AI Security Controls break down barriers for organizations to implement AI at scale, empowering employees and simplifying adoption by addressing critical challenges like data integration, an optimized AI vector store, public and private model flexibility, custom application development, and multi-model chat capabilities.

However, for AI to function effectively, data must be properly formatted, and public AI models like ChatGPT or Gemini pose risks such as data leakage, security vulnerabilities, and unintended consequences. Compounding these concerns is the rise of shadow AI—employees using unauthorized AI tools—which forces organizations to tread carefully, balancing responsible data governance requirements with the need to avoid outright bans on AI technologies. These controls provide a structured, secure path for companies to unlock AI’s full potential while mitigating risks.