The time is now to set the path for AI-competent workforces
In tax consultancy firms, artificial intelligence (AI) is used to automate routine tasks such as bookkeeping and document processing. Some painting firms are using robots for standardised tasks, such as priming large surfaces. In other trades, digital assistance systems support management with route planning, telephone support and workflow management. Artificial intelligence has arrived in small and medium-sized enterprises (SMEs). This is also confirmed by the statistics: In 2025, around one in four SMEs in Germany used AI processes. This was not only more companies than the EU average (19%), but also significantly more than in 2024 (19%).
AI primarily used for support
"Currently, the use of AI in small and medium-sized enterprises primarily serves to relieve employees of time- and resource-intensive tasks. Some management teams also use AI specifically to boost their appeal as employers and attract young talent," reports Dr Jonas Löher, who has investigated the impact of artificial intelligence on the skills shortage together with other researchers at IfM Bonn. The findings showed that reducing the burden on employees can currently help alleviate recruitment difficulties. As artificial intelligence increasingly changes job profiles in general, the demand for suitably qualified staff will rise in the future. Consequently, vocational training, degree programmes and further education courses must be adapted promptly to the new staffing challenges. Otherwise, small and medium-sized enterprises in particular face the risk of competitive disadvantages due to recruitment problems.
Barriers to AI adoption
But even though ever-increasing competitive pressure is forcing smaller companies to engage more intensively with artificial intelligence, its adoption still depends primarily on the digital competence and affinity of the business owner. In many management teams, there is uncertainty regarding which applications are suitable and useful for the company, given the multitude of available solutions. Research by the study team also identifies inadequate data infrastructures, poor data quality and unclear data protection requirements as barriers to AI adoption. "Fundamentally, it is up to companies to capitalise on the numerous opportunities offered by AI. There are already numerous public and private support schemes available for this purpose, such as the BMWE’s ‘Mittelstand-Digital’ funding programme or the funding of AI projects under the ZIM initiative," reports Dr Löher. “In order to allay SMEs’ concerns regarding data security, the necessary conditions should now be created in Europe to enable companies to use AI applications securely and autonomously.”
