Scania is now joining AI Sweden’s network of over 100 partners in industry, the public sector and academia, with the hope of cross-sector collaboration. AI plays a key role in the future of the automotive industry - not least in the development of autonomous vehicles and in data-driven maintenance planning. With its size, global reach and data driven ambitions, Scania will be an important partner to AI Sweden and its current partners.
“Working to spread insights, build and share experiences together in groups such as AI Sweden is valuable and stimulating for Scania and our employees,” says Mikael Cato, Chief Digital Officer at Scania.
With 50,000 employees in over 100 countries worldwide, Scania is a leading provider of transport solutions, including heavy transport such as trucks and buses. The automotive industry and Scania sees a great need for AI in developing autonomous vehicles and for data-driven maintenance planning.
Ulrik Janusson, Technology Leader for Connectivity at Scania highlights Edge Lab and Data Factory as two specific possibilities that Scania wants to engage with.
“We at Scania are excited to join AI Sweden and we see lots of possibilities. Initially we are particularly interested in taking a closer look at the EdgeLab in the Data Factory”.
Daniel Gillblad, Co-Director for Scientific Vision at AI Sweden, welcomes Scania in joining AI Sweden and underlines the importance of cross-sectoral collaboration in order to accelerate the use of AI and strengthen Sweden’s competitiveness.
“As many organisations share the same challenges, collaboration around AI platforms, operations of AI systems, and processes for building data-driven systems should be encouraged,” says Gillblad. “We know Scania as a visionary and resourceful player in the automotive industry, a sector in the forefront of data collection, which can be useful also in other sectors. For example, our partner, the Swedish University of Agricultural Sciences, was inspired by the AI technology behind how autonomous vehicles monitor their surroundings, and have applied it to analyze seabird behavior in the Baltic Sea.”