By 2030, the German labour market alone will lack 3.5 million skilled workers due to demographic change. It will be possible to compensate for some of this by increasing efficiency – but not all of it, you have to be realistic.

What does AI mean for the skills shortage?

AI has been on everyone’s lips since 2022, including the general public, and therefore also opens up broad opportunities for companies when it comes to the skills shortage. A certain basic understanding of AI is important – because AI is not just AI.

What everyone is currently talking about is generative AI, which can, for example, generate texts based on internal expertise. Another type of AI is computer vision, for example, which can analyse images with the help of cameras. A third technical solution is machine learning AI, which can predict decisions.

So before generalising, you need to know what type of AI you are talking about, as each AI offers different use cases and can therefore help in different situations:

Generative AI against the skills shortage

  • Can help office staff to quickly access internal company expertise
  • Can automatically answer tickets in customer support or intercept enquiries directly via an intelligent bot on the website
  • Can create training documents
  • Can help to formulate texts quickly – e.g. for quotations
  • Can check texts and make suggestions for improvement

Computer vision against the shortage of skilled labour:

  • Can recognise inadequate products in quality control, for example, and sort them out automatically
  • Recognises content on documents to classify them automatically
  • Search for images
  • Checking safety equipment for employees, for example

Machine learning to combat the shortage of skilled labour

  • Automation of selection processes, e.g. when setting production parameters
  • Predictive maintenance and servicing of machines so that machines are only serviced as planned and there are no unwanted downtimes

Why is AI not the panacea for the skills shortage?

Although AI offers many benefits and can address various issues related to the skills shortage, there are some limitations and challenges that need to be considered:

  • Complexity of tasks: Some tasks require human intelligence, creativity and interpersonal skills that cannot currently be fully replicated by AI. Complex problem solving, strategic thinking and empathy are examples of skills that will still be required from human professionals.
  • Data protection and ethics: The use of AI can raise data protection and ethics issues, especially when it comes to processing sensitive data or automating decisions with far-reaching effects on people. Companies must ensure that their AI systems are transparent, fair and ethical in order to minimise potential risks and harm. We therefore recommend focussing on German or European providers in particular, who are subject to stricter regulations than larger companies.
  • Costs and resources: The development and implementation of AI systems often requires significant investment in technology, expertise and infrastructure. Smaller companies or those with limited resources may not be able to bear these costs or overcome the required skills shortage. Nevertheless, there are already some government support programmes in place to help these companies with implementation.
  • Dependence on data quality: AI models are heavily dependent on the quality and availability of data. If the underlying data is faulty, incomplete or unrepresentative, the AI models can be inaccurate or biased. This can lead to poor decisions and fail to effectively address the skills shortage. We cannot speak for all systems, but some generative AI solutions, such as amberAI, do not require training of their AI models and work out-of-the-box.
  • Resistance and acceptance: Employees may show resistance to the use of AI for fear of job loss or changes in their work processes. Successful implementation of AI therefore requires not only technological innovation, but also change management strategies to promote employee acceptance and collaboration. Strong communication and the identification of alternative positions within the organisation in line with AI is necessary so that employees do not fear losing their jobs.

Impact of AI on the world of work

With the introduction of (generative) AI into the world of work, it is not only the technology that is changing, but also the understanding and tasks of employees. In the context of New Work, the aim is to promote flexibility, self-determination and a sense of purpose in the workplace, while AI helps to utilise knowledge more efficiently and support decision-making processes.

Traditional notions of human capital are being challenged by the ability of AI to collect, filter and process information. It is no longer crucial that employees master all knowledge in detail, but rather that they are able to access this knowledge, understand it and make informed decisions based on it.The use of AI tools such as retrieval augmented generation systems enables information to be provided quickly and up-to-date, allowing employees to focus on value-adding activities such as customer interaction or the development of innovative solutions.

This change also has an impact on the selection and evaluation of employees, with soft skills and the ability to utilise methodologies and AI tools becoming increasingly important. Companies that want to successfully shape this change must not only consider the technological aspects, but also develop a new mindset and a corresponding digital strategy that is exemplified by managers and supported by employees.