Economists

Conduct research, prepare reports, or formulate plans to address economic problems related to the production and distribution of goods and services or monetary and fiscal policy. May collect and process economic and statistical data using sampling techniques and econometric methods.

The occupation of "Economists" has an automation risk of 50.9%, only slightly below its base risk of 51.8%. This moderate risk level reflects the significant portions of the role that involve systematic data analysis, which are increasingly susceptible to automation through advanced algorithms and machine learning tools. Among the most automatable tasks are the study of economic and statistical data within specialized domains like finance, labor, and agriculture, as these involve standardized methodologies and repetitive data processing. Similarly, compiling, analyzing, and reporting data to explain economic phenomena and forecast trends by applying mathematical models falls within the capabilities of modern AI and statistical software. Additionally, examining the socioeconomic impacts of public policy proposals (e.g., legislation or regulations) can be partially automated as much of this work involves synthesizing large quantitative datasets and generating reports. Despite this high degree of automation potential, certain responsibilities of economists remain more resistant to automation. Tasks such as forecasting the production and consumption of renewable resources—alongside evaluating the supply and depletion of non-renewable resources—require nuanced judgment calls, the integration of diverse information sources, and scenario planning that AI still struggles to fully replicate. Providing litigation support, such as preparing expert testimony or actually testifying as an expert witness, remains highly human-centered due to the need for credibility, adaptability, and communication with legal professionals and courts. Likewise, testifying at legislative or regulatory hearings not only demands deep subject matter expertise but also the original interpretation of complex data and the presentation of recommendations tailored to specific political or social contexts. The primary bottleneck skills limiting further automation in the field of economics are centered on originality, with skill levels at 3.1% and 3.5%. Originality encompasses the ability to generate new ideas, creative policy recommendations, and unique approaches to problem-solving—traits that are very difficult for AI to mimic reliably. While software tools excel at pattern recognition, data crunching, and even running simulations, they lack the nuanced creativity and contextual awareness needed to provide innovative economic solutions or insights. The reliance on originality for tasks such as crafting expert testimony or advising on unprecedented economic scenarios helps maintain a significant human element in this occupation and serves as a current barrier to full automation. As a result, while many technical aspects of economic analysis could be automated in the foreseeable future, truly original thinking ensures that economists retain a vital, irreplaceable role.