Enterprise AI Privacy and Security Risk Management: Why the Threat Surface Is Expanding Faster Than the Defenses

Enterprise AI adoption has outrun enterprise AI security. Over 55 percent of large enterprises have deployed generative AI in business-critical workflows, but fewer than 30 percent have formalized AI-specific security controls. This article examines five converging threat vectors: prompt injection attacks (up 340 percent year over year and present in 73 percent of audited deployments), data leakage through AI systems connected to internal knowledge bases, shadow AI (now a factor in 43 percent of AI-related security incidents), supply chain attacks through compromised open-source AI libraries (the March 2026 LiteLLM breach exposed 434,000 CI/CD pipelines in 40 minutes), and the new attack surfaces created by agent interoperability protocols like MCP and A2A. It includes a Strategy Playbook for AI threat surface assessment, AI-specific security controls, non-human identity governance, and shadow AI remediation.