From the workplace, for the workplace: researching the use of generative AI in the world of work and making its effects measurable—for everyone.

ai:conomics is Lifting the state of Research about AI in the Working World to the next Level.

Since 2025, ai:conomics has focused on studying the impact of generative artificial intelligence (GenAI) on companies and employees. The overarching goal remains the same: to better understand the future of work and help enable involved stakeholders to actively shape it.

In terms of both content and methodology, the project builds on the controlled field studies previously conducted on non-generative AI methods. In addition, a measurement tool is being developed to make the approach transferable and applicable across a wide range of business contexts.

Dual focus: the effects of GenAI on efficiency in business operations and employees

ai:conomics takes a holistic, dual-track approach by examining how GenAI impacts the efficiency of business processes while also influencing employees’ work experience. Through co-creative collaboration with its industry partner, the project measures the impacts of GenAI where they actually occur: in day-to-day business practice. This applied approach is called “Insider Econometrics.” It is based on analyzing company and scientifically collected data from before, during, and after the implementation of AI within the organization—so that the insights gained can also be transferred to other jobs and industries.

Making effects measurable—beyond a single use case

To capture how GenAI is changing work processes, efficiency, and work outputs, ai:conomics uses a systematic four-step methodology.
First, existing use cases are examined closely to understand how GenAI is used in business practice.
Next, GenAI-related changes are analyzed in detail.
Then, the effects of these changes are measured.
Finally, it is assessed to what extent the findings can be generalized.
As part of this, a measurement tool is being developed that can be transferred across different business contexts.

Key research questions

Business efficiency:  

• How does GenAI affect efficiency in companies?
• How can a standardized measurement tool be developed that makes it possible to assess efficiency across different business contexts?
• How does the use of GenAI—whether to augment or replace expertise—affect efficiency and quality in task completion?

Employee perspective: 

• How does GenAI influence employees’ self-concept in terms of their professional competence and occupational identity?
• 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 GenAI affect stress levels, autonomy, and motivation at work?
• Are there differences across age groups or levels of experience?
• What new competences emerge in AI-supported roles?
• How does the use of generative AI change training requirements and knowledge retention?

These research questions aim to deepen the understanding of GenAI’s impact on employees’ professional identity and well-being, on operational efficiency, and on competences and learning.

ai:conomics Counts on Collaboration

In the context of the empirical field studies researchers, companies and political stakeholders work together in a co-creative process.
At ai:conomics co-creation is defined as the transdisciplinary work researchers, employers, employees, technology-experts, members of the works council and political decision-makers put in in unity.

Because neither the research object, nor the variety of stakeholders are trivial in this project. The stakeholders are all fulfilling relevant tasks and share often similar, sometimes disjointed, and once in a while opposing interests. Experience clearly shows that even in such a complex field it is possible to work successfully and effectively, if the process of working together has been actively taken care of.
For this reason, we explicitly value a collaborative process design in this project.

In this way, we are testing on a small scale what is needed on a large scale to ensure that as many people as possible benefit from the use of AI in the working world:
Together with many different players, we are creating many new things.

The project relies on competent scientific leadership and practice-oriented partnerships.

The project is being carried out under the leadership of the Research Centre for Education and the Labour Market (ROA) at the Maastricht University School of Business and Economics. As the central research institution, ROA is responsible for conducting the controlled field studies. In doing so, it draws on close collaboration with practice-oriented partners.
The project’s practice partner is a multinational company in electronics manufacturing.

zukunft zwei GmbH: The SME takes over communication, transfer and designs peer learning and (social) partnership collaborations that strengthen the sustainability, outreach and nationwide transferability of the project results. 

Institute for Employment Research (IAB): IAB in Nuremberg is a collaboration partner and, in the relevant parts of the project, is responsible for analyzing and assessing administrative register data.

The project is funded by the Federal Ministry of Labor and Social Affairs (BMAS/ Denkfabrik Digitale Arbeitsgesellschaft) by resolution of the German Bundestag. It follows the recommendation of the German Enquete Commission on AI to conduct evidence-based research on the employment effects of AI deployment in order to support scientific knowledge progress, management decisions, social partnership agreements and political debates.

Benefiting from Diversity of Perspective

A holistic research design that observes the impact of AI on both a small and a large scale and combines a view of technological, economic and social effects requires a diversity of perspectives and extensive expertise. ai:conomics provides this by bringing together experts from science, business, politics and the social partnership who see themselves as a team across organisational and national borders.

A Short Journey Back in Time

The ai:conomics research project started in 2021—at a time when artificial intelligence was already a major topic. However, the focus was more strongly on non-generative AI systems. The major breakthroughs in generative AI, which is now considered a key technology, were still to come.
ai:conomics was established to study the effects of artificial intelligence on our world of work—and what this means in concrete terms for the labor market, companies, and employees. The project launched with the ambition of answering fundamental questions: How do AI systems change tasks and skill profiles? How does the use of the technology affect the productivity and performance of workers in different occupations? How do employees perceive the use of AI, and what effects does it have on their working conditions and well-being?
From the beginning, the project has relied on the methodology of “insider econometrics” and conducted field studies in several companies to examine the use of AI on site. In addition, extensive administrative register data were analyzed to look at developments in the German labor market as a whole and to place insights from the company studies in a broader context.
ai:conomics conducts research in a technology field that is eager for transformation. To ensure that the scientific findings can be used in practice as a basis for decision-making as quickly as possible, the project emphasizes rapid knowledge transfer: results and insights are made publicly available on an ongoing basis even before the project is completed.