AI powered management through individualization: The dawn of a new management era

Abstract

The objective of the Article is to present the concept of employees' management through individualization, which supports effective attainment of business objectives. The Manager has to manage people with varying belief systems and internal resources. Managers lack tools that would support them in management in a clear, precise and reliable way. In order to manage employees effectively, an IT tool i.e., an AI powered app, was created, which supports people who analyze internal desires of employees and teams, as well as helps translate this knowledge into effective management. The tool was developed drawing on knowledge from various fields: both artificial intelligence (AI) and psychology of management and desires. The application was created on the basis of empirical studies. The app analyzes individual desires of employees and places them on the team's desires matrix in an aggregated way. The software is built using neural networks. Samples were collected during the deep learning process in order to build the model. In the software, each study is treated individually. The results are the basis for further analysis, which generates recommendations and guidelines for the Manager in terms of how to manage and motivate employees. Objectives are also set and ways of communicating them proposed so that they remain consistent with employees' desires. The user evaluates the recommendations, and thus the software learns about their employees and the team and delivers even more optimal tips. The tool was created to support the Manager in their everyday work and its core elements are knowledge about the employee's personality and clues generated by the app for the Manager. The tool gives specific and individualized guidelines for managers on employees' management and it supports organizations in a fast and effective attainment of business objectives. All that thanks to an individualized approach using new information techniques. The proposed IT solution is based on the author's own algorithms and models developed during the research stage.