This project examines how exposure to scholarly forecasts about artificial intelligence's (AI's) impact on labor markets shapes perceptions, decision preferences, and intended behaviors among U.S. workers, business managers, and decision makers. Research into how AI will affect the workforce is important for public debate and individual and business decisions, but it is unclear how such research influences the beliefs and decisions of key stakeholders. The findings of this study clarify how such research informs—or complicates—critical decision-making by these groups. To support broad understanding and practical use of the findings, the project includes development of a public-facing online portal with plain-language summaries of major AI forecasting studies and interactive tools, allowing users to compare labor forecasts across industries, occupations, and demographic groups. The project contributes to national priorities related to AI leadership, the future of work, and science communication, while mentoring students. The research draws on insights from labor economics, science of science, and public administration to design a set of multi-sample online survey experiments targeting three distinct stakeholder groups: workers in non-managerial roles, business managers responsible for organizational decisions, and regulatory decision makers. Participants first answer questions assessing their knowledge, beliefs, and attitudes about AI. They are then randomly exposed to b