The BLANC (Better Language and Contextualized NLP) metric is a novel approach to evaluating AI-generated summaries, focusing on the functional impact rather than lexical overlap with reference texts. It assesses how well a summary improves a language model's understanding of a document by masking certain words and testing the model's ability to fill in the blanks. BLANC offers several benefits, including adaptability across use cases, improved model performance, reference-free assessment, scalability, and objectivity. The metric is particularly useful for industries where AI models need frequent adjustments to keep up with the fast pace of change, such as healthcare, law, and finance. By providing an objective and scalable framework for assessing summaries, BLANC contributes to creating AI systems that are both high-performing and aligned with ethical and practical considerations. However, limitations exist, including challenges with multi-document summaries and potential future developments.