{"id":577708,"date":"2025-08-05T21:05:17","date_gmt":"2025-08-05T21:05:17","guid":{"rendered":"https:\/\/www.esri.com\/en-us\/industries\/blog\/?post_type=blog&#038;p=577708"},"modified":"2025-08-05T21:05:18","modified_gmt":"2025-08-05T21:05:18","slug":"the-agriculture-sig-at-the-esri-2025-user-conference","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference","title":{"rendered":"The Agriculture SIG at the Esri 2025 User Conference"},"content":{"rendered":"<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"798\" height=\"637\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/image.png\" alt=\"\" class=\"wp-image-577709\" style=\"width:840px;height:auto\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png 798w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image-300x239.png 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image-768x613.png 768w\" sizes=\"auto, (max-width: 798px) 100vw, 798px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">If you missed the Agriculture SIG at Esri\u2019s 2025 User Conference, here\u2019s a brief summary: the session, led by Mark Dann, Dr. Elvis Takow, and myself from Esri, featured presentations on ArcGIS as an Artificial Intelligence (AI) Platform and how to refocus AI on <strong><em>Agriculture Intelligence<\/em><\/strong>. Afterwards, a panel discussion included representatives from AC Foods, Land O\u2019Lakes, and Texas A&amp;M.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"h-the-arcgis-ai-platform-by-dr-elvis-takow\">The ArcGIS AI Platform by Dr. Elvis Takow<\/h2>\n\n<p class=\"undefined block-editor-paragraph\">As a summary of many sessions at the conference,&nbsp; Dr. Takow presented ArcGIS as a geospatial AI platform that uses artificial intelligence to increase productivity, support decision-making, and drive innovation. Its three main components are:<\/p>\n\n<ul class=\"wp-block-list\">\n<li>GeoAI analysis for automated data creation, extraction, and analysis,<\/li>\n\n<li>AI assistants with conversational interfaces to streamline workflows,<\/li>\n\n<li>An underlying AI framework supporting both features.<\/li>\n<\/ul>\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"975\" height=\"548\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/image-1.png\" alt=\"\" class=\"wp-image-577710\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image-1.png 975w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image-1-300x169.png 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image-1-768x432.png 768w\" sizes=\"auto, (max-width: 975px) 100vw, 975px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">To meet this technological vision, Esri is updating its AI features to include Assistants, Skills, Agents, and pre-trained models. The platform is designed to remain extensible and customizable for different industries and needs. The framework also allows for the integration of AI, deep learning, and large language models, while also supporting developers in creating custom AI services and integrations.&nbsp;&nbsp;&nbsp;&nbsp;<\/p>\n\n<p class=\"undefined block-editor-paragraph\">The challenge for the Agriculture GIS community will be to carefully introduce a broad range of capabilities into an industry that must succeed given the constant pressures of producing a food supply for a growing population.&nbsp;&nbsp; For that, we need <strong>Agriculture Intelligence<\/strong>, as discussed in the next section.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"h-agriculture-intelligence-by-nick-short\">Agriculture Intelligence by Nick Short<\/h2>\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"982\" height=\"553\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic1.jpg\" alt=\"\" class=\"wp-image-577715\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic1.jpg 982w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic1-300x169.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic1-768x432.jpg 768w\" sizes=\"auto, (max-width: 982px) 100vw, 982px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">While we have heard that ArcGIS is a key Geospatial AI Platform for innovation, how can that help agriculture?&nbsp;&nbsp;&nbsp; This presentation briefly explained how to approach AI appropriately and in a relevant way, why now is the right time, how we can avoid past mistakes, and how Esri&#8217;s experience and longevity benefits the agriculture industry.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"575\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic2-1024x575.jpg\" alt=\"\" class=\"wp-image-577716\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic2-1024x575.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic2-300x168.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic2-768x431.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic2.jpg 1142w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">In considering the integration of artificial intelligence (AI) within the agricultural sector, it is pertinent to pose the question: \u201cWhat defines AI for Agriculture?\u201d This inquiry serves as an invitation to ongoing dialogue about the evolving role of AI in agricultural practice, both now and in the years ahead.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">A central concept must remain at the forefront of this discussion: <strong>trust<\/strong>.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">For the agricultural industry, trust is paramount, particularly in the context of emerging technologies such as AI. Producers and stakeholders often greet technological innovation with skepticism, expressing concerns regarding data privacy, security, and the complexity or usability of new systems. Moreover, the industry\u2019s persistent economic pressures amplify the need for reliability and assurance before widespread adoption can occur.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">The core challenge, therefore, is to determine how the agriculture sector will navigate the adoption of AI technologies in a manner that both fosters and maintains trust within the community.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"577\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic3-1024x577.jpg\" alt=\"\" class=\"wp-image-577717\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic3-1024x577.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic3-300x169.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic3-768x433.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic3.jpg 1211w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">Examining the history of AI offers insights into its patterns of trust and adoption within industry.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">Unfortunately, AI\u2019s development is marked by alternating periods of growth and decline\u2014often referred to as \u201c<a href=\"https:\/\/en.wikipedia.org\/wiki\/AI_winter\">AI Winters<\/a>\u201d\u2014where expectations were not met, leading to phases of disillusionment.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">In the 1980s, AI enjoyed a surge of popularity, with major government organizations&nbsp; investing in artificial intelligence to capture human knowledge in the form of expert systems.&nbsp;&nbsp; AI was seen as a promising tool for tackling large-scale challenges, including climate change research and precision agriculture. This period was marked by optimism and high expectations regarding AI\u2019s potential to revolutionize data analysis and decision-making, leading to significant research and practical applications in key industries.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">By the late 1990s, unfortunately, many organizations discontinued their AI program, as the industry pivoted to the web and away from the dream of AI. During that period, the term &#8220;AI&#8221; was sometimes avoided due to previous unmet promises,&nbsp; where it was often called <strong><em>Almost Implemented<\/em><\/strong>. &nbsp;From these experiences, several lessons emerged from that era:<\/p>\n\n<p class=\"undefined block-editor-paragraph\"><strong><u>1. Scalability Limitations<\/u><\/strong><\/p>\n\n<p class=\"undefined block-editor-paragraph\">A significant challenge was managing and storing very large datasets, specifically with respect to the variety and velocity of data. Database management systems at the time did not adequately address these needs, highlighting the importance of robust and adaptable data management infrastructures\u2014particularly relevant in sectors like agriculture.<\/p>\n\n<p class=\"undefined block-editor-paragraph\"><strong><u>2. Too Much Dependence on Open Source Tools<\/u><\/strong><\/p>\n\n<p class=\"undefined block-editor-paragraph\">Due to a limited number of commercial solutions, there was heavy reliance on internally developed tools and open-source software, which created maintenance and security concerns after personnel changes.<\/p>\n\n<p class=\"undefined block-editor-paragraph\"><strong><u>3. The Importance of High-Quality Training Data<\/u><\/strong><\/p>\n\n<p class=\"undefined block-editor-paragraph\">Developing effective machine learning models depended on accurate, locally informed training datasets. Efforts were made to collect direct satellite data worldwide to enhance predictive performance, including successful applications such as improved hurricane forecasting.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">Currently, technological advancements have addressed many scalability and infrastructure issues, and numerous established companies provide reliable AI solutions. However, the ongoing challenge remains the availability and quality of training data, especially in fields like agriculture where trust and data quality are challenging. In an environment where misinformation can affect outcomes, maintaining trustworthy, accurate, and relevant AI systems is critical to ensuring continued progress and avoiding future setbacks.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"577\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic4-1-1024x577.jpg\" alt=\"\" class=\"wp-image-577718\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic4-1-1024x577.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic4-1-300x169.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic4-1-768x432.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic4-1.jpg 1204w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">The long&nbsp; answer for agriculture is to focus on carefully inserting AI into existing workflows in the Ag value chain.&nbsp;&nbsp;&nbsp;&nbsp;<\/p>\n\n<p class=\"undefined block-editor-paragraph\">Let\u2019s take cotton as an example.&nbsp; Cotton generates roughly $7.1B in US cash receipts, with a third produced in drought-prone Texas, which relies heavily on irrigation from sources like the Ogallala aquifer\u2014 expected to dry up within 50 to 100 years. In 2022, about 74% of farmers abandoned their crops and opted for insurance payouts. Field yields influence where processors locate gins to reduce transport costs, affecting the broader supply chain and sales.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">AI can be applied in many areas to the Cotton Industry: Spatial Data Science aids market analysis for a variety of cultivars; Knowledge Graphs help configure and bale traceability in supply chains; Digital twins simulate gin operations; and LLMs can leverage knowledge graphs of the cotton process and overall state of production.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">However, investing in AI for yield forecasting is particularly valuable, as accurate predictions are critical to the entire supply chain. Let&#8217;s examine this further.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"584\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic5-1024x584.jpg\" alt=\"\" class=\"wp-image-577719\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic5-1024x584.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic5-300x171.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic5-768x438.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic5.jpg 1209w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">Here&#8217;s a straightforward example of estimating cotton yield in North Texas by combining temperature and vegetation data based on growing degree days (see presentation on <a href=\"https:\/\/mediaspace.esri.com\/media\/t\/1_cfaqj1rf\">Raster Analytics<\/a>).<\/p>\n\n<p class=\"undefined block-editor-paragraph\">To forecast yield at the field level for informed farming decisions, the system must recognize field locations. This task uses deep learning, and Esri provides pretrained geospatial models that simplify integration into workflows.&nbsp; With predictive forecasts, farmers can identify underperforming areas and consider conservation or other farm management practices to improve outcomes.<\/p>\n\n<p class=\"undefined block-editor-paragraph\">While guidance from experts supports this approach, validating results requires structured local input from farmers at the field level\u2014county-level USDA data alone isn&#8217;t enough. Local knowledge is crucial for building advanced training sets beyond what pretrained models offer. That&#8217;s why collaboration with companies like Land O\u2019 Lakes and AC Foods, and the Ag GIS community is vital\u2014they have the trusted relationships needed to verify these models. Esri supplies the tools, but extending AI solutions depends on partners&#8217; data and expertise in cooperation with extension services (e.g., Texas A&amp;M AgriLife Extension Service) .<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"579\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic6-1024x579.jpg\" alt=\"\" class=\"wp-image-577720\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic6-1024x579.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic6-300x170.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic6-768x434.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic6.jpg 1213w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n<p class=\"undefined block-editor-paragraph\">In summary, agriculture is a cautious field where errors can cause significant losses. Our role is to ensure AI is fully implemented, with reliable, trusted data management and analytics systems, while involving local agricultural expertise to maintain trusted knowledge. This approach will ensure that AI truly means <strong><em>Agricultural Intelligence<\/em><\/strong>.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"h-the-panel-discussion\">The Panel Discussion<\/h2>\n\n<p class=\"undefined block-editor-paragraph\">To discuss the role of Agriculture Intelligence,&nbsp; the Ag SIG has representatives from both industry and academia, where panelists included (as pictured below, left to right):<\/p>\n\n<ul class=\"wp-block-list\">\n<li>Nick Short, Ag Industry Solutions Manager, Esri<\/li>\n\n<li>Sanaz Havaei, Business Application Analyst, AC Foods<\/li>\n\n<li>Kirk Wythers, Business Value Lead, Land O\u2019 Lakes<\/li>\n\n<li>Mike Buser, Professor, Endowed Chair in Cotton Engineering, Ginning, and Mechanization, Texas A&amp;M AgriLife<\/li>\n\n<li>Mark Dann, Sr. Account Manager, Esri<\/li>\n<\/ul>\n\n<p class=\"undefined block-editor-paragraph\">The panel discussed the following questions:<\/p>\n\n<p class=\"undefined block-editor-paragraph\"><em>What opportunities do you see to leverage ML for Predictive Yield Forecasting, and what impact could it have on the business?<\/em><\/p>\n\n<p class=\"undefined block-editor-paragraph\"><em>\u201cWhat are some of the ways you are using AI &#8211; Advanced Geospatial Analytics in your various businesses and R&amp;D applications?\u201d&nbsp;<\/em><\/p>\n\n<p class=\"undefined block-editor-paragraph\">The general consensus amongst the group was that trusted AI, like Data Science, depends on a solid data management infrastructure to ensure that the algorithms are fed quality data.<\/p>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"686\" src=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/AgSig-pic7-1024x686.jpg\" alt=\"\" class=\"wp-image-577721\" srcset=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic7-1024x686.jpg 1024w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic7-300x201.jpg 300w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic7-768x514.jpg 768w, https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/AgSig-pic7.jpg 1269w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>","protected":false},"author":1826,"featured_media":0,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[6421,113,831,191,142],"tags":[150],"class_list":["post-577708","blog","type-blog","status-publish","format-standard","hentry","category-agriculture","category-artificial-intelligence--ai","category-environment-and-natural-resources","category-natural-resources","category-sustainability","tag-ai","industry-agriculture","industry-environment-and-natural-resources","industry-gis-it"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>The Agriculture SIG at the Esri 2025 User Conference<\/title>\n<meta name=\"description\" content=\"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Agriculture SIG at the Esri 2025 User Conference\" \/>\n<meta property=\"og:description\" content=\"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference\" \/>\n<meta property=\"og:site_name\" content=\"Industry Blogs\" \/>\n<meta property=\"article:modified_time\" content=\"2025-08-05T21:05:18+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png\" \/>\n\t<meta property=\"og:image:width\" content=\"798\" \/>\n\t<meta property=\"og:image:height\" content=\"637\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference\",\"url\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference\",\"name\":\"The Agriculture SIG at the Esri 2025 User Conference\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/image.png\",\"datePublished\":\"2025-08-05T21:05:17+00:00\",\"dateModified\":\"2025-08-05T21:05:18+00:00\",\"description\":\"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform\",\"breadcrumb\":{\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage\",\"url\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png\",\"contentUrl\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png\",\"width\":798,\"height\":637},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"The Agriculture SIG at the Esri 2025 User Conference\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/#website\",\"url\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/\",\"name\":\"Industry Blogs\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/#\/schema\/person\/e2de8356a33181b6946e31de6f4933bd\",\"name\":\"Nick Short\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2026\/02\/nick-headshot-150x150.png\",\"contentUrl\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2026\/02\/nick-headshot-150x150.png\",\"caption\":\"Nick Short\"},\"description\":\"Nick Short has dedicated his career to integrating Esri\u2019s GIS technology into the agricultural sector, including a seven-year tenure working with Esri\u2019s USDA account team. With over four decades of IT experience, he has specialized in AI, business intelligence, advanced analytics, GIS, and data management. His professional journey includes senior management roles at Gartner, SAP, SAS, and several Silicon Valley start-ups. Additionally, he spent a decade at NASA Goddard, where he focused on remote sensing, high performance computing, and AI within the Earth sciences and agriculture sector.\",\"sameAs\":[\"https:\/\/www.esri.com\/about\/newsroom\/author\/short_nick\",\"https:\/\/www.linkedin.com\/in\/nickshortjr\/\"],\"url\":\"https:\/\/www.esri.com\/en-us\/industries\/blog\/author\/nshort\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"The Agriculture SIG at the Esri 2025 User Conference","description":"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference","og_locale":"en_US","og_type":"article","og_title":"The Agriculture SIG at the Esri 2025 User Conference","og_description":"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform","og_url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference","og_site_name":"Industry Blogs","article_modified_time":"2025-08-05T21:05:18+00:00","og_image":[{"width":798,"height":637,"url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference","url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference","name":"The Agriculture SIG at the Esri 2025 User Conference","isPartOf":{"@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage"},"image":{"@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage"},"thumbnailUrl":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-content\/uploads\/2025\/08\/image.png","datePublished":"2025-08-05T21:05:17+00:00","dateModified":"2025-08-05T21:05:18+00:00","description":"Industry Blogs The Agriculture SIG at the Esri 2025 User Conference Agriculture Intelligence, Artificial Intelligence, ArcGIS AI Platform","breadcrumb":{"@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#primaryimage","url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png","contentUrl":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/image.png","width":798,"height":637},{"@type":"BreadcrumbList","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/the-agriculture-sig-at-the-esri-2025-user-conference#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.esri.com\/en-us\/industries\/blog"},{"@type":"ListItem","position":2,"name":"The Agriculture SIG at the Esri 2025 User Conference"}]},{"@type":"WebSite","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/#website","url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/","name":"Industry Blogs","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.esri.com\/en-us\/industries\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/#\/schema\/person\/e2de8356a33181b6946e31de6f4933bd","name":"Nick Short","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/en-us\/industries\/blog\/#\/schema\/person\/image\/","url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2026\/02\/nick-headshot-150x150.png","contentUrl":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2026\/02\/nick-headshot-150x150.png","caption":"Nick Short"},"description":"Nick Short has dedicated his career to integrating Esri\u2019s GIS technology into the agricultural sector, including a seven-year tenure working with Esri\u2019s USDA account team. With over four decades of IT experience, he has specialized in AI, business intelligence, advanced analytics, GIS, and data management. His professional journey includes senior management roles at Gartner, SAP, SAS, and several Silicon Valley start-ups. Additionally, he spent a decade at NASA Goddard, where he focused on remote sensing, high performance computing, and AI within the Earth sciences and agriculture sector.","sameAs":["https:\/\/www.esri.com\/about\/newsroom\/author\/short_nick","https:\/\/www.linkedin.com\/in\/nickshortjr\/"],"url":"https:\/\/www.esri.com\/en-us\/industries\/blog\/author\/nshort"}]}},"text_date":"August 5, 2025","author_name":"Nick Short","author_page":"https:\/\/www.esri.com\/en-us\/industries\/blog\/author\/nshort","custom_image":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/Mt-Yonah-final.png","primary_product":"Agriculture","tag_data":[{"term_id":150,"name":"AI","slug":"ai","term_group":0,"term_taxonomy_id":150,"taxonomy":"post_tag","description":"","parent":0,"count":8,"filter":"raw"}],"category_data":[{"term_id":6421,"name":"Agriculture","slug":"agriculture","term_group":0,"term_taxonomy_id":6421,"taxonomy":"category","description":"","parent":191,"count":2,"filter":"raw"},{"term_id":113,"name":"Artificial Intelligence \u2502 AI","slug":"artificial-intelligence-%e2%94%82-ai","term_group":0,"term_taxonomy_id":113,"taxonomy":"category","description":"","parent":0,"count":7,"filter":"raw"},{"term_id":831,"name":"Environment and Natural Resources","slug":"environment-and-natural-resources","term_group":0,"term_taxonomy_id":831,"taxonomy":"category","description":"","parent":0,"count":20,"filter":"raw"},{"term_id":191,"name":"Natural Resources","slug":"natural-resources","term_group":0,"term_taxonomy_id":191,"taxonomy":"category","description":"","parent":0,"count":12,"filter":"raw"},{"term_id":142,"name":"Sustainability","slug":"sustainability","term_group":0,"term_taxonomy_id":142,"taxonomy":"category","description":"","parent":0,"count":4,"filter":"raw"}],"product_data":{"errors":{"invalid_taxonomy":["Invalid taxonomy."]},"error_data":[]},"primary_product_link":"https:\/\/www.esri.com\/en-us\/industries\/blog\/industry\/agriculture","short_description":"If you missed last week's Agriculture SIG at Esri\u2019s 2025 User Conference, here\u2019s a brief summary: The session, led by Mark Dann, Dr. Elvis Takow,","image":"https:\/\/www.esri.com\/en-us\/industries\/blog\/app\/uploads\/2025\/08\/Mt-Yonah-final-card.png","_links":{"self":[{"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/article\/577708","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/users\/1826"}],"version-history":[{"count":0,"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/article\/577708\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/media?parent=577708"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/categories?post=577708"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.esri.com\/en-us\/industries\/blog\/wp-json\/wp\/v2\/tags?post=577708"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}