Fit for AI: Which skills will become important in the working world
Artificial Intelligence (AI) will change the everyday working lives of many employees - in the factory as well as in the office. The new division of labor between humans and technology requires new skills. The central challenge for the successful introduction of AI systems in companies is therefore the further training of employees. In a recent white paper, experts from Plattform Lernende Systeme analyze the competencies required for different job profiles in the age of AI for an industrial worker, a skilled worker and a controlling employee, and show how these competencies can be developed in six task-oriented steps.
AI-based software systems and robots can relieve people of monotonous routine tasks as well as physically demanding activities and make work richer. AI systems enable more efficient processes and competitive business models in companies. For their use to succeed, employees must be empowered to handle the technology and changed work processes.
"The key to good work in the AI age lies in qualification. On the one hand, the goal is to enable employees to take on new and possibly higher-value tasks. On the other hand, people should be able to deal competently with AI systems. Not all employees need to develop into AI experts, but a basic understanding of the technology, its limits and possibilities is also necessary outside of IT departments," says Wilhelm Bauer, director of the Fraunhofer Institute for Industrial Engineering IAO and head of the "Future of Work and Human-Machine Interaction" working group of Plattform Lernende Systeme.
Physical and operational skills required to perform routine tasks will become less important in the future, according to the working group's white paper "Competence development for AI". In addition to technical skills, communication or problem-solving skills, creativity or reflection skills will become more important in the future when working with AI-based systems in order to be able to react spontaneously to problems and perform unpredictable tasks. People will not only develop AI systems or use them on the job. Rather, employees will become trainers of AI, since - unlike conventional technologies - it is constantly evolving through interaction with users.
Fraunhofer Institute for Industrial Engineering IAO
"The key to good work in the AI age lies in qualification. On the one hand, the goal is to enable employees to take on new and possibly higher-value tasks. On the other hand, people should be able to deal competently with AI systems. Not all employees need to develop into AI experts, but a basic understanding of the technology, its limits and possibilities is also necessary outside IT departments."
The specific competencies required by people in the workplace depend on their respective roles and tasks as well as on the AI technology used. The authors of the white paper illustrate this with concrete examples of different competence profiles in a company. For example, a skilled worker in industrial production must acquire new competencies in human-machine interaction as well as new technical competencies in order to work safely hand-in-hand with and train a robotic tool that is capable of learning. A controlling employee, on the other hand, will need less expertise in budget management in the future, as these operational tasks will now be handled by an AI system. Instead, decision-making and communication skills are required to evaluate the results of the AI system and present them to the company management.
In order to capture the changes in the necessary competencies in the company and to develop suitable training formats, the authors recommend a structured, task-oriented concept management process in six steps:
- Determination of job roles in the context of AI
- Assignment of tasks in the changed division of labor between humans and AI
- Definition of specific AI competencies required for task fulfillment
- Definition of competence profiles for each job role
- Competence needs analysis
- Definition of suitable training measures
Acquiring new competencies alongside the job is a major challenge for employees. The experts from Plattform Lernende Systeme emphasize that in-company continuing education must be supported by working conditions that are conducive to learning. This includes suitable knowledge transfer technologies such as virtual reality, opportunities to gain experience, but also a management structure that enables employees to help shape change in their company.
An adapted management culture is the success factor for the introduction of AI systems. A positive culture of error must be established that encourages employees to think and act independently and critically with regard to AI systems. According to the authors, training employees to use AI is not the sole responsibility of companies. Creating an understanding of the fundamentals of the technology is first and foremost a social task.
About the white paper
Linda Treugut / Birgit Obermeier
Press and Public Relations
Lernende Systeme – Germany's Platform for Artificial Intelligence
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