The use of AI in companies requires a certain level of digital maturity. This includes structured processes or a functioning digital data management system.

Many, especially smaller companies, face limitations here: While expertise, time or financial resources are limited, extensive documentation and verification obligations in the B2B sector or duplicated efforts due to insufficiently harmonized laws tie up important resources that are lacking in digital transformation and the introduction of AI applications.

What the German Chamber of Commerce and Industry (DIHK) considers important now:

• Reducing and simplifying operational documentation, information, and verification obligations to a necessary minimum, especially where the same data must be transmitted multiple times
   
• needs-based offers, through which the federal and state governments support investments in IT infrastructure and qualification – particularly for small and medium-sized enterprises
   
• better coordination of existing funding and support offers from the European Union, federal and state governments to avoid overlaps, organize knowledge transfer more efficiently and use resources sustainably

A growing number of regulations affects companies and new AI technologies.

Data as the Basis for AI: Access to relevant data is often limited due to legal uncertainty and bureaucratic hurdles. Small businesses often lack strategic data expertise.

Germany is renowned for its research in artificial intelligence. However, there is still room for improvement when it comes to spin-offs, scaling, and market introduction of innovative AI solutions. Often, there is a lack of venture capital, tailored financing instruments, and realistic test environments.

Living labs and AI sandboxes can support the testing of new applications under real-world conditions and resolve regulatory questions early on. Access to powerful data center infrastructure is frequently a key factor.

Key points from the perspective of the German Chamber of Commerce and Industry:

• An increase in support for AI start-ups and spin-offs, alongside enhancing the focus of universities and research institutions on transferring knowledge in the field of AI
   
• Strengthening interoperability aspects, such as through support for standardized interfaces (APIs)
   
• Improved access to venture capital through public co-investments, tax incentives, and the expansion of early-stage financing
   
• Low-barrier access to living labs, providing opportunities to utilize high-performance computing capacities and cloud resources for training AI with diverse, high-quality datasets

With the growing use of AI and cloud applications, the demand for computing capacities, fiber optic networks, and powerful mobile networks is increasing. High electricity prices can raise the cost of data center capacities and thus become a stumbling block for innovation and AI use. Lengthy approval procedures for network expansion delay investments and hinder the development of data centers.

What is important from the perspective of the German Chamber of Commerce and Industry (DIHK):

• A significant shortening of the planning and approval procedures for an accelerated expansion of digital infrastructures
  
• Framework conditions that enable competitive electricity prices and support investments in efficient, high-performance data centers
  
• The use and promotion of technological advancements in AI and its applications. Energy-efficient technologies and the use of waste heat from data centers should be specifically supported

Artificial intelligence (AI) is reshaping various professions and workflows. To introduce and utilize new applications responsibly, companies need skilled professionals with technical expertise and a comprehensive understanding of digital processes.

As AI adoption increases, so do risks such as manipulated training data, deepfakes, automated cyberattacks, or malfunctions causing significant harm. However, AI can also enhance security, such as anomaly detection in technical systems.

The speed of administrative digitalisation has a direct impact on the economic location. Digital, AI-supported processes can accelerate approvals, ease staffing burdens, and simplify procedures.

The public sector can act as a demand driver for artificial intelligence, stimulating an AI ecosystem. This requires procurement processes that do not structurally disadvantage start-ups and small and medium-sized enterprises.

What the DIHK considers essential now:

• the targeted use of artificial intelligence to deliberately accelerate and simplify processes within the scope of administrative digitalisation
   
• a reformed procurement law that facilitates easier access for start-ups and small and medium-sized enterprises to public contracts
   
• strengthening open-source software as a strategic driver of innovation