Artificial intelligence is considered a key technology of the 21st century with enormous potential for productivity growth and economic growth. The German government has recognized the importance of AI, presented an AI strategy for Germany in 2018 and updated it in 2020 with the aim of “strengthening Germany as a location for research, development and application of AI in international competition.” Among other things, it has provided funding totaling five billion euros by 2025 in a “Future Package” for AI research, transfer to industry, especially also in SMEs, as well as training and qualification. So all is well?

How does it look in reality?

According to current studies and surveys, after several years of rapid growth, the development of AI and its use in companies is stagnating. The Bitkom IT association’s summer 2022 study on the status of AI in companies shows that while the majority of companies surveyed see the opportunities AI offers, only nine percent actually use it. Most companies state that they have some catching up to do when it comes to AI in-house. In an international comparison, Germany has fallen one place behind the U.S., China and Japan compared to 2021 in the view of the respondents, and very few think that Germany could be a leader in AI in the coming years. In its KI Monitor 2022, prepared for the German Digital Economy Association (BVDW), the Institute of the German Economy (IW) notes a declining value for the first time in the AI Index, which has been calculated annually since 2019. For this purpose, the IW evaluates studies, parliamentary minutes, job advertisements, annual reports, print and digital media, and patent applications. The IW sees the decline as being due in particular to deficits in the “framework conditions” category, with indicators such as “digital infrastructure,” “AI in Bundestag minutes,” “computer science graduates,” “scientific AI publications” and “collaborations between companies and research institutions.”

What is causing the stagnation?

Given the current crises with an uncertain economic outlook, corporate reluctance to invest is understandable. However, AI is a key technology whose potential is crucial not only for optimizing and streamlining workflows and processes, but also for transforming and reorienting business models. What is preventing companies from pushing ahead with AI now is probably due to a whole bundle of causes. A few are singled out here.

• Qualified employees

In the Bitkom survey, a lack of human resources is the number one obstacle to the use of AI in companies. However, according to the KI Monitor, companies have invested less than before in the qualification of their employees, contrary to the recommendations of various bodies to build up AI expertise in-house, especially since funding opportunities are available from the Future Package.

• Legal barriers

Just under half of the respondents (49 percent) in the Bitkom study see “uncertainty due to legal hurdles” as one of the biggest obstacles to using AI, ranking fourth after a lack of human (first place) and financial (third place) resources and a lack of data (second place). The survey does not specify what falls under legal hurdles. It is conceivable that it is the planned EU AI Act, which is intended to ensure the protection of the fundamental rights of citizens in connection with the use of AI. However, the legislative process has not yet been completed, so uncertainty about its content is likely to contribute to caution about AI use. “Violations of data protection regulations” were cited by 61 percent of those surveyed in the Bitkom study as a risk in the use of AI, second only to possible new IT security risks. Since such violations can cost companies dearly, it is conceivable that they will hold back on AI use to reduce or avoid the risks.

Conclusion

Overcoming the stagnation in the development and deployment of AI is crucial for future economic development in Germany. Assistance with legal and ethical assessment is among the most important measures that could advance AI in companies, according to the Bitkom survey. The authors of the AI Monitor recommend that policymakers “take care to create legal certainty and avoid regulatory fragmentation in the regulatory projects undertaken both nationally and internationally.” With regard to the no less important material resources for rapid AI deployment, complaints about a lack of resources on the one hand and filled funding pots on the other could be an indication that assistance for taking advantage of funding could help reverse the trend.