The growing risks of Agentic AI
As artificial intelligence (AI) solutions continue to evolve, the rise of Agentic AI—intelligent systems that can act autonomously on behalf of an organization—presents new security challenges.
Research from Delinea's 2025 AI in Identity Security: Demands a New Playbook report reveals that 66% of organizations actively use Agentic AI in IT operations, and 56% encounter shadow AI issues at least monthly.
The lack of transparency and visibility in many Agentic AI deployments exacerbates these risks, making it difficult to audit actions and identify underlying security issues. Additionally, the emergence of unmanaged shadow AI systems within organizations introduces another layer of complexity to the already challenging task of securing AI architectures.
3 ways to strengthen Agentic AI security
To effectively manage the risks associated with Agentic AI, leading organizations are seeking to adopt a more granular and dynamic approach to access control. Traditional role-based access control (RBAC) models are no longer sufficient in the age of Agentic AI.
Instead, new control mechanisms that focus on identity-centric security will become the cornerstone of secure AI architectures. Here are three key areas where identity-centric security can help organizations better manage Agentic AI risks:
Implement AI-to-AI credential brokering
AI-to-AI credential brokering leverages AI to automate the machine-to-machine exchange and verifies digital credentials for all AI agents that communicate or act on behalf of the organization. By using token-based credentials or digital certificates, organizations can ensure that AI entities are properly authenticated and authorized before engaging in any interactions. This smarter, automated credential exchange is crucial for maintaining secure AI-to-AI communications.
Develop a visual digital identity mapping
As the demand for governance in Agentic AI grows, Chief Information Security Officers (CISOs) must find ways to make authorization relationships understandable and auditable. Visual mapping of digital identities, including AI personas, agent IDs, and training model metadata, will become increasingly important. By clearly distinguishing between human and AI identities, organizations can better manage and control access to sensitive resources and data.
Strengthen Privileged Access Management (PAM)
Organizations must strengthen their PAM models to effectively monitor and control Agentic AI systems. By leveraging PAM, organizations can detect anomalies, such as privilege abuse or unusual access patterns, that may indicate agent compromise or failure. For sensitive or high-impact operations, PAM can also be used to require real-time human approval before an agent can proceed with high-risk behavior, adding an extra layer of security.
A 5-step roadmap for managing Agentic AI risks
To help organizations get started with managing Agentic AI risks, here is a five-step roadmap that can be implemented today:
- Discover and classify AI identities: Utilize automated tools to inventory AI agents across hybrid and multi-cloud environments, and then classify these identities based on their sensitivity, privileges, and business impact.
- Define roles and guardrails: Set clear operational boundaries for each AI identity classification. Use policy-based access to tie privileges to specific tasks, aligned with business intent and risk tolerance.
- Enforce least privilege, just-in-time access: Replace standing privileges with just-in-time access that grants AI agents only the permissions needed, when they are needed.
- Authenticate and authorize by intent: Require strong, verifiable identities for AI-to-system and AI-to-AI interactions. Validate intent, ensuring that actions match approved use cases.
- Monitor, detect, and continuously improve: Continuously monitor AI behavior to detect anomalies and misuse. Log AI agent actions with cryptographic integrity, enforce encryption, and regularly test workflows to harden identity and access controls.
Secure the future of AI with Delinea
As Agentic AI becomes more prevalent, CISOs must adapt their security strategies to manage the unique risks associated with these intelligent systems. By adopting an identity-centric approach to security, organizations can better protect their AI architectures and ensure secure AI-to-AI interactions.
Delinea offers a comprehensive, cloud-native Identity Security platform with market-leading PAM capabilities that can help CISOs and their teams implement the necessary controls to secure Agentic AI and safeguard the future of their organizations.