Six major Spanish and Spanish-based companies have just launched IndesIA: a national strategic consortium. This project has been established to promote the use of data and AI in Spanish industrial companies with the support of pioneering organisations in the field such as the Basque Artificial Intelligence Centre (BAIC). Around 100 small and medium-sized enterprises (SMEs) are already interested in joining IndesIA with the aim of accelerating their digitisation processes, productivity and sustainability in the sector.
IndesIA: a consortium launched by six groups to promote artificial intelligence and data
Telefónica, Repsol, Microsoft, Navantia, Técnicas Reunidas and Gestamp are the six founding members of IndesIA: a consortium for the data economy and artificial intelligence in the industrial sector in Spain that has a European vocation and a desire to integrate other companies and sectors.
IndesIA aims to be a driving project, born with the purpose of positioning Spain as a reference in the use of data and artificial intelligence in the industrial field and to promote the development of a new economy generating economic growth in the country.
This consortium has the support and experience of organisations specialising in artificial intelligence, such as the BAIC, and will also work to try to boost employability, reducing the training gap that exists in science, technology, engineering and mathematics.
The consortium’s focus is on several areas of work
In order to achieve its objectives, the tractor project is structured around the following axes:
- Create acceleration mechanisms that will streamline the process of developing solutions based on megadata and artificial intelligence, facilitating access to the technical and financial resources needed to implement them.
- Generate an ecosystem of start-ups, technology centers and universities specialized in the research and development of artificial intelligence solutions applied to the industrial field that will allow the sharing and application of the most effective knowledge and solutions.
- Promote the creation of a large interoperable industrial data platform that favours the development and consumption of artificial intelligence solutions.
- Conclude agreements to facilitate access to cutting-edge technologies (IoT, 5G, cloud, supercomputing, quantum, edge computing…) that will enable case development.
- Create a school of data and artificial intelligence to be able to involve and train professionals from the industrial sector in the use and analysis of data through appropriate training routes, which also focus on promoting diversity, gender equality and commitment to scientific profiles.
About sixty use cases, the creation of a library of industrial cases and an adapted ecosystem
IndesIA has already identified some sixty use cases based on artificial intelligence that will help drive the value chains of five industrial sectors: engineering, naval, telecommunications, energy and automotive. All the processes in the industrial domain aim to be improved thanks to data and artificial intelligence.
The consortium envisages the generation of a library of transversal and functional industrial cases, duly documented and with access to the data that allowed them to be solved, which will reduce the barriers to entry of artificial intelligence for companies and for more than the hundred SMEs that are already joining the consortium.
To develop these use cases, an ecosystem of companies, start-ups, technology centres and universities specialising in the application of artificial intelligence in the industrial field should be set up soon. This collaborative network will enable the rapid dissemination of the most effective knowledge and practices, as well as their adaptation to the specific needs of each sector.
Several training paths will be defined to cover both the generalized knowledge that employees in the industrial sector need to acquire to better understand how these solutions can help them in their daily lives, as well as specialize in order to retrain new profiles such as data scientists and data engineers internally.