Data governance is a set of processes, policies and procedures that ensure the availability, integrity, quality, security and confidentiality of an organization's data. The goal of data governance is to ensure that data is managed effectively and efficiently so that it can be used to make informed business decisions and to meet legal and regulatory obligations.

In the context of artificial intelligence and machine learning, data governance is essential to ensure the quality of the data used in machine learning models. Machine learning models can only be as good as the data they are trained on, so it is important that the data is accurate, complete and representative of the population being analyzed. In addition, data governance can also help ensure that machine learning models are fair and ethical.

Data governance involves different parts of the organization, including technology, compliance, audit, privacy and security teams. Data governance responsibilities include defining data policies and standards, managing metadata, creating and maintaining a data catalog, defining roles and responsibilities, managing risk, and monitoring data quality.