Abstract This article explores the profound impact of artificial intelligence (AI) on data mapping workflows within the context of personally identifiable information (PII) discovery and classification. Through a comparative analysis of the current market leaders Polygraf AI, Microsoft Azure, Amazon Comprehend, and Google Cloud Platform (GCP), we demonstrate the improvements in accuracy, contextual comprehension, and domain-specific entity recognition that AI has brought to the field of data governance. Through real-case studies and performance benchmarks, we conclude that Polygraf AI's method provides higher accuracy for detecting complex PII types, especially in technical contexts with device IDs, masked strings, and global identification formats. This research illuminates how AI is transforming data compliance practices today and provides fact-based guidance to organizations ready to move their data security practices forward.