The working world of the future will be shaped by Artificial Intelligence (AI). However, it is not yet clear what this will mean in detail for companies, employees and social partners. Therefore, generating a broad knowledge base is a prerequisite to understanding the complex impact of AI on the working world and  to shaping it positively going forward: what is the current state of research? What assumptions can currently be used as a basis? Scientists working on ai:conomics, a research project funded by the Policy Lab, have put together a short dossier of answers to these questions.

Research findings to date can be summed up as follows: 

1. AI has the potential to change the working world more than any previous technology

Previous technological innovations such as computerisation, automation and robotisation all had one primary aim: to make people’s work easier by relieving them of simple routine activities. These advancements were based on automated processes derived from explicit rules and manually written computer programs. AI is different: it is self-learning and able to infer connections independently. As such, it can also assist people with tasks that are analytic and more complex, tasks that frequently cannot be explicitly, systematically described so as to encompass all their various aspects and elements. This means AI is already capable of handling more activities than earlier technologies, and its impact on all professions and sectors will only grow more pronounced in the future.

2. AI is going to replace some tasks while creating new ones

Will the use of AI in the future mean fewer jobs or perhaps more jobs? Just like previous technological innovations, AI applications are going to take on certain tasks formerly carried out by human beings. This is already happening today in fields such as speech and image recognition. But AI can also assist people in their work without replacing them – for example, as a decision-making aid in the detection of cancer. It is also capable of creating entirely new occupations, one example being the specialists who create high-quality data sets for the development and operation of AI. It is not yet clear what form such developments will take. That depends on us and how we shape the use of AI technologies, today and tomorrow.

3. AI creates new qualification requirements

Artificial Intelligences continue to improve. Yet to date, they cannot match the intelligence of human beings, particularly when it comes to tasks calling for a high level of interpersonal and social skills or strong creativity – such as problem-solving, communicating work content or results, or collaborating in interdisciplinary teams. It will therefore be essential that future workforces acquire these capabilities. However, there has so far been little research into what qualifications will be needed in concrete terms. For the future, this means that people need above all to understand the ways in which AI is changing the work they do. They will then be able to develop the skills necessary in order to use this technology productively.

4. AI can improve the work environment – under certain conditions

Past experience shows that new technologies – irrespective of the opportunities they bring with them – can also create increased insecurity and mistrust amongst employees, and that this can impact negatively on motivation, cooperation or satisfaction. This is certainly a risk with AI systems as well. If they generate stress, exhaustion, fear of surveillance or job losses, not only can job satisfaction suffer but so too can employability in the form of mental health issues, for example. On the other hand, this also means that when the use of AI is conceived and implemented properly, it can impact positively on employees by easing their workloads or allowing them greater autonomy, flexibility and creativity. For the future, therefore, it will be essential to ensure that AI technology does not become a burden for employees.

5. Further research is needed

Sooner or later, AI will make its way into every company, albeit to varying degrees. It is not yet possible to give a general assessment of how this will affect workplaces and employees. Further information is needed from the actual companies where AI is being deployed, and this is precisely where the project ai:conomics aims to make a contribution. Case studies are tracking the practical introduction of AI technologies. Because they operate under quasi-laboratory conditions, such studies are able to examine the impact on work tasks and on the skills profiles, health and job satisfaction of employees, and to highlight opportunities for shaping the future. The resulting findings will integrate a wide range of actors, and as such will enable policymakers, the business sector and social partners to make the right decisions, leading to a human-centric use of AI for the public good.