Within the next 15 years, geospatial artificial intelligence will fundamentally change how organisations view and act in the physical world.

That’s according to a new report released by Eagleview, an aerial imagery and geospatial intelligence company.

‘The Future of Geospatial Intelligence: 2026 – 2040’ predicts that AI, agentic systems and continuously updated world models will push geospatial artificial intelligence (GeoAI) “beyond maps and dashboards” into real-time, AI-powered decision-making systems.

“For decades, geospatial intelligence has helped organisations understand what the world looks like,” said Piers Dormeyer, CEO of Eagleview.

“Over the next 15 years, it will help them decide what to do next and predict what happens after.”

GeoAI as a living system

The report, authored by Eagleview’s Head of AI, Dr Dylan Kesler, makes a number of predictions based on several time horizons. They include:

• Geospatial intelligence will move from static maps and reports to natural-language, AI-driven systems that will enable decision makers to ask questions and receive grounded, real-time answers.
• Core GIS capabilities will be integrated into general-purpose AI tools, making spatial reasoning a standard feature of everyday workflows and no longer a specialised function.
• Agentic AI systems will automate data discovery and analysis, producing insights that humans did not ask for, while the people will focus on judgment, validation and accountability.
• Continuously updated, federated geospatial models will replace centralised databases and time-bound datasets, shifting authority toward shared, real-time representations of the physical world.
• Digital twins will become operational platforms that simulate outcomes, test interventions and guide decisions.

“The next generation of geospatial intelligence depends on trusted data, intelligent automation, and systems that can reason at scale,” said Kesler.

“Organisations that succeed will be those that treat geospatial intelligence as a living system. That means one that integrates the physical world into decision-making at machine speed, with human judgment in the loop.”

The ultimate testament

This, effectively, total integration of GeoAI into business decision making will probably even see the use of the term vanish, according to Ed Parsons, Chair of the Board of Directors of the Open Geospatial Consortium, and former Geospatial Technologist with Google.

Writing in Spatial Source in January, Parsons said that “GeoAI [will] likely become a historical term”.

“This isn’t to diminish its importance or the incredible innovations it represents,” he wrote. “Quite the opposite. The eventual disappearance of GeoAI from our lexicon will be the ultimate testament to its value.”

“As AI algorithms become more sophisticated, more accessible and more deeply embedded into every facet of geospatial workflows, the need to call it GeoAI will diminish.

“We won’t be talking about ‘AI-powered mapping’ as a special category; we’ll simply be talking about ‘mapping,’ with the understanding that intelligent automation and analytical capabilities are an intrinsic part of the process.”

Beyond human understanding

Eagleview’s Kesler, writing in the report, says that over the next one to five years, GIS functionality will increasingly be absorbed into conversational AI systems.

The result will be that users will increasingly expect chat-based systems to:

• Natively address temporal patterning and dissimilarity, and present reasoned understandings;
• Generate ad hoc geospatial visualisations on demand;
• Provide insights into regions of uncertainty and disagreement among geospatial artificial intelligence sources and temporal dynamism; and
• Return answers with citations.

Looking further ahead to five to 10 years, GeoAI systems will move beyond query-response interactions to support:

• Automated discovery of relevant datasets;
• Correlation across imagery, text, sensor data and structured records;
• Hypothesis generation and spatial reasoning;
• An intrinsic understanding of objectives, optimisation and returns on investment; and
• Nuanced and unexpected insights and predictions that extend beyond what human users may comprehend.

And looking out to 15 years to the full-on digital twin era, the “culmination of these trends will be the transformation of digital twins from visualisation tools into operational, rapid-cycle, AI-based decision-making interfaces”.

Such a transformation will enable users to ask questions such as “What happens if we intervene here?” and “What is the right course of action, and why have you [the AI] reached that conclusion?”

“In effect, digital twins will become interactive, AI-mediated environments where strategy, operations, and policy converge in continuously updated geospatial information,” Kesler writes.