AI in SMEs: Roadmaps and practical examples for getting started
Artificial intelligence (AI) is a key technology for the future competitiveness of companies of all sizes. It offers an effective tool to improve operational processes and existing products or to develop new business models. However, German SMEs have hardly used the opportunities offered by AI so far. They often lack well-prepared data, know-how and investment scope. In a current publication, Plattform Lernende Systeme shows the potential of AI using successful practical examples from SMEs and provides companies with concrete implementation plans for the introduction of intelligent systems.
Whether it's a car repair shop, a shelf manufacturer or a delicatessen: it's not only large corporations that can set up their business for the future with AI systems. The opportunities for SMEs include efficiency gains, advantages over competitors and increases in profits and earnings. According to current studies, however, only six percent of all small and medium-sized enterprises (SMEs) are currently using AI technologies consistently. The majority of companies (40 per cent) are not currently planning to use AI systems. According to the paper "AI in SMEs", SMEs in particular, with their short decision-making processes and manageable size, have good prerequisites for quickly introducing technical innovations such as Artificial Intelligence.
However, SMEs also face many challenges when introducing AI systems - especially when digitisation is still in its infancy in their company. They often lack the know-how, do not have sufficient good data and shy away from high investments. Technical competencies, existing infrastructure and the strategic orientation of the company determine how well a business is prepared for the use of the technology. Together with small and medium-sized enterprises, the authors of the paper have evaluated various implementation strategies. The paper outlines four ideal-typical AI roadmaps for the gradual introduction of AI that take into account the different prerequisites in the companies.
"In many cases, untapped potential lies dormant in the data of SMEs, which could be raised with AI. But Artificial Intelligence is not an end in itself. Not every problem can or should be solved with AI methods," says Ralf Klinkenberg, founder of RapidMiner and member of the steering committee of Plattform Lernende Systeme. "That's why companies should clearly work out at the beginning of their first AI project what they want to achieve with AI and in which areas the use of intelligent systems is worthwhile."
The authors recommend focusing on business areas such as purchasing or production, in which no personal data is processed, for a start. This is because own AI products or services for customers require a high level of data protection and security and can overwhelm AI beginners. The authors name intelligent sensor technology and AI-based assistance systems as the most promising AI applications for initial projects.
A major hurdle is often the required AI expertise. Companies do not have to build up the necessary know-how themselves, but can obtain the required knowledge from outside. In addition to external advice, cooperation with research institutions or universities is also possible. The paper presents various funding programmes and contact points for SMEs.
If the necessary technical infrastructure such as computer capacities or investment scope for the development of one's own AI systems is lacking, customised solutions can be purchased as so-called AI-as-a-service offers. In the manufacturing industry, for example, companies can make use of the AI services of machine manufacturers, for example for the intelligent maintenance of plants. It should be noted, however, that only proprietary solutions will bring a competitive advantage in the long term.
The challenges often affect several players in the industry. Thus, one company alone rarely has the necessary data for innovative AI applications or business models. The authors advise working together with competitors or suppliers in AI ecosystems. In this way, data, know-how and infrastructure can be shared and risks shared.
About the publication
The practical brochure (in German) Artificial Intelligence in SMEs. Recognise potentials, create prerequisites, master transformation was created on the basis of expert interviews with cooperation partners from research institutions and companies and supported in an advisory capacity by members of Plattform Lernende Systeme.
SMEs can find more information on the introduction of Artificial Intelligence in companies, initial contact points and further case studies in the web special of Plattform Lernende Systeme.
Linda Treugut / Birgit Obermeier
Press and Public Relations
Lernende Systeme – Germany's Platform for Artificial Intelligence
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