Generative artificial intelligence (AI) systems have revolutionized various industries by autonomously generating content, mimicking human creativity. However, concerns about their social and economic consequences arise with widespread adoption. This paper explores these consequences using agent-based modeling (ABM), aiming to predict the impact of generative AI on societal frameworks. The ABM incorporates individual, business, and government agents, simulating education, skills acquisition, AI adoption, and regulation dynamics. Leveraging ABM, this study contributes to understanding AI’s complex interactions, offering insights for policy-making processes. The literature review highlights ABM’s efficacy in forecasting AI impacts. Results indicate AI adoption, employment, and regulation trends, suggesting potential policy implications. Future work involves refining the model, assessing long-term implications and ethical considerations, and advancing understanding of generative AI’s societal effects.