren't standardized. Although most studies report evidence from high-income countries and firms with higher levels of innovation, this leaves a gap in studies concerning SMEs and lower-income contexts, which are actually more vulnerable to disruption. Most research studies the effects of AI and automation on employment and wages but does not investigate job quality, worker autonomy or wellbeing. Gig platforms and algorithmic governance have increasingly transformed the work experience into one that is more flexible but also precarious. Policymakers have favoured reskilling, continuous learning, and social protection systems, but although many policy options exist there are few evaluations of their effectiveness. There is limited causal evidence of long-term labour market consequences, meanwhile patterns of diffusion of new technologies in different sectors are still not fully understood.