So Millie, could you give me specific examples of how AI impacts these utility workers and end users?

Yes, I can definitely give you a few examples where AI is relevant, depending upon where you are in the entire energy value chain.

Let's take an example of an asset manager who's responsible for the overall operation and maintenance of a substation, which includes anywhere from your transformer, your switch gears, circuit breakers, right? So with the AI-powered predictive tools, the asset manager can get an early warning sign of a potential failure to an equipment that reduces a disruption, any downtime that is not anticipated, and the impact to the overall users is you have the lights on all the time.

Another good example may be as you are driving home on your freeway, you look to the right and left, you'll see high voltage transmission towers.

Traditionally, it's a huge production where the trained engineers go with the truck roll.

They climb up the transmission tower and manually probe to see what are risks to failure conditions.

Now take that with the scenario where drones are being flown around the transmission towers, and these drones are capturing images from different angles, and these images are being processed through pre-trained machine learning models, which gives you, again, the risk to failure conditions.

Have you got a couple of real world AI case studies in your portfolio and any lessons learned that you could share?