Starting a career with AI: opportunities and risks

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AI is accelerating career entry

Artificial intelligence is rapidly changing the world of work. Processes are becoming automated, tasks are shifting, and job profiles are being redefined. Anne-Sophie Mayer, Professor of Digital Work at LMU Munich School of Management, is investigating how AI is shaping everyday life and interaction in companies. Her focus is on what this means for the learning, skills, and careers of young professionals.

What newcomers use the tools for

Young consultants use ChatGPT, Copilot, or Midjourney primarily as accelerators. Routine tasks are handed over to the machine, and presentations and visualizations are created faster and often more accurately. Many also use AI as a personal sparring partner, for example for salary negotiations or annual reviews. In some teams, AI also becomes part of the collaboration, reflecting ideas, making recommendations, and helping with brainstorming.

How AI is changing skills acquisition

The use of AI is changing how young professionals learn. On the one hand, junior consultants can work more independently because they can now often use a digital assistant to answer questions that used to be directed to experienced colleagues or managers. On the other hand, this makes it more difficult for managers to identify knowledge gaps or training needs among new team members. In addition, some of the learning that used to take place through direct interaction is being lost because questions, feedback, and joint problem-solving are becoming less common.

Mentoring and networks are becoming more important

Mayer emphasizes that individual mentoring will not be replaced by technology anytime soon. It is still people who recognize potential, open doors, introduce the right people, or specifically include someone in a project. Networks also remain central. They are important for acquiring skills and for career advancement opportunities, but also for corporate culture. If communication and knowledge work are increasingly shifted to AI tools, the dissemination of knowledge within the company may suffer. AI assistants work in isolation with individual users, and many questions, ideas, or solutions remain in the tool and are not shared with the team. Mayer believes that companies have often underestimated this risk so far.

The added value must be visible

The quality of work is also changing. Individual users can become more creative thanks to AI. At the team level, however, there is often greater standardization of content, as other studies suggest. This increases the pressure on young professionals to make their added value visible. Results can be linguistically and visually impressive, even though it remains unclear how they were produced and whether they are accurate. Checking outputs is therefore becoming more important for managers.
Many young professionals seek direct exchange with managers, share helpful prompts, or pursue targeted further training, for example in LLM engineering. Self-marketing is becoming more important because performance is less self-explanatory. Those who want to be perceived as valuable must show more often what their own contribution is and how it differs from that of other colleagues or tools.

Why managers need to demand more and check more thoroughly

Managers are raising expectations. Mistakes are less tolerated, and linguistic and formal quality is assessed more strictly. At the same time, an evaluation problem arises because it is often no longer possible to trace how a result was achieved. Added to this is the risk of professional-looking documents containing incorrect figures or fabricated content. However, managers often lack the time for detailed checks, even though an error in a customer presentation can cause noticeable damage to their reputation.

How companies can counteract this

Some companies are trying to counteract this. In the consulting firm studied, interim reviews were introduced in which junior consultants explain how they arrived at their results and make the work process transparent. This is intended to prevent pure copying and pasting. In addition, a continuing education program was set up that teaches basic skills despite AI and reinforces the reflective use of the tools. At the same time, the company is working on its own language models to increase quality and traceability. This includes requirements to cite sources and show the path to the result, not just the finished result.

Does AI accelerate career advancement?

According to Mayer, it is unclear whether AI helps career starters advance more quickly. She describes a paradoxical situation in which junior consultants are now involved in projects and visit clients earlier, even though they previously spent two to three years mainly doing preparatory work. Nevertheless, this does not automatically lead to faster promotion. In hierarchical industries, senior positions are limited. Some companies are therefore already considering whether they will need as many entry-level positions in the future as they have had in the past.

What career starters can do now

Mayer advises career starters not to avoid AI because the tools can offer great added value, both for individuals and for organizations. At the same time, she says, it is becoming increasingly important to understand how the systems work and how to use them innovatively and responsibly. Career starters can make a valuable contribution by sharing their experiences, pointing out risks, and highlighting potential. She recommends building technical skills, including good prompting or a basic understanding of how an LLM is created. At the same time, career starters should consciously cultivate social networks because relationships within the company remain crucial when it comes to expertise, access to projects and jobs, and personal and professional development.