Digitization has been as revolutionary for industry as the introduction of electricity. Now artificial intelligence (AI) and big data are generating new opportunities – and a number of challenges.
In the “Artificial Intelligence in Europe” report published by consultancy firm EY, some 57 percent of the companies surveyed expect AI to have a significant or very significant impact on business areas that are “entirely unknown to the company today,” and 65 percent expect AI to have a significant or very significant impact on their core business.
Changing the game “The opportunities generated by digitization in general are game changers in most sectors, which is one reason why digital solutions have gained a strong foothold in different parts of society,” says researcher Daniel Langkilde, who develops AI solutions for Scania, Volvo and other major companies.
Digitization lays the foundation for entirely new business models, sometimes simultaneously throwing out the old models. A new model could be based on servitization, with revenues being secured directly by the performance of the products. This creates an incentive for suppliers to constantly optimize the outcome, which has also become easier through digitization, Langkilde explains.
Magnus Ekbäck, Vice President Strategy and Business Development at Sandvik Coromant, summarizes the main trends driving the digitization of the manufacturing industry: “More and more things are being equipped with sensors, giving us more data. At the same time the connectivity has improved fast and the demand for using data in the decision-making process has increased quickly. These three factors together are important in explaining the automation of the manufacturing industry that we see today; they are the enablers.”
“The term ‘Artificial Intelligence’ can be misleading, because computers that make calculations and analyses are actually nowhere near intelligent in the usual sense of the word,” notes Langkilde. “But they can learn to see connections by being fed large volumes of data, and the more data they receive, the better their analyses become.”
There may also be more strategic areas of use, such as detailed scenario planning or researching a large number of possible design variants of a new product.