How Agentic AI Can Put Your Company’s Intellectual Property at Risk

Agentic AI can put your company’s intellectual property at risk, according to a Shumaker blog. It promises to transform business operations by automating complex workflows with autonomous digital “agents.” However, these agents prioritize task completion over data protection. In doing so, they create hidden pathways for confidential information and intellectual property to leak across agents, memories, and integrations.

Unlike traditional generative AI, which responds to prompts, agentic AI breaks down broad goals into subtasks and executes them independently, often in collaboration with other agents. This autonomy, while powerful, leads to risky behaviors such as “context dumps,” where agents overshare full documents or communication histories, and “fuzzy retrieval,” where memory searches pull in irrelevant but sensitive materials. Additional vulnerabilities emerge from overly broad system permissions, shared memory with weak boundaries, and misconfigured multi-tenant systems. Altogether, these patterns turn leakage from a rare mishap into a default behavior.

The legal implications are serious. Data spills can undermine trade secret protection by demonstrating a failure to maintain secrecy, jeopardize patent rights through unintended public disclosure, and raise concerns regarding copyright ownership and infringement. Even trademarks are at risk when AI-generated content creates confusion or erodes their distinctiveness.

To counter these threats, legal and compliance professionals must adopt “security-by-default” design principles. Each agent should operate on the principle of least privilege, exchanging only what’s necessary through structured data wrappers. Memory should be segregated by sensitivity, ensuring that restricted data never enters general storage. Automate safeguards with policy-as-code, cryptographically sign agent-to-agent messages, and monitor “canary” markers to detect leaks and enforce compliance. Finally, prohibit data training in vendor contracts, require deletion of logs, and ensure traceable compliance. 

The potential of agentic AI is immense, but so are the risks. Only by embedding rigorous data governance into its architecture can organizations protect their intellectual property from risk.