Exploring and Shaping the Use of AI in the Working World Together

The change that artificial intelligence is bringing to our working world is multidimensional. The technology changes the tasks we face, work results and the way we work together.Since the emergence of generative AI such as ChatGPT in 2022, this development has gained even more momentum. Generative AI can process information, create creative content, and support decision-making across a wide range of use cases.

There is no doubt that the transformation driven by AI can—and must—be shaped. This requires a deep understanding of the changes that come with it, as well as measurement models that help companies capture the complex effects of using generative AI. The goal is to make the impacts measurable and transferable, and to make insights accessible to the stakeholders involved. This is where the research project ai:conomics comes in: since 2021, it has been examining the effects of AI on the world of work—always with the aim of providing decision-makers in business, politics, and society with a scientific basis for AI adoption decisions that can benefit companies, employees, and the common good.

With this goal in mind, a central concern of the research project is to respond—within a rapidly transforming environment—to key developments, challenges, and questions that are relevant in practice. Given the rapid spread of generative AI since 2022, ai:conomics further sharpened its focus in 2025: since then, it has concentrated on the concrete impacts of generative AI on companies and employees in Germany, as well as on developing a tool that makes these effects measurable and transferable across different business contexts.

By combining scientific field experiments with a co-creative process design, ai:conomic expanded the basic knowledge on how AI changes our working world and affects employees. Doing so, it built a new scientific foundation for shaping the future of work and the use of AI in this specific context with a positive social impact. 

To this end, these and other research questions were investigated:

How does generative AI affect efficiency in companies?

How does the use of generative AI—whether to augment or replace expertise—affect efficiency and quality in task completion?

Does AI support lead to greater trust in, or rather skepticism toward, AI-driven work and one’s own professional value?

How does the use of generative AI affect stress levels, autonomy, and motivation at work?

What new skills emerge in AI-supported roles?

Explore the answers to these questions and other valuable insights in our Policy Briefs, scientific posters, and the ai:conomics podcast (only available in German).