AI in Knowledge Management Training – Structuring Knowledge, Making It Accessible, and Utilizing It Sustainably
Upon request
1–2 days
Munich, Online, or In-House
Upon request
German or English
Digital Certificate of Participation
Artificial intelligence for improved information flow, faster research, and strategic knowledge management. In companies, knowledge is often scattered across documents, emails, filing systems, and disparate systems. This makes relevant information difficult to find, leads to knowledge loss, and causes employees to spend a great deal of time on research and data preparation. Artificial intelligence opens up new possibilities for structuring knowledge, identifying connections, and making information available more quickly for day-to-day work.
Our AI in Knowledge Management training course shows you how to use Claude, ChatGPT, Microsoft Copilot, and other AI tools specifically for knowledge generation, documentation, research, and collaboration. You’ll learn to analyze existing knowledge bases, develop appropriate AI use cases, and build a realistic strategy for AI-supported knowledge management. The focus is on data quality, information security, governance, and the sustainable integration of these practices into everyday business operations.
Content and Structure of the AI in Knowledge Management Training Course
This continuing education program combines the fundamentals of knowledge management with strategic, technological, and organizational issues related to artificial intelligence. All modules can be combined freely.
- Fundamentals of Modern Knowledge Management and Its Processes
- Integrating Knowledge Generation, Structuring, Preservation, and Utilization
- Introduction to AI, Generative AI, Machine Learning, and NLP
- Opportunities, Limitations, and Strategic Importance of AI in the Context of Knowledge
- Distinction from Traditional Knowledge Management and Search Systems
- Success Factors for Sustainable AI Implementation
Result
: A shared understanding of the potential and strategic importance of AI in knowledge management.
- The Importance of Data Quality, Availability, and Consistent Knowledge Structures
- Working with structured and unstructured information, such as documents and emails
- Identify shadow data, knowledge gaps, and redundant data
- Fundamentals of Knowledge Extraction, Indexing, and Semantic Search
- Identify and Evaluate Relevant AI Use Cases
- Knowledge chatbots, AI assistants, automatic summarization, and classification
- Fundamentals of Prompting for Knowledge Applications
- Exercises Using Selected AI Tools
Results: Transparency regarding the organization’s knowledge base and prioritized AI use cases for knowledge management.
- Develop a Strategy for AI-Driven Knowledge Management
- Compare Cloud, On-Premises, and Open-Source Solutions
- Making Make-or-Buy Decisions and Evaluating Suppliers
- Integrating AI into existing systems, processes, and work practices
- Fundamentals of Automation, Interfaces, and Intelligent Workflows
- Define Roles and Responsibilities
- Shaping Project Management and Collaboration with IT and Business Units
- Develop a roadmap from the vision through the pilot phase to scaling
Result
: A technically and organizationally realistic strategy with a concrete implementation and pilot plan.
- Data Protection, Copyright, Information Security, and Legal Requirements
- Dealing with Bias, Hallucinations, Flawed Sources, and a Lack of Transparency
- Develop access, sharing, and control mechanisms for knowledge resources
- Shaping Change Management, Competency Development, and Acceptance Building
- Quality Assurance and Continuous Improvement of AI-Supported Knowledge Processes
- Define KPIs, such as search quality, usage rate, time savings, and knowledge transfer
- Establish Feedback Loops and User Monitoring
- Develop the Initial Individual Action and Transfer Plan
Result
: Responsible, measurable, and sustainably integrated use of AI in knowledge management.
What You Can Put into Practice Right Away After the AI in Knowledge Management Training
After completing this training, you will be able to use AI in a targeted manner to better organize, make accessible, and further develop knowledge within your company.
- Systematically analyze knowledge bases, documents, and information sources
- Identifying knowledge gaps, hidden data, and redundant information
- Using AI Tools for Research, Summarization, and Knowledge Extraction
- Strategically Evaluating Knowledge Chatbots and AI Assistants
- Prioritize relevant AI use cases and plan initial pilot projects
- Further Developing Information Architectures and Knowledge Structures
- Creating a Roadmap for AI-Powered Knowledge Management
- Measuring Success with Appropriate KPIs and Feedback Loops
- Embedding AI-Supported Knowledge Processes Sustainably Within the Organization
Who is the "AI in Knowledge Management" training course intended for?
This training is intended for:
- Knowledge Managers and Information Management Professionals
- Specialists and managers responsible for knowledge and processes
- IT, Data, and Digital Transformation Leaders
- Project Manager for Transformation and Organizational Development
- Manager of Documentation, Research, and Internal Services
- Companies that want to use knowledge more efficiently and strategically leverage AI
This continuing education program is suitable for both beginners and participants who already have some experience in knowledge management or working with AI tools.
Prerequisites for Participation in the AI in Knowledge Management Training
A basic understanding of knowledge management, information management, or digital work processes is helpful but not required. No prior technical knowledge of artificial intelligence is required.
Custom AI Training for Knowledge Management
- Customized In-House Training for Companies and Teams
- Integration of in-house knowledge bases, systems, and processes
- Evaluation of Specific AI Use Cases from Your Work Environment
- Development of Customized Knowledge Workflows and Pilot Projects
- A combination of a seminar, a workshop, and strategic implementation support
About Us as a Provider of AI Training for Knowledge Management
We are an experienced management consulting firm with deep expertise in digital transformation, knowledge management, and artificial intelligence. Our training programs combine strategic management knowledge with practical applications for information flows, documentation, and collaboration.
We help companies capture knowledge in a structured way, make it more readily accessible, and preserve it for the long term. In doing so, we take into account not only technology and data, but also organizational structure, governance, user acceptance, and actual usage in day-to-day work.
01
02
03
04
05
06
Expertise in AI and Knowledge Management – Your Trainer
Thorsten Müller combines expertise in digital transformation, modern work practices, and artificial intelligence. He clearly explains how companies can use Claude, ChatGPT, Microsoft Copilot, and other AI tools for research, documentation, knowledge management, and collaboration.
AI and Human Resources:
Request a no-obligation
appointment now
- Using AI Specifically for Knowledge Management and Information Processes
- Customized Professional Development for Companies and Teams
- Proven Expertise in AI, Knowledge, and Digital Transformation
- Practical Methods for Research, Knowledge Synthesis, and Sustainable Implementation
TISAX and ISO certification apply only to the Munich location
Your message
TISAX and ISO certification apply only to the Munich location
Discover more continuing education programs, seminars, and training courses
ChatGPT Training: Using AI Professionally in Your Daily Work
Less effort, more impact: By using ChatGPT strategically, you can turn daily routines into real value creation.
ChatGPT and Copilot Training: Save Time in Your Daily Life with AI and Effective Prompt Engineering
In this training session, learn how to use ChatGPT, Copilot, and targeted prompt engineering to efficiently integrate artificial intelligence into your daily work—for greater innovation, value creation, and productivity.
Product Owner Training: Your Guide to Successful Scrum Teams
In this training course, you’ll learn how to fulfill your role as a Product Owner strategically and effectively—for greater clarity, focus, and sustainable success in day-to-day agile project work.
Resilience Seminar for Executives
In this resilience seminar for leaders, learn how to use proven methods and effective routines to strengthen your own resilience and that of your team—for greater confidence, clarity, and stability in challenging leadership situations.
Release Manager Training
In this training, learn how to establish and optimize structured and agile release management processes to ensure faster and more reliable service delivery in your organization.
Requirements Engineering Training: The Key to Successful Projects
In this training course, you’ll learn how to create clearly defined requirements and, as a result, make your projects more efficient, more customer-focused, and less risky—for demonstrable success right from the start.
Resilience Training for Executives, Teams, and Employees: Targeted Strengthening of Resilience
Training: How to Attract, Lead, and Retain Generation Z
Find out here how to apply modern leadership approaches to successfully inspire, attract, and retain young Generation Z talent in your company.
Scrum Basics Training – Agile Fundamentals for Sustainable Business Success
In this course, you’ll learn the basics of agile work using Scrum. You’ll gain practical insights and learn how to effectively use modern project management methods and apply them directly.
FAQ – Frequently Asked Questions About the AI in Knowledge Management Training
AI can search through, summarize, and organize information based on specific criteria more quickly. This makes it easier for employees to find relevant knowledge and reduces the time they spend on manual research. In addition, it can highlight knowledge gaps, connections, and recurring questions.
Depending on the system, documents, emails, presentations, meeting minutes, manuals, and knowledge bases—among other things—can be analyzed. Unstructured information can also be processed and classified using AI. Data quality, access permissions, and data protection must always be taken into account.
The training will cover Claude, ChatGPT, and Microsoft Copilot, among other topics. You’ll also gain an overview of knowledge chatbots, semantic search solutions, and other AI-powered applications. The focus is on selecting the right tools for your knowledge processes and business needs.
A traditional search typically uses keywords and returns relevant documents or lists of results. An AI-powered search can understand contextual questions, combine information from multiple sources, and summarize results. However, the quality depends heavily on the knowledge structure, the database, and the control mechanisms.
Suitable use cases often arise in situations where employees regularly need to search for information, summarize content, or combine knowledge from various sources. During the training, you’ll evaluate potential applications based on their benefits, feasibility, data availability, and risk. This will help you distinguish quick wins from strategic initiatives.
Data protection and security are central components of the training. You will learn which information requires special protection and how to design access and approval policies. In addition, the training covers responsibilities, data sources, and the secure integration of AI tools.
New systems will only be successful if they are easy to understand, easily accessible, and truly helpful in day-to-day work. That is why communication, training, and employee involvement are key components of the implementation process. During the training, you will develop strategies for fostering acceptance, gathering feedback, and ensuring continuous improvement.
Yes. In-house training programs can incorporate existing documentation, knowledge bases, and search processes. This makes it possible to analyze specific knowledge gaps and areas for improvement. Confidential content should only be used in authorized systems or in anonymized form.
Possible metrics include search quality, usage rate, time savings, response quality, and knowledge transfer. Qualitative feedback from users and a reduction in recurring inquiries can also be taken into account. During the training, you will develop appropriate success criteria for your organization.