Gartner Says Earth Intelligence Is a $20 Billion New Revenue Growth Opportunity for Technology and Service Providers Through 2030
By 2030, Enterprises Will Be Spending More on Earth Intelligence than Governments and Military Bodies Combined
Earth intelligence will significantly impact every industry as it rapidly moves from government to the private sector, with Earth intelligence annual revenue surpassing $4.2 billion in 2030, up from nearly $3.8 billion in 2025, according to Gartner, Inc. The cumulative Earth intelligence direct revenue opportunity for technology product and service providers will reach nearly $20 billion from 2025 to 2030.
This revenue forecast is for technology and service providers, and it focuses on direct revenue from Earth intelligence data, analysis services and software applications. It does not take into account the wider range of Earth intelligence value drivers, which can include productivity improvements and cost avoidance.
Gartner defines Earth intelligence as the application of AI to Earth observation data to deliver solutions specific to industries and business functions. It encompasses gathering and providing Earth observation data, fit-for-purpose transforming it, and then using it to produce actionable insights with domain-specific AI models, tools and applications.
"The future of Earth intelligence will be won by the vendors that move quickly to develop technologies that make sense of the oceans of raw data they collect," said Bill Ray, Distinguished VP Analyst at Gartner.
"The value of Earth intelligence data is only now being realized. For example, vendors are leveraging satellites to pinpoint fallen trees blocking railroad tracks in a storm, monitoring the temperature of every metal refinery to assess global production, counting vehicles to analyze traffic patterns and consumer trends, and track sea cargo to evaluate shipping activity," Ray said. "These unprecedented insights are delivering immense value, and new use cases are being discovered daily as the AI vendor race intensifies with the ever-expanding volume of available data."
Currently, the raw data that fuels Earth intelligence is primarily collected and analyzed by governments. However, there is a shift taking place. In fact, Gartner predicts that by 2030, enterprises will be spending more on Earth intelligence than governments and military bodies combined, accounting for more than 50% of total Earth intelligence, up from less than 15% in 2024.
"As private technology and service providers begin to dominate Earth intelligence, they have the opportunity to sell data, models and applications to companies that lack the resources to analyze data for themselves," Ray said. "Earth intelligence will lead to new markets and offerings for data, models, stand-alone tools and applications as well as capabilities to embed within existing applications. This represents a massive business opportunity for technology product and service providers."
New economics are evolving because very low Earth orbit (VLEO) satellites are cheaper to build and launch, and these satellites are watching the earth in new ways. Radar and hyperspectral techniques see things which used to be invisible, and revisit times can be an hour or less. Private companies are also experimenting with VLEO (very low Earth orbit) which can deliver a resolution as low as 10 cm. That's small enough to spot a mouse.
"This is driving, and will continue to drive, massive amounts of Earth observation data. Combining satellite data with ground observation data from sensors and drones further enhances Earth intelligence value," said Ray. "This is where AI plays a critical role. Unlike many domains, there is a plethora of data. But that data needs to be engineered into fit-for-purpose information to feed industry- and function-specific AI models."
Additional information is available to Gartner clients in the report, High-Tech FutureSight: Earth Intelligence Is an Emerging Multibillion Dollar AI Vendor Race, and Emerging Tech: Top Use Cases for Earth Intelligence in Production Measurement.
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Matt LoDolce
Gartner
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Meghan Moran
Gartner
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