Large companies competing in international markets face constant pressure to improve efficiency, modernize and seek new business opportunities. This pressure is also reflected in subcontracting chains, which drives the entire industry forward. Digitalization, automation and optimization are the keywords of development, and artificial intelligence offers effective tools to achieve these goals.
“Artificial intelligence can help, for example, with predictive maintenance, optimizing energy consumption, improving quality control, and developing new products and materials,” says the industrial professor at LUT School of Business. Mika Ruokonen.
The forest industry is an excellent example of an industry where the potential for artificial intelligence is enormous. Valuable data is constantly being generated not only in production processes but also in the forest. For example, forest machines that harvest timber collect real-time information about their own operations and the efficiency and results of harvesting. With the help of artificial intelligence, this massive raw data can be transformed into clear and useful information.
Harnessing the power of data streams into everyday life
Although artificial intelligence offers great potential, its large-scale use in industry is hampered by the physical production environment and tangible products. Unlike, for example, media, banking or the platform economy, industry does not only process data, but also tangible materials.
Digital industries are used to dealing with mostly structured data, such as text and numbers. In industry, data streams are more diverse, originating from many sources: sensors, production machines, and visual inspections. This data can be inconsistent, inaccurate, and even erroneous.
Developing artificial intelligence for industrial needs requires much more than just processing large amounts of data. It requires creating complex models that solve problems in the physical world. These models are significantly more demanding than traditional algorithms designed to analyze only digital data.
Expertise and cooperation as keys to development
One of the barriers to wider adoption of AI in industry is the skills gap. New skills are needed, and they must be acquired through recruitment and training. While external consultants can help, their know-how is no substitute for the basic internal understanding that is critical to day-to-day operations.
"For example, data analytics literacy and related problem solving will also be needed in industrial tasks in the future. The skills gap therefore does not only affect white-collar workers, but the entire personnel," says Ruokonen.
The current economic downturn is imposing its own limitations and slowing down large-scale investments in AI. Ruokonen encourages agile experiments that offer the opportunity to understand the benefits of AI without major financial risks. It is also a good idea to increase cooperation with universities.
"LUT University's location near the forest industry centers of Lappeenranta and Imatra enables active cooperation and joint research and development projects, as well as bringing the message of the forest industry into teaching," says Ruokonen.
Ethics first, but we need to invest in financing
Europe has joined the AI race from a clear distance behind. While the United States and China emphasize the speed of progress and business benefits, Europe has decided to focus on the transparency, reliability and ethical aspects of AI. Ruokonen believes that these value choices can serve as strengths up to a certain point.
"The path chosen by Europe in the development of artificial intelligence is in itself a positive thing. At the same time, it must be understood that development related to artificial intelligence should not be regulated blindly. Sufficient resources, and in particular the EU's €200 billion
The concretization of the InvestAI initiative's funding streams are crucial factors for the development of European artificial intelligence and ensuring its scalability," emphasizes Ruokonen.
In his discussions with industry leaders, Ruokonen has observed that companies are preparing for the changing operating environment brought about by artificial intelligence. However, companies are aware that change will not happen overnight.
"In this situation, industry must have the ability to learn new things and tolerate uncertainty. Creativity, leadership skills, and a deep understanding of optimization and automation are key factors for future success," sums up Ruokonen.
