Abstract

The demand for products continues to increase in today’s society, and to meet this demand
companies are searching for new ways to improve the performance of their workers.
Therefore, there is a constant push to develop and implement new technological solutions
within the Industry 4.0 approach. The aim of this study is to research the different pathways
one could take when implementing these technological solutions and what challenges it
would entail, with a focus on Artificial Intelligence (AI). This is done in collaboration with
Saab Surveillance within their production division, who wishes to increase their
performance within their white-collar environment. In this study, performance is defined and
measured through productivity. The main indicators of productivity will, therefore, be time
dedicated to a task as well as the potential to improve the quality of a task. The result of this
study is presented with a roadmap framework where seven key areas, i.e., work processes,
were discovered that could benefit from AI applications. These areas were uncovered by
conducting a contextual inquiry and semi-structured interviews, and were then matched with
relevant AI applications. The discovered key areas are categorized based on a cost-benefit
analysis, with the scale of; low, medium, and high. The roadmap illustrates in which areas it
could be most beneficial to implement the suggested AI applications. Using this study, Saab
and other companies can make more informed decisions on the pathways for adopting new
technological solutions that will improve the performance of their white-collar workers.