This research project employs the Delphi method to systematically elicit expert-based expectations about the future of the agri-food system in the US, with a particular focus on policy, markets, technologies, and farm structure. The study is designed around two complementary Delphi surveys conducted between June 2025 and November 2025: a national-level survey and a set of state-level surveys. The national Delphi survey included 28 participants representing a diverse group of experts (from academia, government agencies, private sector, and civil society) with knowledge of US agri–systems, policies, and markets. In parallel, state-level Delphi surveys were conducted in three states Ohio (OH), Georgia (GA), and Nebraska (NE) with ≈ 15 participants in each state. These state-level surveys allowed for a more context-specific exploration of agri–futures, capturing regional heterogeneity in farm management practices, environmental conditions, and agri–production systems, among others. Together, the two survey components provide both a broad national perspective and more localized insights, enabling a deeper understanding of how the US agri-food system may evolve by the year 2050.
This research project employs the Delphi method to systematically elicit expert-based expectations about the future of the agri-food system in the US, with a particular focus on policy, markets, technologies, and farm structure. The study is designed around two complementary Delphi surveys conducted between June 2025 and November 2025: a national-level survey and a set of state-level surveys. The national Delphi survey included 28 participants representing a diverse group of experts (from academia, government agencies, private sector, and civil society) with knowledge of US agri–systems, policies, and markets. In parallel, state-level Delphi surveys were conducted in three states Ohio (OH), Georgia (GA), and Nebraska (NE) with ≈ 15 participants in each state. These state-level surveys allowed for a more context-specific exploration of agri–futures, capturing regional heterogeneity in farm management practices, environmental conditions, and agri–production systems, among others. Together, the two survey components provide both a broad national perspective and more localized insights, enabling a deeper understanding of how the US agri-food system may evolve by the year 2050.
The Delphi method is a structured, iterative process used to collect and synthesize expert judgments on complex and uncertain issues. Originally developed for forecasting purposes, the method is particularly useful in situations where empirical data may be limited or when future conditions are inherently uncertain. A classical Delphi study typically involves several key characteristics: anonymity of participants, iterative rounds of questioning, provision of feedback between rounds, and aggregation of group responses into statistical summaries. These features are designed to minimize the influence of dominant participants and groupthink, encourage independent views, and gradually move the group towards more considered and refined judgments (generate group consensus). In modified applications, including this project, the Delphi method often incorporates both quantitative and qualitative elements. Participants are not only asked to provide estimates or predictions but also to justify their responses with explanations or reasoning. The iterative structure of Delphi surveys allows participants to reconsider their responses in light of aggregated group feedback, thereby improving the quality of the results.
The Delphi method is a structured, iterative process used to collect and synthesize expert judgments on complex and uncertain issues. Originally developed for forecasting purposes, the method is particularly useful in situations where empirical data may be limited or when future conditions are inherently uncertain. A classical Delphi study typically involves several key characteristics: anonymity of participants, iterative rounds of questioning, provision of feedback between rounds, and aggregation of group responses into statistical summaries. These features are designed to minimize the influence of dominant participants and groupthink, encourage independent views, and gradually move the group towards more considered and refined judgments (generate group consensus). In modified applications, including this project, the Delphi method often incorporates both quantitative and qualitative elements. Participants are not only asked to provide estimates or predictions but also to justify their responses with explanations or reasoning. The iterative structure of Delphi surveys allows participants to reconsider their responses in light of aggregated group feedback, thereby improving the quality of the results.
The national Delphi survey addressed a wide range of topics central to the US agri-sector, particularly those influenced by federal policy and national market dynamics. Key topics included:
These topics reflect critical components of agri–policy and market systems that are expected to shape the future trajectory of US agriculture. By focusing on these areas, the survey captures expert perspectives on how institutional programs and socio-market drivers may evolve over time.
The national Delphi survey addressed a wide range of topics central to the US agri-sector, particularly those influenced by federal policy and national market dynamics. Key topics included:
These topics reflect critical components of agri–policy and market systems that are expected to shape the future trajectory of US agriculture. By focusing on these areas, the survey captures expert perspectives on how institutional programs and socio-market drivers may evolve over time.
In contrast, the state-level surveys focused on issues that are more region-specific but still highly relevant to broader agri-food system transformations. Across OH, GA, and NA, participants were asked about:
These topics reflect localized production realities, environmental conditions, and technological adoption patterns. For example, irrigation and other farm management practices may differ significantly between the three states due to climatic and hydrological differences (for irrigation), regional market opportunities and institutional support (for emerging crops and BMPs).
In contrast, the state-level surveys focused on issues that are more region-specific but still highly relevant to broader agri-food system transformations. Across OH, GA, and NA, participants were asked about:
These topics reflect localized production realities, environmental conditions, and technological adoption patterns. For example, irrigation and other farm management practices may differ significantly between the three states due to climatic and hydrological differences (for irrigation), regional market opportunities and institutional support (for emerging crops and BMPs).
Survey respondents were provided with graphical representations of trends over the past 15–20 years for each variable included in the Delphi questionnaires. These visualizations served as a baseline, helping participants anchor their expectations in observed patterns while still allowing room for foresight. Participants were then asked to estimate the values of these variables for the year 2050. In addition to providing point estimates, respondents were also asked to indicate their level of confidence in their predictions. This adds an important layer of information for more nuanced analysis and increases the reliability of the results.
Survey respondents were provided with graphical representations of trends over the past 15–20 years for each variable included in the Delphi questionnaires. These visualizations served as a baseline, helping participants anchor their expectations in observed patterns while still allowing room for foresight. Participants were then asked to estimate the values of these variables for the year 2050. In addition to providing point estimates, respondents were also asked to indicate their level of confidence in their predictions. This adds an important layer of information for more nuanced analysis and increases the reliability of the results.
Beyond quantitative forecasts, the survey design placed strong emphasis on collecting qualitative data in the form of participant rationales. Respondents were asked to explain why they expected certain variables to increase, decrease, or remain stable by 2050. This qualitative component is crucial for understanding the mechanisms driving expected changes. While numerical forecasts provide an indication of direction and magnitude, the accompanying explanations reveal the underlying assumptions, beliefs, and mental models of the participants.
Beyond quantitative forecasts, the survey design placed strong emphasis on collecting qualitative data in the form of participant rationales. Respondents were asked to explain why they expected certain variables to increase, decrease, or remain stable by 2050. This qualitative component is crucial for understanding the mechanisms driving expected changes. While numerical forecasts provide an indication of direction and magnitude, the accompanying explanations reveal the underlying assumptions, beliefs, and mental models of the participants.
Analysis of the responses across both national and state-level surveys reveal several major categories of drivers that are expected to shape future outcomes:
Across all responses, overall, a central theme emerges: the future of the US agri-food system will be shaped by changes in climate and the roles and interactions of different actors and institutions. Rather than being driven by a single factor, changes in the values of key variables are expected to result from the interplay of a range of forces by 2050.
Analysis of the responses across both national and state-level surveys reveal several major categories of drivers that are expected to shape future outcomes:
Across all responses, overall, a central theme emerges: the future of the US agri-food system will be shaped by changes in climate and the roles and interactions of different actors and institutions. Rather than being driven by a single factor, changes in the values of key variables are expected to result from the interplay of a range of forces by 2050.
