Author
Listed:
- Górka, Ernest
- Ćwiąkała, Michał
- Wojak, Gabriela
- Baran, Dariusz
- Soboń, Janusz
- Muszyński, Adam
- Saługa, Kamil
- Zawadzki, Daniel
- Agaciński, Marcin
- Wyrzykowska-Antkiewicz, Monika
- Magda, Jan
Abstract
Purpose: This paper examines how artificial intelligence (AI) tools influence employees' work-life balance (WLB) in contemporary organizations. It analyzes both the opportunities and the risks associated with the implementation of AI in work design, communication, learning, and performance management. The study also explores how AI-supported practices may affect employee motivation, well-being, and organizational effectiveness. Design/methodology/approach: The article adopts a conceptual research approach based on a critical review of literature on work-life balance, digital work, artificial intelligence, and human resource management. The analysis integrates perspectives from organizational behavior, management studies, and selected business practice examples. Particular attention is given to AI-enabled flexibility, task automation, and the ethical implications of digitally mediated work systems. Findings: The analysis suggests that AI may positively support work-life balance by automating routine tasks, enabling more flexible work arrangements, and personalizing learning and work processes. At the same time, AI may also intensify boundary erosion, permanent connectivity, and performance pressure if implemented without appropriate safeguards. The findings indicate that the impact of AI on WLB is not inherently positive or negative, but depends on organizational design, managerial practice, and the human-centeredness of implementation. Research limitations/implications: The paper is conceptual and based on secondary sources rather than original empirical data. Future research should examine how specific AI tools influence work-life balance across occupations, sectors, and demographic groups. Additional empirical studies could also assess the long-term effects of AI-supported flexibility on motivation, burnout, and employee retention. Practical recommendations: Organizations should adopt a human-centered approach to AI implementation and ensure that digital tools support rather than undermine employee well-being. HR departments should combine AI deployment with transparent governance, flexible work policies, digital boundary protection, and ethical data practices. AI should be used to reduce unnecessary workload, increase autonomy, and strengthen employee support systems.
Suggested Citation
Górka, Ernest & Ćwiąkała, Michał & Wojak, Gabriela & Baran, Dariusz & Soboń, Janusz & Muszyński, Adam & Saługa, Kamil & Zawadzki, Daniel & Agaciński, Marcin & Wyrzykowska-Antkiewicz, Monika & Magda, J, 2026.
"AI as a Tool for Improving Work Efficiency and Well-Being,"
EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(1), pages 607-618.
Handle:
RePEc:zbw:espost:339721
DOI: 10.35808/ersj/4334
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JEL classification:
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
- M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
- M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management
- O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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