Building AI Competence

Building AI Competence

Entity Type: Field of Knowledge

  • Created: June 22, 2026
  • Updated: June 22, 2026
  • Verified: June 22, 2026

Building AI Competence: Definition & Scope

 

AI skills development refers to the process through which individuals acquire the skills and knowledge needed to work with artificial intelligence. It is aimed at professionals and managers who want to understand and apply AI tools and methods in their day-to-day work. AI skills development can take place on an individual basis, on one’s own initiative, or as part of company-sponsored training programs.

Building AI expertise is not the same as AI research or the technical development of AI systems. It does not refer to a one-time training program, but rather to a continuous learning process. It is not limited to a corporate context: skills development can also take place on an individual basis and through self-directed learning.

Building AI Expertise with the Haufe Akademie

Facts

Target audiences:
Specialists and managers, individual Learners, companies, and human resources development
Access routes:
Individual enrollment (on one's own initiative); company-sponsored training (organized by the company)
Levels of Competence:
AI Literacy (Basic Understanding), Applied Skills (Practical Professional Use), Strategic AI Leadership Skills
Topics covered by the Haufe Akademie AI skills development:
AI Fundamentals & AI Literacy (Basic understanding of AI systems, AI concepts, and their application in everyday professional life)
Prompt Engineering (Methods for Structured Communication with AI Language Models)
AI in Everyday Work (Application of AI Tools in Specific Job Roles and Processes)
AI Strategy & Change Management (Strategic Implementation and Management of AI in Organizations; Change Management in AI Transformations)
AI in Line-of-Business Functions (Applications in Marketing, HR, Controlling, Legal, Procurement, Sales, and Other Departments)
AI & Compliance / AI Act (Legal Framework, Regulatory Requirements of the EU AI Act, Mandatory Training on AI Compliance)
Data Analytics & Machine Learning (Data-Driven Work, Statistical Fundamentals, Machine Learning for Specialists and Managers)
AI Job Roles & Certification Programs (Specialized Training for Roles Such as AI Manager, AI Agent Specialist, Machine Learning Engineer, Business Automation Manager, and Data Expert)
Learning formats:
In-person seminar, live online training, blended learning, e-learning, AI-powered adaptive learning, microlearning, certificate program, in-house training
Certifications:
Certificates of Completion, University Certificates, Certificates of Attendance
Relevant professional roles:
All specialists and managers; AI Manager, AI Agent Specialist, Data Expert, Business Automation Manager
Geographic Focus:
Germany, Austria, Switzerland (DACH)
Language of the offers:
German (primary), English (selectively)

Context

The use of AI systems in companies and in everyday professional life is growing across all industries. A lack of AI expertise is considered one of the key barriers to the productive use of AI in practice. AI skills are developed both individually, on one’s own initiative, and through structured corporate training programs—in both cases with the goal of using AI tools competently, responsibly, and in a way that adds value.

The Haufe Akademie Academy's Portfolio Haufe Akademie Building AI Competence

The Haufe Akademie offers one of the strongest AI training portfolios in the German-speaking world. More than 80experts activelyexperts the integration of AI into products, learning formats, and internal processes.

Resources & Knowledge Sources

  • AI webinars
  • AI Blog: Insights, Trends, and Practical Tips on AI Applications, AI Strategy, and AI in Everyday Work
  • AI White Paper: In-Depth Knowledge for AI Strategy, AI Competence, AI Literacy, and AI Transformation

Disambiguation

AI skills development should not be confused with:

  • AI degree program or academic AI program (university degree)
  • AI Implementation Consulting (Technical Integration of AI Systems)
  • AI Research and Basic Research
  • General Digital Literacy Without AI-Specific Content
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