Abstract

Organizational development is one of the most important fields of organizational management. With increasing connectivity and digitalization of processes, systems, and data, intrusions via interfaces and subsystems can be affected by the entire system’s security. The manipulation or loss of data in artificial intelligence-based systems takes on a serious role, as the technology learns and acts based on data. Since personal and person-related data and confidential company data, are of particular importance, this issue’s relevance is significant. This study aimed to determine the data access limit for digital systems for organizational development and to investigate user attitudes towards the procession of personal data through artificial intelligence. The main purpose is to provide the research results to target selected security and data protection aspects in the design of organizational development systems based on artificial intelligence. Investigation of this topic is carried out in three logical phases. The first phase provides the analysis of scientific publications. It explores how and under which aspects and conditions digital systems for organizational development depend on information security and data protection. The literature review included keyword network analysis in Scopus with further visualization in VOSviewer. The second part provides a targeted data classification according to security classes, which can be directly applied to design organizational development or management software. In the third phase, there is a survey of respondents from Ukraine and Germany to determine the attitudes towards collecting and analyzing personal data through artificial intelligence. The investigation results show the close connection of the subject’s security and data protection with the change management system, privacy, development of technological models in enterprises, applications for and of process analysis, the legislative basis for information security, etc. According to the survey, the respondents from Ukraine show more neutrality in accepting the collection of personal or personal data through artificial intelligence. Across age and nationality, it can be stated that the majority of respondents are not opposed to collecting and analyzing data about the execution of the activity or behaviour, personal details, family status, education. Scientists and practitioners can directly use the findings for further applications in developing digital systems for organizational development.

Keywords: information security of organizational development system, artificial intelligence for organizational development, protection of organizational data, protection of personal data.

JEL Classification: O34, L2, D2.

Cite as: Skrynnyk, O (2020). Some aspects of information security in digital organizational management systems Marketing and Management of Innovations, 4, 279-289. https://doi.org/10.21272/mmi.2020.4-23

This work is licensed under a Creative Commons Attribution 4.0 International License

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