{"id":585509,"date":"2026-07-27T16:40:09","date_gmt":"2026-07-27T16:40:09","guid":{"rendered":"https:\/\/www.esri.com\/en-us\/industries\/blog\/?post_type=blog&p=585509"},"modified":"2026-07-28T13:57:34","modified_gmt":"2026-07-28T13:57:34","slug":"2026-esri-user-conference-creating-a-more-agriculturally-intelligent-world","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/2026-esri-user-conference-creating-a-more-agriculturally-intelligent-world","title":{"rendered":"2026 Esri User Conference: Creating a More (Agriculturally) Intelligent World"},"content":{"rendered":"

Agriculture at Esri’s User Conference<\/h2>\n\n
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Esri’s Jared Beard kicks off Tuesday’s Agriculture Activities<\/em><\/figcaption><\/figure>\n<\/div>\n\n

It was an exciting conference and successful year for the GIS Agriculture community! Not only did the community have many more papers than in recent years (six!), but two Special Achievements in GIS (SAG) were awarded to members of this community[see Section I.]<\/strong>. This is a testament to the great work you all are doing to drive GIS adoption into a challenging industry that has been stressed by volatility in recent years.<\/p>\n\n

This year also highlighted a monumental shift in Esri’s approach to the Ag industry day, where the focus is on “business first” over technology. A major theme throughout the day was the emphasis on careful and “ole school” engineering practices tightly coupled to well-defined business drivers, rather than getting caught up in all the AI hype [see reprint of my talk in Sect. III below]<\/strong>.<\/p>\n\n

Underlining that shift – we were also joined by a distinguished panel who is on the forefront of GIS, AI, and Agriculture . The panel had a great discussion about the challenges their organizations are facing, the state of the industry, and the future of Ag [Sect. II]<\/strong>.<\/p>\n\n

The takeaways from the panel were certainly seen in the sessions throughout the day. Issues ranging from climate change (or “weird weather” as we call it in the US) [Sect. IV.A-D]<\/strong> to driving economic efficiencies [Sect. IV.E-F] <\/strong>were reflected in all the papers presented and serve as requirements for where Esri needs to go to support the Ag industry. To support the industry, Dr. Elvis Takow detailed [Sect. V]<\/strong> the key, current capabilities in the technology stack and how to carefully navigate the geospatial AI journey. <\/p>\n\n

While this blog serves to document 2026, we look forward to many new capabilities from Esri during the year as we move to empower the Ag GIS community for a successful 2027 user conference.<\/p>\n\n

I. Celebrating Special Achievements in (Agricultural) GIS<\/h2>\n\n

Bunge received Esri\u2019s SAG award in recognition for the way Tijs Lips\u2019 and Pitt Onn Wong’s Bunge team has applied GIS at global scale to strengthen responsible sourcing, sustainability, and transparency in the palm oil supply chain. By combining ArcGIS Pro, ArcGIS Online, satellite-based deforestation alerts, supply chain maps, and ground verification workflows, Bunge can trace sourcing areas to mills and supply landscapes, monitor 113.9 million hectares, support EUDR requirements, and demonstrate traceability to customers and stakeholders. As highlighted on pp. 56-7 of their 2026 Sustainability Report<\/a>, this work turns sustainability commitments into operational practice\u2014protecting biodiversity, supporting human rights, and helping suppliers, including smallholder farmers, participate in more sustainable value chains. Bunge\u2019s achievement stands as a powerful example of how GIS can drive measurable environmental and social impact across global agriculture. <\/p>\n\n

The Sugar Cane Growers Cooperative (SCGC) of Florida earned the SAG award in recognition of managing one of agriculture\u2019s most complex harvest logistics operations using a modern, real-time, GIS-driven enterprise system. Because sugar cane must be processed within 24 hours of harvest, SCGC needed to coordinate continuous harvesting, transportation, equipment assignments, and mill capacity across 150 consecutive days with exceptional precision. Working with Esri Professional Services, the team consolidated six disparate systems into a unified ArcGIS-based operational environment powered by real-time data processing, web maps, dashboards, and mobile workflows. The result replaced paper tickets and disconnected spreadsheets with live spatial intelligence that field crews, managers, directors, and executives can use anytime to track harvest progress, optimize resources, reduce downtime, and improve mill efficiency. This transformation has delivered more than $5.5 million in operating expense savings<\/strong> and a triple-digit ROI.<\/p>\n\n

II. The Agriculture Special Interest Group (SIG) Panel<\/h2>\n\n
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Nick Short\/Esri, Dr. Hoda Helmi\/Corteva, Baxter Clark\/SCGC, and Melissa Gayley\/Bunge on the Ag SIG panel.<\/em><\/figcaption><\/figure>\n\n

This year’s panel was constructed to represent the three pillars of success for a geospatial AI journey: 1) business discipline 2) in-depth knowledge of AI and 3) a solid foundation in GIS.<\/p>\n\n

Baxter Clark, VP-Operations at SCGC, brought a business-first perspective to improving how agriculture operations run, which comes from his roots on a cotton farm and experience spanning farming, agronomy, seed technology and consulting. Corteva’s Dr. Hoda Helmi, whose PhD is in AI, emphasized the need to reduce point solutions that prevent coordination at the enterprise level. Her team’s work with the One Seed Digital Twin initiative is a perfect example of how to integrate data, optimize using predictive models, and incorporate agentic AI into closed-loop pipelines. Drawing from over 20 years of GIS experience, Melissa Gayley from Bunge stressed the need for a hub and spoke architecture to bring together pockets of GIS expertise in order to accommodate Bunge’s growing GIS needs.<\/p>\n\n

III. An (Agriculturally) Intelligent World Starts with Trusted Geospatial Data<\/h2>\n\n

Reprinted from AG SIG presentation.<\/em><\/p>\n\n

Artificial intelligence is advancing quickly, but in agriculture, speed alone is not enough. A recommendation that arrives too late, is based on incomplete data, or cannot be trusted can affect decisions that are tied directly to yield, supply chains, and long-term producer confidence. That is why the most important conversation about AI in agriculture is not only about algorithms. It is about the data, human expertise, and geospatial infrastructure required to make those algorithms reliable.<\/p>\n\n

That theme was reinforced throughout the Ag SIG panel discussion. As I listened, I was struck by how much the current conversation around AI echoes earlier periods in the field\u2019s history. I began my career in AI in 1984, and I am often asked what has changed since then.<\/p>\n\n

My answer is that two significant developments have reshaped the field:<\/p>\n\n