AI Data Security Workshop Overview

This document is a guide that outlines the AI Data Security Workshop conducted by Sentinel. It details the structure and focus of the workshop, emphasizing a policy-first approach rather than a tools-first perspective. The workshop identifies various types of gaps in data security, focusing on five key areas: governance, classification, controls, visibility, and training. Participants learn to prioritize their security gaps based on dependencies, determining which issues must be addressed immediately and which can be postponed. A written report is provided for internal use to assist organizations in understanding their data security challenges. The guide also presents a maturity model to help attendees recognize where to concentrate their efforts first. The objective is to enhance clarity on the multifaceted nature of AI data security challenges and to provide direction for organizations looking to improve their security posture.