Coinciding with the launch of AI Agents, CARTO's third State of Spatial Data Science Report reveals spatial data science is core to 73% of respondents' business strategy

SAN FRANCISCO, July 17, 2024 /PRNewswire/ -- CARTO, the cloud-native spatial analysis platform, today announced the launch of CARTO AI Agents in private preview, the industry-leading AI tool that combines geospatial technology with AI. AI Agents enable decision-makers to address vital spatial questions quickly, democratizing access to spatial analytics and driving improved decision-making.

The introduction of AI Agents aligns with the release of the third edition of CARTO's State of Spatial Data Science Report, which found that nearly three-quarters (73%) of respondents say Spatial Data Science is core to their business strategy. While spatial analysis has grown, a quarter of organizations are not using AI in their spatial data science initiatives and only 31% of organizations have invested in AI tools and technologies. As AI solutions continue to grow, 15% are holding out, reporting that they don't plan to make any AI investments.

With the introduction of CARTO AI Agents, the barriers of complexity that have traditionally limited map application use to geospatial experts are no longer in place. Leveraging Large Language Models (LLMs), AI Agents provide a more intuitive, conversational interface, allowing users of all technical backgrounds to navigate and analyze complex spatial data easily.

"Geospatial data is often isolated from other business data, affecting decision-making," said Javier de la Torre, founder and CSO of CARTO. "The Spatial Data Science field is on the cusp of an industry-wide transformation as AI allows quick answers to spatial questions and wider access to spatial analytics. With CARTO's AI Agents, businesses can transform their approach to problem-solving, plan and execute solutions, and adapt to changing scenarios in a specific location or across the globe."

This solution allows CARTO customers to effortlessly derive actionable insights from maps through intuitive, natural-language interactions, enhancing their understanding and engagement with spatial data. AI Agents unlock location data in a way that revolutionizes each industry it touches. From improved customer insights to cost savings, it enables seamless spatial analysis, making location intelligence and its insights accessible to everyone.

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, but it also eliminates the need for specialist geospatial knowledge, allowing users to "ask the map" without needing to understand every detail of the geospatial application.
  • Enhanced user and stakeholder engagement: Analysis never needs to feel static and everyone in the organization can pose questions.
  • Instant and insightful responses: Spatial data can be inherently complex and difficult to interpret but with AI Agents, users can now rapidly provide understandable, actionable insights.
  • Adaptive reasoning: Access insights adapted to user queries and dynamic reasoning about map data, offering tailored and precise responses.

CARTO AI Agents streamline problem-solving by creating actionable plans and utilizing diverse tools, adapting strategies as needed for efficient solutions.

CARTO customer, Aramex, shared the following about AI Agents, "Determining the best routes for drivers is key to providing great customer service and improving profitability in parcel delivery, but last-mile delivery operations can be difficult to optimize. CARTO's AI Agents will help our operational managers quickly get detailed information on delivery routes in a simplified way, leading to more efficient routes, saved costs, and improved customer satisfaction."

As businesses continue to uncover the benefits of spatial analysis, CARTO's latest report provides further insights into the Spatial Data Science landscape, including:

  • On-prem data silos are breaking down: Nearly 70% of respondents confirm doing spatial analysis on the cloud, an increase of 15 percentage points from 2022.
  • GIS is no longer the leading profession for those in Spatial Data Science: Over half (52%) of all respondents have data analysts doing spatial data science, followed by data scientists (45%) and GIS professionals ranking third (44%).
  • Organizations that leverage spatial data have matured: Only 25% of organizations use spatial data for simple analysis and visualizations, while close to half of the organizations surveyed have matured to using the technology to run localized, one-off analysis (22%) or build more complex and iterative pipelines (22%).

"As Spatial Data Science continues to evolve and become more embedded across multiple industries, this report highlights both the opportunities and challenges that lie ahead," said  Michael Johns, Geospatial Specialist Leader at Databricks. "From issues that we have been facing for years - such as open data availability, interoperability and talent scarcity - to newer developments like AI which are set to revolutionize the way we work, it's more critical than ever to understand the geospatial landscape."

To review the full findings of this year's State of Spatial Data Science report, visit https://go.carto.com/state-spatial-data-science-2024. For more information about CARTO visit www.carto.com. 

About CARTO
From smartphones to connected cars, location data is changing the way we live and the way we run businesses. Everything happens somewhere, but visualizing data to see where things are isn't the same as understanding why they happen there. CARTO is the world's leading cloud-native Location Intelligence platform, enabling organizations to use spatial data and analysis for more efficient delivery routes, better behavioral marketing, strategic store placements, and much more. Data Scientists, Developers, and Analysts use CARTO to optimize business processes, and predict future outcomes through the power of Spatial Data Science. www.carto.com

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