What does this research mean for the field?

The AIGATE framework provides an integrated Zero Trust governance architecture that treats agentic AI systems as non-human enterprise identities to manage delegated authority, runtime tool control, and accountability. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To establish a comprehensive Zero Trust governance framework that addresses delegated authority, runtime tool control, and accountability for autonomous AI agents in enterprise systems.

September 10, 2026InformaticsOpen Access

From Service Accounts to Agentic Identities: A Zero Trust Governance Framework for Delegated Authority, Runtime Tool Control, and Accountable Non-Human Actors in Enterprise Cybersecurity

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Authors

MNMohammad Nizamuddin RSRyana Sikder

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Overview

Framework analysis demonstrates an integrated Zero Trust architecture for autonomous AI agents, highlighting enhanced accountability and runtime control in enterprise environments.

Key Points

To establish a comprehensive Zero Trust governance framework that addresses delegated authority, runtime tool control, and accountability for autonomous AI agents in enterprise systems.
Conducted a structured critical synthesis of literature across agentic AI security, machine identity, Zero Trust, runtime enforcement, and AI governance.
Developed the AIGATE framework comprising eight governance layers that map explicit authority and operational controls across the agent lifecycle.
Demonstrated practical implementation concepts using three illustrative operational scenarios spanning security operations centers, DevOps, and finance.
Identified persistent governance gaps in conventional IAM and Zero Trust models regarding dynamic delegated authority, intent tracking, and runtime tool use by autonomous agents.
Formulated the eight-layer AIGATE architecture to enforce intent-bound access, least agency, runtime tool-call control, and continuous human-attributable audit trails.

Cite This Study

Nizamuddin et al. (2026) studied this question.

synapsesocial.com/papers/6aa27ae958559d80afc73ce2 https://doi.org/10.3390/informatics13090146

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September 10, 2026InformaticsOpen Access

From Service Accounts to Agentic Identities: A Zero Trust Governance Framework for Delegated Authority, Runtime Tool Control, and Accountable Non-Human Actors in Enterprise Cybersecurity

View Full Paper

Ask AI

Bookmark

Authors

MNMohammad Nizamuddin RSRyana Sikder

Discussion

Member takes

Overview

Framework analysis demonstrates an integrated Zero Trust architecture for autonomous AI agents, highlighting enhanced accountability and runtime control in enterprise environments.

Key Points

To establish a comprehensive Zero Trust governance framework that addresses delegated authority, runtime tool control, and accountability for autonomous AI agents in enterprise systems.
Conducted a structured critical synthesis of literature across agentic AI security, machine identity, Zero Trust, runtime enforcement, and AI governance.
Developed the AIGATE framework comprising eight governance layers that map explicit authority and operational controls across the agent lifecycle.
Demonstrated practical implementation concepts using three illustrative operational scenarios spanning security operations centers, DevOps, and finance.
Identified persistent governance gaps in conventional IAM and Zero Trust models regarding dynamic delegated authority, intent tracking, and runtime tool use by autonomous agents.
Formulated the eight-layer AIGATE architecture to enforce intent-bound access, least agency, runtime tool-call control, and continuous human-attributable audit trails.

Cite This Study

Nizamuddin et al. (2026) studied this question.

synapsesocial.com/papers/6aa27ae958559d80afc73ce2 https://doi.org/10.3390/informatics13090146

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