Digital Workplace : Information overload: User perspective and application of artificial intelligence

University essay from Linnéuniversitetet/Institutionen för informatik (IK)

Abstract: Information overload is a well-known phenomenon and researchers from the different field have identified the related factors based upon their interpretation and their respective field of specialization like psychology, information system, organizational studies, social structure and accounting. Aim of this qualitative study is to investigate user experience, their perception and opinion about the factors responsible for information overload in today’s digital workplace and how artificial intelligence is used in the organization to overcome information overload. An interpretive method is used in this study to capture the perception and experiences of users. This study has been taken place in a knowledge-intensive organization. Total seven users were interviewed, and the convenient sampling method was used to select the participants. Interviewees were selected from different job profile, age and varied years of experience to seek representation from diverse perspectives on the topic. Lichtman Thematic analysis method is used for data analysis. This study finds that despite all technological advancement at the workplace, information overload is still a problem and should be a priority for an organization to address. We have seen some good feedback of the tools with embedded intelligence which motivates the organization to explore the use of artificial intelligence more to make information processing easier and more accessible to the right recipient. This study also helps us to understand the need for intelligent tools at the digital workplace to manage and filter the required information to reduce information overload. The tools which can learn user behaviour and can act automatically without manual interference, augment with human intelligence and plays a vital role in reducing the overload. Even every participant was not aware of the features which are inbuilt inside the tool but over time can sense that they are getting right and accurate information.

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