“It’s like a rock concert, where Jack Dangermond is the lead guitarist.”
I don’t remember who told me this before attending my first Esri User Conference, but they nailed it with that description. This past week was full of networking, community, digital twins, conservation, and AI (including all its pros and cons). It was also an impressive demonstration of what is possible with evolving technology and what we have the power to change for good if it’s in the right hands.
If there was one word that defined this year’s conference, it was community. Jack Dangermond, CEO and founder of Esri, opened the closing session by admitting that the original conference theme, “GIS Creating a More Intelligent World,” was meant to include one more word: “together.”
After a week spent watching thousands of practitioners from over a hundred countries share ideas, challenges, and solutions with each other, the leadership team agreed the omission was a mistake. This wasn’t just a technical gathering—it was a demonstration of collective intelligence in action, where geography and spatial thinking served as the shared language enabling people to understand each other and solve problems no single organization could tackle alone. Attendees echoed the sentiment directly, calling for more opportunities to learn from one another: real success stories, more mentoring, and more spaces where practitioners can experiment together and share what they discover.
AI: From Fear to Cautious Optimism, But Not Without Real Costs
Nowhere was the shift in mood more visible than around artificial intelligence. Two years ago, when Esri asked its audience how many feared AI would take their jobs, nearly every hand in the room went up. When asked the same question again this year, only a handful of hands rose. That change reflects a hard-won understanding: AI is a tool, not a replacement. It’s a hammer, as one leader put it, but not every problem is a nail. The good news was substantial. AI is helping GIS practitioners create and analyze data, automate tedious processes, and even generate code, while GIS in turn is giving AI the structured, science-based context it needs to be trustworthy. New capabilities like MCP will soon let organizations expose their own maps and models to the broader agentic AI ecosystem.
However, the optimism was tempered by real concern. Attendees pressed hard on where the money and control actually sit, worried that GIS professionals are being swept along by decisions made in Silicon Valley boardrooms rather than by their own communities. Leadership acknowledged the tension without fully resolving it: future costs could emerge if organizations choose to build custom applications on top of external large language models, and nobody, including Esri, claims to know exactly where this technology lands.
Esri Chief Scientist Dawn Wright raised perhaps the most sobering point of the week, the environmental cost of AI itself. Dangermond then cited a formula shared at a recent Microsoft conference, suggesting that intelligence effectively equals energy consumption, and that consumption carries a real carbon cost. Esri leadership maintained that their own AI usage remains comparatively lightweight next to the industry’s largest models but committed to greater transparency about their cloud partnerships and energy footprint going forward.
Digital Twins: You Already Have One
The definition of a digital twin has always been elusive, but leadership at Esri seems to have reframed the concept. GIS, almost by definition, already functions as a digital twin, whether it’s a simple two-dimensional model or a more sophisticated three-dimensional, real-time representation of the world. The real question isn’t whether an organization has one, but how mature it is and what outcome it’s meant to serve.
This topic was widely discussed at this year’s conference; two standout case studies grounded the conference’s digital twin discussions in real-world scale. New Zealand’s Transport Agency shared how it built the country’s first authoritative national transport network model, a living, multimodal digital twin covering roads, rail, ferries, and pathways, unified from previously fragmented and non-standardized local data through a multi-year digital engineering program. The City of Raleigh, North Carolina described a more incremental but equally ambitious journey. Facing rapid population growth and pressure on transportation and city services, Raleigh has spent over a decade evolving its GIS into a true digital twin through layering in drone-derived imagery, BIM models from developers, and even physics-based microclimate models to study urban heat block by block. Both stories underscored a common theme: a digital twin isn’t a single product to buy, but an evolving, living system built from whatever authoritative data an organization already has.
Conservation: A Living Laboratory at the Dangermond Preserve
The conservation thread began early in the conference, when keynote speaker Kristine Tompkins spoke about how GIS underpins the work of Tompkins Conservation, her organization dedicated to protecting and restoring wild landscapes. Her talk resonated deeply, so much so that the Map Gallery Awards host referenced it directly, noting that hearing Tompkins speak made the conference’s “creating a more intelligent world” theme feel more urgent and more personal. It was a reminder that maps aren’t just data but tools for showing people the places worth caring about.
That same spirit carried through to the Jack and Lauren Dangermond Preserve, a 24,000-acre stretch of protected California coastline cared for by the Nature Conservancy. Kelly Easterday, who leads technology and data science for the preserve, described building a true “digital twin for nature”—one that unites fragmented ecological data across more than a hundred sensors, forty institutional partners, and over 160 active research projects into a single, living platform anyone can explore.
It was a vivid demonstration of what conservation looks like when data, technology, and long-term stewardship come together and turn a single protected landscape into a model the rest of the world can learn from. Attendees called for more sessions on exactly these themes — oceans, stormwater, flooding, and fire — signaling where the community wants to focus its collective intelligence next.
Closing Thoughts
As the conference concluded, Dangermond returned to something more personal: a realization about the relationship between what people do and who they become through their work. He traced it back to his own early days in GIS and computer mapping, when he found it exciting to apply his work to something meaningful. That excitement changed him, and the more it changed him, the more he wanted to do.
He described it as a kind of feedback loop, saying, “What I did changed who I am… and it made me want to do more.” He’d seen the same pattern play out across the community all week: people getting a taste of purposeful work with GIS, wanting more of it, and becoming more purposeful people in the process.
Attendees were encouraged to carry that momentum home—to write down what they’d learned and keep the thread alive rather than letting it fade once the routines of ordinary work resumed. The invitation, as always, was to keep the feedback coming, because, as he reminded the room, Esri can only get better at supporting its community if the community keeps telling it how.
