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Abstract
In enterprise IT environments, Artificial Intelligence (AI) plays a vital role in driving business decisions, automating operations, and improving efficiency. However, the opaque nature of AI models has raised concerns regarding trust, interpretability, and regulatory compliance. This paper explores the integration of Explainable Artificial Intelligence (XAI) techniques into enterprise systems to ensure that AI decisions can be understood, validated, and audited by stakeholders. We review foundational literature on XAI, propose a layered framework for enterprise integration, and provide evaluation metrics for model explainability.
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