An Analysis of Knowledge Management Changes Through Artificial Intelligence with Probst's Model

In recent years, the integration of Artificial Intelligence (AI) into Knowledge Management (KM) has led to transformational changes. These changes have significantly enhanced traditional KM processes. To identify how AI technologies improve and reshape knowledge processes, this study conducted a systematic literature review. The review identified AI technologies suitable for each of Probst's building blocks, which outline the eight central KM processes. The research reveals a wide range of AI technologies, including machine learning, natural language processing and chatbots such as ChatGPT. These technologies can be applied in different domains and introduce innovative approaches to improve KM processes. Based on the AI technologies analysed, this study proposes a four-stage model to support the documentation and application of best practices and lessons learned. The model is designed to enhance the knowledge development process and aims to document and secure key project developments in the long term. A further objective was to analyse which KM process is most affected by chatbots. The findings indicate that chatbots have the potential to transform the use of knowledge in organisations. They act as facilitators by breaking down existing barriers, foster an open culture of knowledge sharing, streamline workflows and increase the accessibility of knowledge. The study also examines the broader changes that AI will bring to KM and forecasts the sixth generation of KM. It draws on Bencsik's (2021) evolutionary and revolutionary perspectives that specifically forecast this next generation. The study shows that AI not only enhances existing KM processes but also has the potential to fundamentally disrupt traditional methods and approaches. These findings underline the need for future research to explore the effective integration and scalability of AI technologies in real-world KM environments. This will help ensure that their long term impact and potential benefits are fully understood across different industries and organisational contexts.

Authors

Institutions

Publication Details

Journal
Proceedings of the International Conference on AI Research.
Published
2024-12-04
DOI
https://doi.org/10.34190/icair.4.1.3156
Citations
1
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Analysis of Knowledge Management Changes Through Artificial Intelligence with Probst's Model

Burak Toptas
1 citations
Proceedings of the International Conference on AI Research.
Organizational and Employee Performance
0.35
article

An Analysis of Knowledge Management Changes Through Artificial Intelligence with Probst's Model

Burak Toptas
article en
1 citations

Abstract

In recent years, the integration of Artificial Intelligence (AI) into Knowledge Management (KM) has led to transformational changes. These changes have significantly enhanced traditional KM processes. To identify how AI technologies improve and reshape knowledge processes, this study conducted a systematic literature review. The review identified AI technologies suitable for each of Probst's building blocks, which outline the eight central KM processes. The research reveals a wide range of AI technologies, including machine learning, natural language processing and chatbots such as ChatGPT. These technologies can be applied in different domains and introduce innovative approaches to improve KM processes. Based on the AI technologies analysed, this study proposes a four-stage model to support the documentation and application of best practices and lessons learned. The model is designed to enhance the knowledge development process and aims to document and secure key project developments in the long term. A further objective was to analyse which KM process is most affected by chatbots. The findings indicate that chatbots have the potential to transform the use of knowledge in organisations. They act as facilitators by breaking down existing barriers, foster an open culture of knowledge sharing, streamline workflows and increase the accessibility of knowledge. The study also examines the broader changes that AI will bring to KM and forecasts the sixth generation of KM. It draws on Bencsik's (2021) evolutionary and revolutionary perspectives that specifically forecast this next generation. The study shows that AI not only enhances existing KM processes but also has the potential to fundamentally disrupt traditional methods and approaches. These findings underline the need for future research to explore the effective integration and scalability of AI technologies in real-world KM environments. This will help ensure that their long term impact and potential benefits are fully understood across different industries and organisational contexts.

Proceedings of the International Conference on AI Research.Vol. 4(1)
Lutheran University of Applied Sciences Nuremberg (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 31%
Organizational and Employee Performance
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An Analysis of Knowledge Management Changes Through Artificial Intelligence with Probst's Model — Burak Toptas · Proceedings of the International Conference on AI Research. (2024) | TGRS Research Map | TGRS