How Election Cycles Influence Automation Adoption: A Comparative Study of Public and Private Sector Policies in the U.S

This dataset examines how U.S. electoral cycles influence automation adoption trends in the public and private sectors. Drawing on a mixed-method approach, the data combine longitudinal quantitative analysis of automation rates over the period 2000–2020 with qualitative insights from semi-structured interviews with 30 decision-makers. Significant increases in public sector automation are seen after the election, given the policy for modernization by an incoming administration, while private sector investments in automation are much lower during the pre-election period due to uncertainty over future regulations. The current study fills an important gap between political economy and technological adoption by providing empirical evidence and practical recommendations for policymakers and business executives. These drivers include regulatory uncertainty and an electoral mandate; a dataset on the trends, regression analyses, and thematic insights was drawn upon.