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INS3705 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 - DUE August 2024 ; 100% TRUSTED Complete, trusted solutions and explanations. R46,82   Add to cart

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INS3705 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 - DUE August 2024 ; 100% TRUSTED Complete, trusted solutions and explanations.

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INS3705 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 - DUE August 2024 ; 100% TRUSTED Complete, trusted solutions and explanations.

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  • July 9, 2024
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  • 2023/2024
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INS3705 Assignment
2 (COMPLETE
ANSWERS) Semester 2
2024 - DUE August
2024 ; 100% TRUSTED
Complete, trusted
solutions and
explanations.




ADMIN
[COMPANY NAME]

,QUESTION 1 Identify four knowledge management processes in
any organisation of your choice and discuss the purpose of each
knowledge management process and two examples of artificial
intelligent technologies that can be used in each of the knowledge
management processes (mini essay). [10) QUESTION 2 A senior
employee with valuable tacit knowledge is retiring in your
organisation. Define tacit knowledge and suggest five methods or
tools that you would use to enhance knowledge retention and
prevent knowledge loss (mini essay). [10]


To address these questions effectively, let's break down each part
into mini essays:
Question 1: Knowledge Management Processes and AI
Technologies
Knowledge management (KM) processes are crucial for
organizations to capture, store, share, and utilize knowledge
effectively. Here are four key KM processes, their purposes, and
examples of AI technologies that can support them:
1. Knowledge Creation and Acquisition:
o Purpose: To generate new knowledge and insights within
the organization.
o AI Examples:
▪ Natural Language Processing (NLP): Used for
analyzing customer feedback, internal documents,
and market trends to generate new insights.
▪ Machine Learning Algorithms: Assist in data
mining and pattern recognition to identify new
knowledge patterns from large datasets.
2. Knowledge Storage and Organization:

, o Purpose: To store and categorize knowledge for easy
retrieval and use.
o AI Examples:
▪ Knowledge Graphs: Utilized to map relationships
between different pieces of knowledge within the
organization.
▪ Document Management Systems: AI-powered
systems that tag, classify, and retrieve documents
based on content analysis.
3. Knowledge Sharing and Collaboration:
o Purpose: Facilitate the exchange of knowledge among
employees and teams.
o AI Examples:
▪ Collaborative Filtering Algorithms: Recommend
relevant knowledge and experts based on user
preferences and past interactions.
▪ Chatbots and Virtual Assistants: Provide instant
access to knowledge by answering queries and
guiding employees through knowledge repositories.
4. Knowledge Utilization and Application:
o Purpose: Ensure that knowledge is applied effectively to
improve decision-making and innovation.
o AI Examples:
▪ Predictive Analytics: Forecast future trends and
outcomes based on historical data and knowledge
inputs.
▪ Decision Support Systems (DSS): AI-driven
systems that analyze complex data to provide
recommendations for strategic decisions.
Question 2: Tacit Knowledge Retention Strategies

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