AI foundational knowledge refers to the shared basic understanding of what Artificial Intelligence can achieve, how it works, and where its limitations lie. It enables employees and managers to appropriately classify AI, use it responsibly, and make informed decisions when dealing with AI.
AI foundational knowledge includes a basic understanding of how AI works and arrives at its results. Employees should be able to assess the data basis on which AI operates and why results may be probabilistic. This knowledge is crucial for classifying, questioning, and responsibly utilizing results, without requiring technical detailed knowledge themselves.
Another component is understanding applications. Companies should know in which areas AI can be effectively used today, for example, to automate repetitive tasks, support decision-making, or in knowledge work, and where its use brings little added value. Further information on this can be found in our blog posts “Where does AI offer the greatest added value for companies?” and “Which processes can be automated with AI?”.
AI foundational knowledge also encompasses an awareness of topics such as data protection, information security, bias, transparency, and responsibility. Employees must understand why clear rules, approvals, and governance are necessary – especially when using customized AI agents that are deeply integrated into processes.
Finally, the role perspective is also part of foundational knowledge: What does AI specifically mean for my work? Which tasks change, and which responsibilities remain with humans? These questions are closely linked to change management and help reduce uncertainties.
AI foundational knowledge thus creates a common language within the company. It forms the basis for further training, effective AI implementation & project management, and the sustainable integration of AI into daily work.
