Predictive Maintenance in Software Systems Using AI
Date: 13/11/24
By: Krzysztof Lewczuk
The internet of things is coming to street near you – where your home will do the dishes and wash clothes for you at night to take advantage of lower market prices; where at power plants, self-regulating, repairing, and optimising turbines will utilise artificial intelligence (AI) to enhance performance, reduce wear and tear and lower emissions; and where smart grids will be able to control supply and demand by monitoring power consumed in real time.
The utility sector has a lot to look forward to in this new AI world. So it’s all the more surprising that according to a recent Roland Berger report, only 23% of utilities executives answered that they had a defined strategy for incorporating AI in their companies. And as many as 40% replied that they had no strategic targets or strategy defined. There’s a strong disconnect between high executive appreciation of AI’s importance and pro-active planning for its implementation. So why is AI so special for utilities? And what’s holding so many back from AI?
While improvements can be made to firms’ operations with off-the-shelf and non-customised AI technology, the sector should look to the first mover success of AI implementation in FinTech and other sectors. The report also argues that ‘establishing a competitive edge in more specialist areas of utilities’ business will require internal solutions, however, meaning longer development times.’ Roland Berger suggests that firms move quickly on implementing more innovative AI strategies in order gain an advantage over their industry rivals.
The survey also reveals that the potential of harvestable data is not being taken advantage of by industry players. 73% responded that data was either not collected or unknown and only 17% rated their firm’s data quality and availability as ‘good.’ The industry seems to have a lack of concern over harvestable data – a key driver of AI. To fully utilise the technology, firms need to collect, understand, and use the vast amounts of data they generate. And UK utility companies need to act soon as the AI future becomes clearer and because data harvesting requirements need to be identified early in the strategic process.
It’s clearly time to stop being a utilities laggard and become a leader!
Date: 13/11/24
By: Krzysztof Lewczuk
Date: 05/11/24
By: Krzysztof Lewczuk
Date: 30/10/24
By: Krzysztof Lewczuk
Date: 24/10/24
By: Krzysztof Lewczuk
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