AI/ML and Enabling Technologies: Strategies for Earth Observation Service Providers

"The complexity of multi-modal satellite data, and the insights we can derive from it, make it increasingly necessary for EO service providers to invest in AI and ML solutions."

The current adoption of AI in Earth observation (EO) is limited to simple automation and does not fully take advantage of the self-learning capabilities of artificial intelligence (AI). Furthermore, AI is underused in downstream analytics applications.

This report provides strategic guidance for EO service providers on adopting AI and how AI can be used together with emerging technologies such as foundation models to offer tailored solutions for end users.

Questions answered in this report:

• What is the current level of adoption of AI in EO?
• What role do foundation models play?
• How can generative AI (GenAI) help to build tailored solutions and enable value differentiation for downstream analytics players?
• What should different stakeholder groups do to address the increasing adoption of AI and benefit from this emerging market trend?
• Which partnerships will enable these stakeholders to enhance and improve their AI/ML capabilities?