The Impact of Artificial Intelligence on Tacit Knowledge in Modern Organizations: A Comprehensive Review

Session

Medicine and Nursing

Description

This comprehensive review explores the transformative impact of Artificial Intelligence (AI) on tacit knowledge man- agement in modern organizations. Tacit knowledge, which is deeply embedded in individual experiences and often difficult to ar- ticulate, is a critical asset for innovation, problem-solving, and decision-making. However, its elusive nature presents significant challenges in terms of capture, sharing, and utilization within organizational contexts. AI technologies, including natural lan- guage processing (NLP) and machine learning, are emerging as powerful tools to address these challenges by enabling the identi- fication, codification, and dissemination of tacit knowledge. The review systematically examines the role of AI in enhancing knowledge management processes by analyzing vast amounts of unstructured data, such as emails, meeting transcripts, and col- laborative workspaces. These AI-driven tools can uncover hidden patterns and insights that were previously inaccessible, thereby transforming tacit knowledge into more explicit forms that can be easily shared across organizational boundaries. This democra- tization of knowledge not only fosters a culture of continuous learning but also breaks down knowledge silos, allowing for more effective collaboration and innovation.The review identifies potential risks, such as the oversimplification of complex knowledge and the ethical concerns related to data privacy and employee trust. There is a danger that AI may reduce nuanced, context- specific knowledge to algorithmic outputs that lack the depth necessary for effective application. The review concludes by em- phasizing the need for a balanced approach to AI integration in knowledge management. Organizations must leverage AI's strengths while safeguarding the essential human elements of knowledge creation and sharing. Future research should focus on developing ethical frameworks and best practices to ensure that AI enhances rather than diminishes the value of human knowledge in organizational settings.

Keywords:

Artificial Intelligence, Tacit Knowledge, Knowledge Management, Information Technology, Organizational Learn- ing.

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-982-15-3

Location

UBT Kampus, Lipjan

Start Date

25-10-2024 9:00 AM

End Date

27-10-2024 6:00 PM

DOI

10.33107/ubt-ic.2024.348

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Oct 25th, 9:00 AM Oct 27th, 6:00 PM

The Impact of Artificial Intelligence on Tacit Knowledge in Modern Organizations: A Comprehensive Review

UBT Kampus, Lipjan

This comprehensive review explores the transformative impact of Artificial Intelligence (AI) on tacit knowledge man- agement in modern organizations. Tacit knowledge, which is deeply embedded in individual experiences and often difficult to ar- ticulate, is a critical asset for innovation, problem-solving, and decision-making. However, its elusive nature presents significant challenges in terms of capture, sharing, and utilization within organizational contexts. AI technologies, including natural lan- guage processing (NLP) and machine learning, are emerging as powerful tools to address these challenges by enabling the identi- fication, codification, and dissemination of tacit knowledge. The review systematically examines the role of AI in enhancing knowledge management processes by analyzing vast amounts of unstructured data, such as emails, meeting transcripts, and col- laborative workspaces. These AI-driven tools can uncover hidden patterns and insights that were previously inaccessible, thereby transforming tacit knowledge into more explicit forms that can be easily shared across organizational boundaries. This democra- tization of knowledge not only fosters a culture of continuous learning but also breaks down knowledge silos, allowing for more effective collaboration and innovation.The review identifies potential risks, such as the oversimplification of complex knowledge and the ethical concerns related to data privacy and employee trust. There is a danger that AI may reduce nuanced, context- specific knowledge to algorithmic outputs that lack the depth necessary for effective application. The review concludes by em- phasizing the need for a balanced approach to AI integration in knowledge management. Organizations must leverage AI's strengths while safeguarding the essential human elements of knowledge creation and sharing. Future research should focus on developing ethical frameworks and best practices to ensure that AI enhances rather than diminishes the value of human knowledge in organizational settings.