The introduction of AI agents coincides with the release of the third edition of CARTO's State of Spatial Data Science report, with nearly three-quarters (73%) of respondents saying spatial data science is core to their business strategy. While spatial analytics is expanding, a quarter of organizations are not using AI for their spatial data science efforts, and only 31% are investing in AI tools and technologies. As AI solutions continue to expand, 15% are taking a wait-and-see approach, reporting they have no plans to invest in AI at all.
The introduction of CARTO AI agents removes the complexity barriers that traditionally limited the use of mapping applications to geospatial experts. Leveraging large-scale language models (LLMs), AI agents provide a more intuitive conversational interface, enabling users of all technical backgrounds to easily navigate and analyze complex spatial data.
“Geospatial data is often disconnected from other business data and how it influences decision-making,” he said. Javier de la Torre“The field of spatial data science is on the brink of an industry-wide transformation as AI makes it possible to answer spatial questions faster and expands access to spatial analytics,” said , CARTO founder and CSO. “CARTO's AI agents enable businesses to transform their approach to problem solving, plan and execute solutions, and adapt to changing scenarios in specific locations and across the world.”
The solution enables CARTO customers to easily extract actionable insights from maps through intuitive, natural language interactions, enhancing their understanding and engagement with spatial data. AI agents unlock location data in ways that revolutionize each industry they touch. From improving customer insights to reducing costs, seamless spatial analytics become possible, democratizing location intelligence and insights.
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Key benefits of CARTO AI agents include:
- No coding or geospatial skills required. Access to spatial insights is now truly democratized: AI not only eliminates the need for code, it also eliminates the need for specialized geospatial knowledge, allowing users to “ask the map” without needing to understand all the details of a geospatial application.
- Enhanced user and stakeholder engagement: Analysis doesn't have to be static and can be questioned by anyone in the organization.
- Immediate and insightful response: Spatial data is inherently complex and can be difficult to interpret, but AI agents can help users understand it and provide actionable insights quickly.
- Adaptive Inference: Access insights that adapt to your queries and dynamic reasoning about map data to deliver personalized, precise responses.
Aramex, a CARTO customer, had this to say about the AI agent: “Determining the optimal route for drivers is key to providing great customer service and improving parcel delivery profitability, but optimizing last-mile delivery operations can be difficult. CARTO's AI agent helps our operations managers easily and quickly get detailed delivery route information, leading to more efficient routes, reduced costs, and increased customer satisfaction.”
As businesses continue to discover the benefits of spatial analytics, CARTO’s latest report offers further insights into the state of spatial data science, including:
- On-premise data silos are collapsing. Nearly 70% of respondents confirmed they are running spatial analytics on the cloud, up 15 percentage points from 2022.
- GIS is no longer the primary profession in spatial data scienceMore than half of respondents (52%) have data analysts working on spatial data science, followed by data scientists (45%) and GIS professionals (44%).
- Organizations leveraging spatial data are maturing. While only 25% of organizations use spatial data for simple analysis and visualization, nearly half of the organizations surveyed have matured to the point where they can use the technology to perform localized, one-off analyses (22%) or build more complex, iterative pipelines (22%).
“As spatial data science continues to evolve and permeate multiple industries, this report highlights both the opportunities and challenges ahead,” said Michael Jones“From issues we've faced for years, like open data availability, interoperability, and talent shortages, to new developments like AI that are revolutionizing the way we work, understanding the geospatial landscape is more important than ever,” said , Geospatial Specialist Lead at Databricks.
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