The State of Spatial Analytics 2026 - Register interest!

Summary

Key findings from the survey reveal major changes since 2024. Register interest now and get early access to the State of Spatial Analytics 2026 Report.

This post may describe functionality for an old version of CARTO. Find out about the latest and cloud-native version here.
This post may describe functionality for an old version of CARTO. Find out about the latest and cloud-native version here.
The State of Spatial Analytics 2026 - Register interest!

Across the last few years, the field of Spatial Analytics has dramatically evolved, transforming from a specialized niche into a business-critical function that informs real-time, strategic decisions. 

Our annual report series has tracked this journey, revealing how the industry has shifted from its traditional, niche community to a mainstream, multidisciplinary field.

A screenshot showing the timeline of key findings from previous "State of Spatial" reports
Timeline from the State of Spatial Data Science 2024 Report

How Spatial Analytics has changed

Let's take a look at the most significant shifts we've tracked over the last two years and what they tell us about the future of Spatial Analytics.

Key Area Shift over the last 2 years What will we learn in 2026?
Working with spatial data Nearly 70% of respondents now conduct spatial analysis on the cloud — a 14 percentage point jump from the previous report. This adoption reinforces the cloud as the cornerstone for handling inherently large and complex spatial data. How is this cloud-native approach driving higher performance and scalability for real-time and large-scale spatial workflows?
Platforms and tools Data analysts are using a diverse mix of core libraries (GeoPandas, GDAL), dedicated platforms (CARTO, Esri), and tools (QGIS, Tableau). End-to-end platforms remain popular for simplicity around licensing and implementation, while specialist and open-source solutions continue to serve niche use cases. Which platform combinations and interoperable toolchains are emerging as standard across industries — and which roles (beyond Data Analysts and Data Scientists) are adopting LLMs and AI to support spatial analysis tasks?
Skills and careers Nearly 69% of respondents found it difficult to hire a Spatial Data Scientist, underscoring a sustained skills shortage and growing demand for specialised spatial expertise across the broader data profession. What new training and upskilling strategies are most effective at addressing the talent gap, and which roles are getting reskilled to take on spatial responsibilities?
AI adoption Over 25% of organizations reported not using AI in spatial analytics — mainly due to data security/privacy concerns and unclear organizational use cases. Has AI adoption increased since the last report, and what new barriers (technical, ethical, or operational) remain for integrating AI successfully into spatial workflows?

The key findings from our previous report paint a clear picture of an industry evolving in terms of both democratization and scale.

Get early access to the fourth edition of the State of Spatial Analytics report!

Key findings from the survey reveal major changes since 2024. 

Register interest now and get early access to explore the numbers behind the trends driving the Spatial Analytics landscape, from democratization and integration to the critical roles of the cloud, data governance, and AI adoption. 

Understanding these trends is crucial for navigating the transition from traditional GIS to the intelligent, agent-driven future of our industry.

register interest to the state of spatial analytics 2026