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PlainID, the Enterprise Authorization Leader and a global provider of Identity Security, introduces Policy Management for Agentic AI. Securing the future with a solution that brings identity-aware, policy-based access control to the next generation of AI systems. To learn more about how PlainID protects enterprise data generated by AI with identity-aware, Policy-based Access Control,
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As organizations rapidly adopt AI and LLM-based systems, they are ingesting and processing vast amounts of sensitive, and high-risk data. Organizations are exposed to:
- Data leaks and compliance violations (e.g., PII, IP, regulated content)
- Regulatory and reputational risks from misused or exposed data
- Inability to ensure auditability and accountability in AI-driven decisions
- Delays in AI adoption due to governance bottlenecks and misalignment between security and engineering teams
“As enterprises accelerate AI initiatives, PlainID empowers teams to govern AI data and decisions without compromising innovation. Through policy management and access enforcement, we ensure every AI interaction is secure, compliant, and policy-aware,” said Gal Helemski, Chief Product Officer and Co-Founder of PlainID. “The principals of zero trust and identity-first security are directly applicable to Agentic AI, and with this solution, we’re making them a reality.”
Policy Management for Agentic AI enables organizations to define granular policies that control what data AI agents can access, how they process it, and which actions they may take—ensuring that every AI-driven workflow abides by corporate and regulatory mandates. Key capabilities include:
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- Identity-aware control – Enforce access based on human and non-human identity (NHI).
- Dynamic, fine-grained policies – Apply adaptable controls to every AI Agent interaction with data, APIs and services.
- Centralized policy management – Manage and govern all policies in one unified, standardized interface.
- Seamless integration – With popular AI platforms and orchestration frameworks
- Zero Trust Alignment – Ensure AI operations align with enterprise security and compliance frameworks, by design.
- Auditability – Gain full visibility into AI decision chains, access attempts, and policy outcomes.
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