How to build a geospatial AI roadmap (that actually works)

The text explores the challenges and opportunities in scaling geospatial AI within organizations, highlighting that only a quarter of AI projects achieve their expected return on investment (ROI). It outlines a five-step roadmap to enhance geospatial AI impact, emphasizing the need for strong data governance, workflow automation, and integration of AI into existing tech stacks. The roadmap encourages organizations to transition from individual productivity tools to enterprise-scale automation, ensuring spatial insights contribute directly to decision-making. The text underscores the importance of enabling all team members, from engineers to decision-makers, to interact effectively with AI systems. It concludes by advocating for a continuous cycle of learning and refinement in AI adoption to achieve organization-wide transformation and measurable impact, with examples from industry leaders like BT and Cotality successfully embedding spatial reasoning into their AI strategies.

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