Evaluating the Impact of Artificial Intelligence on Public Service Delivery Efficiency in the United States

There was a significant lack of empirical data on the measure of the effect that Artificial Intelligence (AI) has on the efficiency of operations in the U.S. municipal governments. Robust research providing evidence on pre and post-implementation measures were non-existent despite the high level of acknowledgement of the theoretical potential. The present study had the positive influence of AI integration on the indicators of public service delivery as an object of investigation. The main research question was to assess any efficiency improvement in its main key operation dimensions before and after adoption of AI. A cross-sectional quantitative methodology was used accompanied by a before and after comparative design. Results were drawn through surveys of 152 Chief Information Officers of municipalities with a city size of greater than 100,000. Descriptive statistics and t-tests were performed on seventeen efficiency indicators-response time, cost, citizen satisfaction and transparency. The outcome showed statistically significant results on all of the dimensions (p < 0.001). Mean efficiency in service delivery shifted up by 43 percent, 3.12 to 4.46. The process automation reflected a maximum mean preference (+ 1.44), second is response time (+ 1.32) and environmental impact (+ 1.30). The cost of providing a service per transaction was reduced severely (mean improvement of + 1.21 on an efficiency scale) as were the satisfaction levels of citizens with a mean increase of 1.27 points. The results are strong empirical evidence that AI implementation can be a lever of introducing significant efficiency improvement, which municipal leaders and policymakers should consider when evaluating the possibility of using technology to make the most out of the available resource and achieve significant improvements in terms of outcomes for the population.