Government and industry experts are sounding the alarm: the space industry must significantly accelerate its adoption of artificial intelligence or risk falling behind. This urgent call came during a recent symposium hosted by the Universities Space Research Association and George Washington University’s Space Policy Institute. Participants from the space and AI sectors strongly advocated for broader AI utilization in both spacecraft and the processing of space-based data.
While space missions have incorporated AI for decades, early implementations were relatively basic. Today's advanced large language models and machine learning systems provide far more sophisticated capabilities. Steve Chien, a senior research scientist at the Jet Propulsion Laboratory, pointed to software enabling space telescopes to autonomously skip or replan observations as an illustration. "Twenty years ago, you would absolutely call that AI," he stated. "Now, you would say, maybe not."
Chien joined others in urging companies and government agencies to embrace AI more fully in space systems. "The aerospace sector has not been as fast as it needs to be," he emphasized. "We need to change." This reluctance is increasingly unusual. Rupak Biswas, director of exploration technology at NASA’s Ames Research Center, noted, "Everyone is doing AI. If you say that you’re not doing AI, people think you’re very strange."
Biswas highlighted AI's crucial role in analyzing massive datasets and uncovering insights beyond human capabilities. Bryan Dorland, principal director for space technology at the Office of the Assistant Secretary of Defense for Critical Technologies, similarly emphasized the importance of AI for future defense programs. These include enhancing space domain awareness, providing mission autonomy in cislunar space, and supporting the proposed Golden Dome missile defense system. "It’s gotten beyond the point where humans can be in the loop in processing information," he observed.
Leading AI developers are also encouraging greater space industry adoption. John Platt, a Google fellow, described how Google is leveraging its AI technologies at the intersection of space and climate, such as analyzing building imagery to optimize solar panel placement and using AI to analyze data from FireSat, a wildfire detection constellation. Similarly, Meta is promoting its Llama open-source AI models for space applications.
Laura McGorman, director of Meta’s “Data for Good” initiative, cited an MIT project using Llama for spacecraft AI navigation and another application processing Earth observation data to count global tree populations. While acknowledging a lack of targeted outreach to the space industry, McGorman identified a significant hurdle: "You have this huge awareness problem… and I think that’s probably the biggest barrier right now," she said. "Expanding that level of awareness… is, I think at times, a tall order."
Chien observed that established space companies are less inclined to adopt AI than startups, which are more experimental. "They’re running ahead with AI," he noted. "AI is now a branding." Platt urged university researchers to embrace experimentation: "I don’t want you to be alarmed. I want you to be excited. No one really knows what we can do for any particular application. It’s so new," he said. "It’s just open. No one knows what they’re doing, and that’s great."