Artifical Intelligence: Say goodbye to frustration and hello to success!

“Artificial intelligence?” – “Sure, I’ve heard of it” is a common reaction. But companies are often at a loss as to how they can profitably use AI technologies. Our scientists give businesses a helping hand in a consortium project that offers numerous advantages.

Artificial intelligence (AI) is a key factor determining the success of companies today. When you put your ear to the ground, however, you quickly discover that only a small minority knows what it really is – in place of factual knowledge, there are a lot of misconceptions doing the rounds. And things get even trickier when it comes to the concrete question of how to use artificial intelligence to solve a company’s individual issues in a targeted and effective manner. As a result, businesses often end up choosing unsuitable or overly complicated applications when looking to use AI – leading to frustration rather than the success they were seeking. In many cases, this leaves the potential of AI unexploited.

Getting from an airy buzzword to specialist knowledge, methodological expertise and concrete implementation

Scientists at Fraunhofer IIS’s Engineering of Adaptive Systems division EAS have embraced the goal of changing this unfortunate situation and allowing companies to tap the benefits of artificial intelligence by means of a consortium project that was launched on September 16, 2020 and was founded in conjunction with KEX Knowledge Exchange AG. “Through the consortium project, we want to pull artificial intelligence down out of the buzzword clouds and make it tangible and usable for our partners – after all, the employees in the companies rarely come from an AI background,” says Anne Loos, Head of Business Development at the Engineering of Adaptive Systems division EAS. The project has attracted a lot of interest in the industrial sector, with 20 companies signing up to participate, ranging from small businesses and SMEs to large corporations. There is also a lot of diversity in terms of different sectors.

The project comprises three phases. To begin, there is foundational training: “There’s a tendency to think of artificial intelligence as something you turn to when you reach the limits of your own capabilities,” Loos says. “But that’s actually way off the mark: AI can’t always solve problems for which we ourselves don’t yet have a solution. But it does help us speed up complex procedures and relationships – provided we’ve described them first.” That is to say, the true core of artificial intelligence is the training phase, during which expert knowledge is represented in the AI. Only when the system has been trained in this way can AI take a step beyond and learn things independently.

It is important to convey these and other fundamentals to the participants before getting down to the nuts and bolts. “We deliberately go into companies to align expectations with reality. What problems and tasks do you want to solve using artificial intelligence? What do the underlying processes look like? How mature is the company’s planned use case for AI?” summarizes Toni Drescher, CEO of KEX AG. After learning the basics, participants take part in a technology study, in which the project team starts out by identifying concrete solution options that suit the use cases they have elaborated together with the industrial partners. At the beginning of the third phase, the companies jointly select preferred use cases that are to be implemented as prototypes in the further course of the project. “As such, our consortium partners always hold the reins,” Drescher says.

When initial applications have been found, the researchers prepare them for the companies. For example, what “homework” still needs to be done? In regular meetings, the project team presents the various use cases in the consortium – in anonymized form of course. In this way, the participants gain a good overview of where AI can be used effectively, including in areas outside their own immediate sphere of concern. They can discuss the various applications and learn from each other and from the various use cases.

At the end of the project, the participants are presented with concrete roadmaps laying out how AI can be implemented in their company. They also bring home the requisite know-how: in a five-day intensive training course at the end of the project, the project team teaches them deeper knowledge about artificial intelligence, thus transferring technological knowledge into the companies.

And now to the question that companies will probably be most interested in: What advantages does participating in the consortium project offer them? Several answers spring immediately to Loos’s mind: “In the consortium project, which will be running until June 2021, the companies gain the opportunity to evaluate the use of AI for their use case from a commercial and technical perspective. Moreover, they obtain individual access to the latest knowledge, technologies and applications relating to AI – and all this for a relatively low price.” The companies can incorporate their very individual requirements into future AI research projects and so accelerate their own AI process development. They gain access to a network of AI experts along with ideal opportunities to expand the AI expertise of their employees. In short, they learn to leverage the advantages of artificial intelligence in a highly targeted manner for their company.