VoBAKI

  Specialist working on a computer Copyright: © Martin Braun Project logo VoBAKI  

Assessment and Selection Approach of AI Competencies in SMEs

 

Key Info

Basic Information

Duration:
01.01.2022 to 30.06.2024
Research Area:
Work Scientific Support of Change and Transformation Processes
Status:
Running

Contact

Name

Susanne Mütze-Niewöhner

Head of Work Organization Department

Phone

work
+49 241 80-99451

Email

E-Mail
 

Synopsis

In order to improve processes, Artificial Intelligence is used more and more as a technology in various business areas. Particularly large companies are already using the potential of AI. Yet small and medium-sized enterprises, or SMEs, also experience competitive and innovative pressure, thus, they increasingly develop interest in the implementation and use of AI applications. Nonetheless, small and medium-sized businesses face several obstacles in implementing AI technologies, such as high costs, a low quality of available data, and, on the personnel side, fear of change as well as a lack of knowledge. The recruitment of personnel with the appropriate knowledge is already proving difficult in times of a shortage of skilled workers, so further strategies are required to acquire, develop and secure AI competencies in the long term. The aim of the project VoBAKI is therefore to create a structured approach for the evaluation and selection of sourcing strategies in the lifecycle of an AI application. The project’s goal is to enable SMEs to identify necessary AI competencies and to select the most suitable strategies for competency assurance.

Challenges

When planning the implementation of an AI application, it is necessary to consider competencies that are required along the entire lifecycle of the application to ensure that it can be implemented successfully in the company. Therefore, it is inevitable that people with different roles do need varying competencies on the AI technology. Here, companies face the challenge of bringing the necessary AI competencies into the company or reducing existing competency gaps. This challenge is illustrated in the following two examples:

Even though the recruiting of new personnel is a source of gaining competencies, it needs to be considered that the industry-wide shortage of skilled workers makes this sourcing strategy quite difficult, especially when SMEs need to compete with large companies. Alternatively, they may engage extern service providers to bridge the competency gaps. However, since AI competencies are needed not only for the application itself, but often in upstream and downstream processes, this sourcing strategies’ long term profitability is questionable. This makes it necessary for companies to leave the classic ways of competency acquisition and to develop and use new sourcing strategies.

Goals

The VoBAKI project aims to enable SMEs to independently identify processes and competencies needed in the lifetime cycle of an AI application and based on this, to deviate the most fitting sourcing strategies. In close cooperation between research partners and members of the project's accompanying committee, a procedure is being developed to support SMEs in the evaluation of AI competencies and the corresponding selection of sourcing strategies.

Methodology

At the beginning, the research partners work out goals regarding the use of AI applications together with the practice partners. The following step is to identify relevant processes and activities in the lifecycle of an AI technology, for example, planning, implementation, use, and maintenance. Then, for all of those activities, necessary AI competencies in particularly can be determined. Subsequently, the activities identified and associated with competence requirements can be assigned to different AI roles. This results in clear role profiles in which the required AI competencies are mapped.
Possible sourcing strategies are to be described and concretized with respect to the application context as well as evaluated with respect to their practical relevance. Depending on business demands and prerequisites, the different sourcing strategies and their possible designs are evaluated in terms of their contribution to achieving operational objectives. The results will be consolidated into an approach for evaluation and selection of the most appropriate sourcing strategy.

Funding

This research project is funded within the scope of the program to promote joint industrial research by the BMWK – Bundesministerium für Wirtschaft und Klimaschutz (German Federal Ministry of Economic Affairs and Climate Action) via the AiF – Arbeitsgemeinschaft industrieller Forschungsvereinigungen e. V. (German Federation of Industrial Research Associations).
The VoBAKI project is run together with FIR e.V. at RWTH Aachen University and the FKM working group “Forschung I4.0 und KI (Research I4.0 and AI)”. The project committee consists of companies of different industries and sizes.

IGF-Project No.: 22009 N

Project Partner

FIR e.V. at RWTH Aachen University

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