Knowledge acquisition is the process of acquiring, processing, understanding, and recalling information through one of a number of methods. It is a key component of machine learning and knowledge-based systems. In the context of expert systems, knowledge acquisition is the process of extracting, structuring, and organizing knowledge from one source, usually human experts, so it can be used. The process of knowledge acquisition typically involves the following steps:

• Evaluating the domain to determine if the type of knowledge in the domain is suitable for an expert system.
• Identifying and evaluating the source of expertise to ensure that the specific level of knowledge required by the project is provided.
• Identifying the specific knowledge acquisition techniques and participants needed.

There are various techniques used in knowledge acquisition, including interviews, observation, and re-use based approach. In interviews, the knowledge engineer asks questions to the expert to elicit knowledge about the domain. In the re-use based approach, knowledge can be developed in ontologies that conform to standards such as the Web Ontology Language (OWL) .

Acquiring knowledge is an essential part of personal and professional development. It involves identifying a need, gathering knowledge (skills), and internalizing that knowledge through practice and application. Knowledge acquisition can be done through various sources such as customers, suppliers, competitors, and partners/alliances.