2 min readSep 2, 2022


AI and space

AI is likely to deliver various advances in aerospace over the next 15 years by reducing costs, shortening the design process, duplication, experimentation, augmentation, support, production, and updating things. Advances in artificial intelligence can help aerospace companies improve their manufacturing processes. Let’s take a look at some of the applications where AI is changing the aerospace industry.

Product design. When combined with artificial intelligence, advanced design programming can help product designers learn multiple design options in a short amount of time. Designers can use this breakthrough to produce new lightweight and cost-effective products. For example, parts can be made using dynamic design with artificial intelligence combined with 3D printing. As a result, AI can help the aerospace industry optimize architecture and manufacturing processes.

Fuel efficiency. Fuel quality is important to the aerospace industry, and even a small reduction in fuel use can have a significant impact on a company’s sustainability. With artificial intelligence technology, we can reduce fuel use by 5–7%.

ESA’s planetary defense mission, Hera, will use AI as it guides itself through space to an asteroid, taking an approach similar to unmanned vehicles. While most deep-space missions have a definitive driver on Earth, Hera will combine data from different sensors to build a model of its environment and make board decisions, all autonomously.

Already on Mars, intelligent data transfer software aboard Mars rovers eliminates human planning errors that might otherwise lead to the loss of valuable data. This increases the amount of useful information coming from the red planet. Similar technology can be applied to long-term missions that will explore the solar system, which means they will require minimal supervision by human controllers on Earth.

And these are not all the possibilities of AI applications in space; the potential of this technology in this area simply cannot be overestimated.