Organizations across industries are adopting AI to automate workflows, accelerate analysis, and expand access to insights. As AI capabilities mature, architects and IT leaders face new design decisions such as how to integrate AI into existing systems, how to govern AI workloads responsibly, and how geospatial data, capabilities, and reasoning fits.
ArcGIS is a geospatial platform that is enhanced with AI. As a geospatial platform, ArcGIS delivers geospatial data, capabilities, and infrastructure that enable organizations to create, manage, analyze, and map geospatial data. It is enhanced with AI to:
AI has become one of the first topics raised when organizations plan new ArcGIS systems. The scope of this lens is to help with that planning. It is written for the architects and technical leaders who have to turn “we should use AI” into concrete design choices, focusing on the patterns, decisions, integration points, and governance that come with putting AI into geospatial systems.
This lens complements and connects the ArcGIS Trust Center, which covers Esri’s AI principles and commitments, and the product documentation covering the features themselves.
New to ArcGIS? Start with the Introduction to ArcGIS for platform context before working through this lens.
The lens is intended primarily for technical leaders, IT architects, and IT/GIS professionals who design AI workloads on or with ArcGIS. This includes readers who come from a GIS background and are adding AI to systems they already run, as well as those that know AI well and are working out how geospatial data and capabilities fit into a wider AI strategy. The lens is written with both in mind.
The lens assumes you arrive with a working knowledge of ArcGIS architecture and a general grasp of AI concepts. The next chapter offers a short primer on both, mostly to settle terminology — it does not try to teach AI from the ground up.
You can read the lens front to back, which is the path we recommend the first time through, or treat it as a reference and pull the chapter you need. A few chapters stand on their own: AI concepts and vocabulary and integration and interoperability.
In particular, the architecture pillars page is worth noting. The ArcGIS Well-Architected Framework is organized around six pillars — reliability, performance and scalability, security, integration, automation, and observability. The pillars chapter in the AI lens does not restate them, it shows where AI workloads change the calculus for each.
This is a living document, refreshed often. Because AI capabilities in ArcGIS move quickly, it refers to them by name and by maturity — announced, private beta, beta, or generally available — rather than by release date. Specific timing shifts often; consult the release notes and the product roadmap for those details.
The ArcGIS Trust Center is where Esri publishes its AI principles, its commitments, and the AI transparency cards for individual features.
ArcGIS Living Atlas of the World provides the authoritative content and pretrained models that are continuously referenced in the chapters ahead.
The Geospatial AI resources page provides capability-specific stories as well as blogs, customer examples, and additional resources.
The product documentation provides feature-level detail on any products and technologies referenced in this lens.