An ever-increasing digitalization of industrial activities, ever more voluminous data generated, a potential of business value still under the radar of most decision-makers, …
Nothing new about AI, you’d think.
Well, think again!
Upon closer look, major projects have been undertaken by many industrial groups, which were previously perceived as lagging behind other sectors, such as retail or financial services. Thanks to the hard work of many, the fundamentals of digitalization and data governance are now much better understood. Everyone is taking action and gradually transforming their business with data and AI. This has been confirmed by our recent study, based on a series of thirty interviews with data & AI experts in industry.
Unsurprisingly, manufacturers have started off taking the Data & AI topic from the side of operational excellence, making it a lever for competitiveness. Nevertheless, their recent investments are directed towards two new subjects. The first one is the environmental footprint: use cases are being developed for biodiversity and carbon neutrality purposes. The second is knowledge and adaptation to the market. This is certainly a no-brainer in other sectors, but it tends to be more difficult to implement in industrial groups, often stuck with a B2B mindset.
Emerton Data is a specialist in data and AI for the industry sector, with a mission to support its clients in the transformation of their business, by helping them define their data & AI strategy, equipping them with custom AI solutions and incubating AI SaaS software.
This white paper is being published alongside the AI for Industry 2022 event. It will explore the major Data & AI use cases of the moment, before diving into the Data & AI Factory model.
These elements will then be illustrated in depth through a succession of interviews and opinion pieces from the current leaders in data and AI for industry.
If deep learning will definitely play a crucial role in automation and improvement of the daily insurer operations involving image, text, and audio processing, it is not expected in the mid-term to deeply impact the core insurer business related to risk management.
The aim of this short paper is to share a point of view on the use of deep learning technologies in the insurance sector.