As enterprises increasingly adopt agentic artificial intelligence (AI) to automate complex processes, traditional security methods are proving inadequate. Agentic AI refers to autonomous systems capable of pursuing complex goals with minimal human intervention , making decisions based on continuous learning and external data. This autonomy, which makes them so powerful, also introduces significant security risks.
Conventional identity and access management (IAM) systems rely on action-based permissions, which define what operations a user or system can perform. This model works well for humans or deterministic bots but is not enough for AI agents . Administrators often grant overly broad access to avoid breaking workflows, which introduces vulnerabilities. Common issues include overprivileged access, a lack of approval workflows, and insufficient guardrails . A compromised AI agent could become a powerful tool in the hands of a malicious actor, capable of exfiltrating data or causing widespread disruption.
This is where intent-based permissions come in. Instead of focusing only on 'what' an agent can do, they examine the 'why' behind the action . This model evaluates the purpose of an action before granting access. For example, an AI agent might be allowed to access customer PII if the intent is resolving a support ticket, but blocked from the same access if the task is training a model . This approach introduces semantic awareness into access management, mapping actions to business goals.
Implementing intent-based permissions extends the principles of zero trust and least privilege into the age of AI. The principle of least privilege dictates that an agent should be granted only the minimum level of access required to perform its designated function . Intent-based permissions achieve this by dynamically granting access only when actions align with approved business objectives. Transitioning to a hybrid IAM model, which combines tighter action-based controls with intent-aware policy engines, is crucial . This involves auditing AI agents, integrating context-aware policy engines, and moving toward unified identity frameworks.
As agentic AI continues to evolve, adopting an intent-based security framework is not just a best practice but a necessity. It allows enterprises to innovate safely, ensuring autonomous systems operate within defined boundaries that align with business purposes . By doing so, organizations can harness the incredible power of agentic AI while minimizing its inherent risks.