What the future costs

According to Reuters, BMW invests 400 million euros in its training programs every year. Moritz Kippenberger, vice president for personnel services, recruitment, and qualifications at BMW, assumes that through additional training, over 90 percent of the required competencies can be achieved based on the existing skills of the employees. Lifelong learning is therefore an important keyword. Volkswagen is also investing heavily in qualifications; in 2023, the company spent a total of about 399.3 million euros on further training without vocational training.

Artificial intelligence, in particular, is driving the need for qualification measures further. "Digitalization and AI lead companies to not only reevaluate their processes but also rethink their qualification concepts," says Simone Kauffeld, professor of work and organizational psychology at TU Braunschweig. The trend is also moving towards shorter training sessions that focus on specific continued learning for the job. Lengthy qualifications are becoming less common, partly because it is often unclear how job profiles might change in the near future.

AI and data experts are in demand

For example, Mercedes-Benz announced as early as 2023 that it plans to invest over 2.2 billion US dollars in employee training by 2030. With corresponding programs, employees from production, production-related areas, and administration are to be specifically trained as data and AI specialists. From the perspective of the Stuttgart-based automaker, the further development of digital skills in the workforce is crucial for the future of the company.

Especially now that many repetitive tasks are being eliminated by generative AI, qualification becomes all the more important so that people can focus on more creative, value-adding, or strategic tasks. This could change many career paths in the long term. "AI is far more than an automation tool - it is increasingly evolving into a co-worker with whom we enjoy collaborating. For this collaboration to be successful, both humans and AI must continue to develop," states Corina Apachite, Program Head Artificial Intelligence and Key Technologies at Continental.

Retraining programs should therefore not only aim to prepare people for new tasks, but also strengthen their ability to interact efficiently and creatively with AI. From Apachite's perspective, this includes not only building AI competencies but also focusing on collaboration with AI. Training should promote dealing with AI as a partner in decision-making processes and creative workflows, according to Apachite.

In addition, interdisciplinary learning must be at the forefront: the goal is a combination of technological knowledge with domain-specific skills to fully exploit the added value of AI, especially in the automotive industry. "Only in this way will people be enabled to use AI not just as a tool, but as a true innovation partner in value-creating processes," adds the tech expert.

Can the middle class catch up on new topics?

The Tier-1 supplier has established the Continental Institute for Technology and Transformation (CITT) as a competence center for digital transformation and qualification. Continuing education programs are offered here for all qualification levels. This applies to both Continental employees and external customers and partners who can prepare their employees for the AI-supported working world there. The practical training takes place in training facilities such as TechSpaces for 3D printing, robotics, and augmented reality.

Progress from the corporation is also making its way into the training world, such as the AI awareness training developed in collaboration with the Continental AI Lab in Berlin. "The CITT actively supports the industry in shaping change by offering innovative learning formats and strategically promoting AI competencies," reports Corina Apachite.

These skills secure developers and engineers their jobs

The automotive industry is in crisis. Development engineers are also noticing this. Should they be worried about the cuts at OEMs and suppliers? Not if they have special skills.

This can be an important contribution, as small and medium-sized suppliers often find it difficult to keep up with the further qualification of their team due to a lack of resources. For SMEs, it is therefore advisable to rely on structures such as digital centers or local transformation networks like ReTraSON, says Simone Kauffeld. It has proven successful, for example, for employees to learn from each other in networks with other companies.

Especially with regard to AI and specifically to large language models (LLM), she sees a significant gap in the automotive mid-market. "Although some companies have already understood the relevance of the technology, many are in a waiting position. It is important not to wait for the big strategy but to start and gain experience - and to offer training and clear guidelines for AI use," says Kauffeld. However, due to market developments, many companies are currently focusing on reducing jobs rather than on current qualification approaches.

Transfer gap is a problem

How and in what formats learning takes place also determines whether investments in further education are actually worthwhile. "Surveys show that often only ten percent of newly learned further education knowledge reaches the company. Due to the typical transfer gap, it remains unclear how the newly learned knowledge could be practically applied. The trend towards digital learning platforms, where employees learn on their own initiative, has not been very helpful," explains Kauffeld. While some people cope well with this form of learning, this is not the case for many others - thus these approaches lack efficiency.

Instead, Simone Kauffeld advocates for focusing on transfer projects where work and learning merge. "The external knowledge input is directly applied to work on practical projects internally over a longer period of time and thus become 'change makers'," says the expert.

This concept is also adopted by Mercedes-Benz with its part-time qualification program D.Shift. Employees from production who are interested in data and AI can apply for a "Digital Challenge" and retrain as data specialists. During the program, they receive intensive support and guidance, already work on concrete practical projects, and complete internships. At the end of the program, they transition to the target positions defined and established at the beginning.