“Artificial intelligence is changing the world of work. Innovative companies are showing how this transformation can be successful.
In many industries, artificial intelligence (AI) is considered a driving force of the future. Nevertheless, current studies show that only two to six percent of companies in German-speaking countries and the US are currently using AI comprehensively. Catching up requires more than just technical understanding. A look behind the scenes at leading companies worldwide reveals how AI technologies can be strategically integrated.
The key lies in the interplay of organizational capabilities, technological infrastructure, and corporate governance. Companies that focus on this strategic integration of AI are demonstrably more innovative.
Interviews with nearly 50 AI managers from leading companies across 17 industries, from automotive to pharmaceuticals, offer a glimpse into the AI transformation. All these companies have one thing in common: they understand AI not as an isolated technical phenomenon, but as something that requires adapting strategies, structures, and processes. Specifically, they are investing in organizational capabilities, technological infrastructure, and governance structures.
Overall, the results published in the "Journal of Product Innovation Management" show that companies understand AI not only as a technical issue, but above all as a management issue.
A central lever is the development of skills. This involves not only hiring technically skilled computer scientists, but also providing further training for the entire workforce. For example, BASF is establishing an AI academy, and Microsoft, together with other companies, has launched a training initiative, as research shows. In terms of content, most of these programs focus less on technical skills and more on so-called meta-competencies. According to current research, these competencies enable employees to assess the potential and limitations of AI technologies in their specific tasks. They also learn to better evaluate their own judgment when using AI.
In practice, companies are promoting these competencies in addition to training programs that are complemented by networks and AI initiatives. The goal is to exchange ideas, reflect, and learn from one other. Mercedes-Benz, for example, maintains an internal AI network with approximately 3,500 members, and Allianz hosts digital presentations featuring AI experts. In so-called "promptathons," employees at Telekom, Deutsche Bahn, and the state bank Nord-LB learn how to solve innovation challenges using large language models such as ChatGPT, Claude, and others. Internal AI conferences, such as those at Sartorius and Bosch, also contribute to greater visibility and stronger networking.
This networking concept is also reflected in newly emerging roles. According to the interviews, the role of the so-called AI Business Translator is particularly relevant. This is an interface function between the technical expert teams and the business departments. As bridge builders, AI Business Translators translate between programming code and business logic, thus ensuring that AI applications solve concrete business problems.
For AI applications to be technically sound and accurately developed, a technological infrastructure with corresponding development teams is necessary. Their work is based on data, the foundation of every AI application. This data must be available in sufficient quantity and quality to conduct meaningful analyses and, if necessary, train proprietary AI applications. Data silos, where individual departments claim ownership of data sets, hinder this process. Leading companies are therefore deliberately breaking down these silos by, for example, building knowledge transfer platforms. On these platforms, information such as programming code is shared across departments, and use cases and contact persons are made visible. This enables the business departments to leverage synergies and simultaneously provides a showcase for flagship projects.
Successful companies also rely on clear control mechanisms and responsibilities. The management board plays a key role in this, as it can initiate and drive the focus on AI. In her speech at the 2025 Annual General Meeting, for example, Merck CEO Belén Garijo highlighted AI as a key focus of the pharmaceutical company. BASF Chairman Dr. Markus Kamieth even called AI "absolutely groundbreaking" at this year's annual general meeting. Studies also show that companies with a Chief Information Officer (CIO) are more likely to have a strategic focus on AI, and those with a tech-savvy CEO are better able to translate the potential of AI into innovation successes. This support from top management works in two ways, as the following illustrates: Interviews clarify several points. Firstly, they legitimize internal activities surrounding AI. This promotes openness towards the technologies and creates opportunities for experimentation.
Secondly, support from the executive board facilitates the provision of personnel and financial resources.
Numerous corporations, including KPMG, Pfizer, and Boeing, are appointing a Chief AI Officer as a management position for AI and establishing AI departments. These central points of contact bundle expertise and strategic directions, oversee use cases and investments, and track trends and regulations such as the EU AI Act. To prevent AI departments from becoming bottlenecks, companies are relying on multipliers. AI-interested employees share their knowledge within their respective departments and act as a link to the AI department. In the summer of 2025, the Otto Group, for example, launched a program to train AI ambassadors who share their experiences with AI in their respective departments and thus encourage the use of AI.
According to the interviews, AI strategies and ethical guidelines are increasingly serving as guardrails for the AI transformation. Covestro and Volkswagen demonstrate that such strategies are more than just theoretical projects. The chemical company Covestro has integrated AI into its business strategy with a focus on innovation potential, thus ensuring strategic coherence. Volkswagen highlights the importance of its AI strategy in its 2024 annual report and simultaneously emphasizes that AI is not an end in itself. In addition to AI strategies, companies are increasingly formulating ethical guidelines. These guidelines focus on transparency, accountability, traceability, and the protection of personal data – principles that Mercedes-Benz and Fiege, for example, have enshrined in their AI principles.
It is clear: AI is more than just technology. It's about skills, structures, and leadership, and therefore about people.
Ann-Katrin Eicke is an assistant professor at Ludwig Maximilian University of Munich and received the Schmalenbach Prize 2025 for her doctoral thesis in business administration on artificial intelligence in companies." [1]
1. Es geht bei KI um mehr als Technik. Frankfurter Allgemeine Zeitung; Frankfurt. 24 Nov 2025: 16. Von Ann-Katrin Eicke
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