TRANSFORMATION OF MANAGEMENT FUNCTIONS UNDER THE INFLUENCE OF GENERATIVE ARTIFICIAL INTELLIGENCE
Abstract
The article examines the transformation of management functions under the influence of generative artificial intelligence (GenAI). Its purpose is to synthesise changes in planning, organising, motivating, controlling, coordinating and regulating, and identify boundaries for transferring managerial tasks to technology. The methods include structural-functional and comparative analysis, systematisation and conceptual modelling. The findings show that GenAI does not eliminate management functions but alters the content, speed and informational basis of managerial operations. It advances scenario development in planning, supports hybrid workflows in organising and enables personalised assistance in motivating, while creating risks to employee autonomy. It also facilitates continuous monitoring in controlling, aligns people and information flows in coordinating, and accelerates corrective action in regulating. Three delegation modes are distinguished: assistive, collaborative and partially autonomous. Their selection depends on task formalisation, the scale and reversibility of consequences, output explainability, data confidentiality and the impact on employees. A functional-delegation model is proposed, linking the role of GenAI within each function to the delegation mode, risks, human oversight and powers retained by the manager. Partial autonomy is acceptable only for formalised, repetitive, low-risk and reversible operations within predefined limits. As harm and irreversibility increase, technological autonomy should decrease and human oversight should intensify. Strategic goal setting, ethical and contextual judgement, employee sanctions, reconciliation of conflicting interests and final accountability must remain with the manager. The theoretical contribution lies in integrating functional transformation, delegation modes and managerial accountability within a single framework. The model can inform organisational policies for responsible GenAI adoption. Further research should test it across organisations and assess effects on decision quality, employee motivation and trust.