@article{OlanNyuurArakpogunetal.2023, author = {Olan, Femi and Nyuur, Richard B. and Arakpogun, Emmanuel Ogiemwonyi and Elsahn, Ziad}, title = {AI: A knowledge sharing tool for improving employees' performance}, journal = {Journal of Decision Systems}, issn = {1246-0125 (Print)}, doi = {10.1080/12460125.2023.2263687}, institution = {IfTI - Institute for Trade and Innovation}, pages = {1 -- 21}, year = {2023}, abstract = {The utilisation of artificial intelligence (AI) is progressively emerging as a significant mechanism for innovation in human resource management (HRM). The capacity to facilitate the transformation of employee performance across numerous responsibilities. AI development, there remains a dearth of comprehensive exploration into the potential opportunities it presents for enhancing workplace performance among employees. To bridge this gap in knowledge, the present work carried out a survey with 300 participants, utilises a fuzzy set-theoretic method that is grounded on the conceptualisation of AI, KS, and HRM. The findings of our study indicate that the exclusive adoption of AI technologies does not adequately enhance HRM engagements. In contrast, the integration of AI and KS offers a more viable HRM approach for achieving optimal performance in a dynamic digital society. This approach has the potential to enhance employees' proficiency in executing their responsibilities and cultivate a culture of creativity inside the firm.}, language = {en} }