What is the main focus of the Auditing feature within the Einstein Trust Layer?

The main focus of the Auditing feature within the Einstein Trust Layer is to provide insight into AI decision-making processes. This feature is crucial as it helps organizations understand how AI models arrive at specific conclusions or recommendations by analyzing the decisions made by the AI. Transparency in AI decision-making is vital, especially in scenarios where decisions significantly impact users or business operations. By auditing the AI processes, stakeholders can ensure that the AI's reasoning aligns with ethical standards and regulatory compliance, fostering trust and accountability in AI systems.

The other options address different aspects of data management and security but do not align with the primary objective of auditing in the context of the Einstein Trust Layer. Enhanced data storage capacity pertains to infrastructure capabilities, increased speed of AI processing deals with performance optimization, and preventing unauthorized access focuses on security measures. Each of these functions is important, but they do not capture the essence of what the auditing feature aims to achieve in relation to AI decision-making transparency.