Navigating New Complexities in Data Quality

Generative AI is redefining data quality challenges by introducing significant complexities in enterprise applications. Unlike previous methodologies, many applications now operate without human oversight, complicating the maintenance of high data quality. These applications frequently interact directly with customers, increasing stakes and potential impacts. Additionally, the growing presence of unstructured data and natural language in these contexts requires new governance strategies and evaluation techniques, as they are less straightforward to manage compared to traditional data types. Overall, while discussions around data quality have persisted for decades, the advent of Generative AI escalates the complexity compared to historical data practices.