How AI is changing occupational roles, skills, and career paths

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What does it mean for professionals and organizations when artificial intelligence is deployed for decision-making and other tasks that were previously exclusively performed by human experts? And what consequences does the increasing use of AI have for organizations and the social relationships of which they are made? Professor Anne-Sophie Mayer.

investigates these questions by using ethnographic methods that allow insights from cases and companies from various industries and fields.

“What we’re seeing in all different contexts – whether it’s in radiology, loan consulting, or recruiting – is that in most cases it’s not about replacing humans with a new technology as often suggested by public discourses. Instead, we see how professionals’ role profiles, professional identities and competencies are fundamentally changing through the increasing deployment of emerging technologies such as AI,” says Mayer.

Mayer has been Professor of Digital Work at LMU since April 2025, which she describes as her absolute dream job: “It’s a great privilege to be able to work at such a renowned institute.” Previously, she worked for three years at the KIN Center for Digital Innovation of the Vrije Universiteit Amsterdam, first as a postdoctoral researcher and then as assistant professor. Initially, she wanted to become a teacher, but decided instead to pursue her interest in business administration. She completed a dual-degree program in international business studies at Harz University of Applied Sciences and Otago Polytechnic in New Zealand. Subsequently, she undertook a master’s degree in international cultural and business studies at the University of Passau, where she also obtained her doctorate. “From the first day of my doctoral studies, I enjoyed research so much that I just knew I wanted to stay in academia,” she recalls.

Exploring AI’s impact on work through on site field work

Her research has a sociotechnical focus, holistically considering the technology, the user, and its environment when studying the impact of AI and other emerging technologies on work and organizations. This has generated a lot of interest from businesses. “Management often underestimates the importance of the perceived meaningfulness of one’s job – and this meaningfulness drastically changes in many cases where AI is deployed, even if the job is not intended to be replaced.” Mayer’s studies show that management and HR departments should actively shape the role change of professionals when introducing AI, as otherwise, the technology implementation can lead to dissatisfaction and misbehavior.

For instance, in a project within the banking sector, the researcher observed how loan officers affected by the introduction of an AI-based decision system attempted to “game” the tool that had begun making loan decisions on their behalf. They hoped to influence the outcomes in their favor by manipulating the AI’s inputs. This finding proved valuable to the company in two ways. First, it revealed the difficulties employees faced when advising customers based on opaque AI decisions that they could not verify or fully understand. Second, the manipulation attempts exposed incorrect outputs of the AI system, which were subsequently improved through the employees’ domain expertise.

New challenges for managers through AI

Another research area of Mayer explores the implications of algorithmic management on workers, organizations and digital platforms. For example, in the platform economy, which includes companies such as Uber and Amazon Mechanical Turk, many management decisions are now made by algorithms rather than humans. These decisions include the evaluation of performance and the determination of pay rates. Mayer investigates what it means for affected stakeholders when traditional management functions are delegated to algorithms instead of being carried out by humans.

In this context, Mayer also explores how more advanced AI tools, in particular generative AI technologies, reconfigure how managers work. For instance, when employees begin to obtain everyday information and guidance from GenAI tools rather than from their supervisors or colleagues, this can erode managers’ ability to assess their teams effectively. “Expertise is relational: It is acquired by asking others for advice, learning from one’s own mistakes, and from the mistakes of others,” Mayer explains. She raises the question of what happens to organizations when these social interactions diminish and managers lose direct insight into where employees stand and what support they need. “As a manager, how do I identify high performers and evaluate who is doing well? Is it those who can present their ideas persuasively on their own, or those who are skilled at prompting? And how does this transformation reshape career requirements and trajectories?”

These questions are also directly relevant for young professionals entering the workforce. In a recent study, Mayer explored this topic through the example of new-entry professionals in the consulting sector, examining how the adoption of AI affects their early career experiences and development.

Her students share this curiosity about the implications of AI—after all, they will soon face these issues themselves. Mayer recalls “many very open, lively, and critically engaged discussions” during her first semester at LMU. “I was impressed by how interested and active the students were,” says the professor, adding that she too benefits from these exchanges: “When it comes to AI, there are always new things to learn.”