Artificial intelligence in knowledge management

In this article, we devote ourselves to the subject of artificial intelligence in knowledge management and how to work effectively. The AI ​​resumes automation of processes that consume time until the provision of personalized information. Integration will increase efficiency, knowledge gaps and support teams to work more in a more productive way.

Artificial intelligence (AI) transforms knowledge management by automating the tasks that consume time beforehand. It allows new approaches to use knowledge and an increase in process efficiency.

Most applications include:

1. Automated categorization: The AI ​​assesses and sorts the content such as documents, reports and presentations. It is not only saving time, but simplifies the search for relevant information.

2. Personalized recommendations: Based on the analysis of user behavior, AI offers specific content due to the needs of employees.

3. Training with company specific data: AI models can be trained with internal information to answer targeted questions and provide individual analyzes.

The generative AI is enormously extends the possibilities of knowledge management because it creates and actively optimizes the content, the examples are:

• Automated text entry: Artificial intelligence in knowledge management can create on the basis of data, reports, protocols or existing articles. Employees save a lot of time here.

• Creation of visualizations: Diagrams, infographics or illustrations are automatically generated to make content more understandable and improve communication.

• Recognize connections: The AI ​​assesses the documents, identifies thematic relationships and missing information supplements.

1. GAILING ON TIME: The tasks that are part of the routine, such as marking of documents or reports, are automated, which creates capacities for other areas of responsibility.

2. Increase in efficiency: All information is quickly available, which improves cooperation between teams and accelerates other processes.

3. Scalability: AI knowledge -based knowledge management systems adapt flexibly to the company's requirements and can easily be integrated into various industries.

4. Fail reduction: Automated processes reduce human errors and increase the quality of the final results.

5. Continuous knowledge of knowledge: THE Artificial intelligence maintains up -to -date knowledge database and supports relevant long -term information.

Transparent IA integration into existing knowledge management systems is crucial and the most important aspects include friendly dashboards, high security standards and the adaptability of AI models to specific needs.

Wisdom too, the Knowledge management software By Zehnplus, for example, used independently without support in AI. But by connecting the elements of AI, it makes it possible to form the system specifically to the data of the company.

The integration of AI into knowledge management gives each company an advantage because it promotes both efficiency and cooperation and allows knowledge to accumulate in the long -term business. As a current study shows, many German companies are already counting on AI to implement these advantages. Here it works For statistics. The field of natural language treatment is particularly interesting here. Because if AI systems include natural language, users can interact much more easily with AI.

In addition, AI creates new perspectives on existing knowledge and helps recognize gaps in knowledge at an early stage. It optimizes not only internal processes, but also increases progress by allowing teams to access current information and to use it in a creative manner.