Our Artificial Intelligence heritage

How our heritage in artificial intelligence has created a platform for its sustainable technology future.

We have more than 30 years of experience in using advanced analytics to gain insights that allow us to break through technological barriers and bring new value to our customers.

Our use of data analysis techniques in the early 1980s helped us make sense of measurements taken on engine test beds and signified the start of a new data-driven journey.

Our use of artificial intelligence started in earnest in 1999 in a new and disruptive service to the jet engine marketplace, called engine health monitoring, which formed the core what became our TotalCare package.

This involved gathering data from jet engines after planes landed, allowing us to predict maintenance and accurately schedule engine care so our customers’ gained more value from their engines and for Rolls-Royce it became a multi-billion pound component of our business.

Away from flying, we are now at the cutting edge of industrial AI, using robots to perform quality checks on critical components in our manufacturing centres.

We have used our ethics process to ensure that this was the right thing for our business to do, and we apply our trustworthiness process to ensure that the decisions made by the AI are all trustworthy.

Since 2017 this work has been led by the federated data innovation catalyst, R2 Data Labs, which is positioned across our business to use data to improve performance, create customer value, and crucially, to build a powerful digital culture that is transforming how power is created, managed and delivered in a low carbon world.

And this is our future. We will deploy AI, within the bounds of our ethics framework, across our business to ensure we work smarter and use our people for high value tasks. We are continuing our data journey to examine how we can improve the performance of our products, be it compact nuclear power stations, train engines, microgrids, or back up power systems for data centres, making data itself more a low carbon tool.

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