As AI use cases grow in scope and number worldwide, unique attack surfaces and threats are also on the rise. Organizations need to implement security measures to manage and secure the use of AI across the enterprise. These should include strong user authentication, a centralized AI governance framework, regular audits to identify unauthorized AI deployments, and more. 

To secure the use of AI, organizations must: 

• Evaluate overall use of AI broadly, including AI systems used internally or via SaaS. This includes specific AI models, data science tools, shared MLOps and data analysis platforms.
• Evaluate the approach to assessing the potential vulnerabilities in AI models and related systems.
• Assess current AI security capabilities, such as data governance, model management, vulnerability management, and red and blue team exercises.
• Identify defenses against AI attacks, such as prompt injection, data poisoning, model theft, adversarial examples, etc.
• Review existing plans for AI and AI security.