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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

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Research and review articles are invited for publication in January 2026 (Volume 18, Issue 1)

Automating Trust at Scale: Infrastructure-as-Code for Secure and Compliant AI Environments in the U.S.

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  • Automating Trust at Scale: Infrastructure-as-Code for Secure and Compliant AI Environments in the U.S.

Ifeoma Eleweke *

Department of College of Technology and Engineering, Westcliff University, USA.

Research Article

International Journal of Science and Research Archive, 2025, 17(02), 123-137

Article DOI: 10.30574/ijsra.2025.17.2.2962

DOI url: https://doi.org/10.30574/ijsra.2025.17.2.2962

Received on 20 September 2025; revised on 02 November 2025; accepted on 04 November 2025

As artificial intelligence (AI) systems increasingly underpin critical operations across U.S. industries, the ability to automate trust at scale has become both a technical necessity and a national imperative. This paper examines how Infrastructure-as-Code (IaC) can be strategically leveraged to secure AI ecosystems and enforce regulatory compliance across development-to-production processes. The central challenge lies in maintaining continuous compliance within dynamic, rapidly evolving AI environments, where manual configuration is both error-prone and unsustainable. IaC offers a foundational solution by embedding security and policy enforcement directly into system provisioning, transforming infrastructure deployment into an auditable, repeatable, and verifiable process. Empirical evidence consistently shows that human misconfigurations account for most cloud breaches, emphasizing the need for codified automation to minimize risk and ensure integrity. This study demonstrates that IaC enables consistent, immutable environments across AI development, training, and production stages, significantly reducing configuration drift and vulnerability exposure. Moreover, Policy-as-Code frameworks such as Terraform Sentinel and Open Policy Agent allow regulatory standards, including NIST SP 800-53, FedRAMP, and HIPAA, to be expressed as machine-readable rules enforced in real time. Integrating IaC security tools such as tfsec and Checkov, alongside robust secrets management within CI/CD pipelines, yields measurable improvements in compliance auditing and breach prevention. Through a proposed reference framework and real-world case studies spanning U.S. federal agencies and healthcare systems, this article illustrates how IaC can function as a scalable trust mechanism capable of unifying security, compliance, and automation in AI DevOps. Ultimately, embedding IaC into AI infrastructure is not merely a technical optimization; it is a strategic imperative for national cybersecurity resilience and policy assurance in the era of intelligent systems.

Infrastructure-as-Code (IaC); AI Security; Compliance Automation; DevOps; Policy-as-Code; Drift Detection; Continuous Integration and Continuous Delivery/Deployment (CI/CD)

https://journalijsra.com/sites/default/files/fulltext_pdf/IJSRA-2025-2962.pdf

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Ifeoma Eleweke. Automating Trust at Scale: Infrastructure-as-Code for Secure and Compliant AI Environments in the U.S. International Journal of Science and Research Archive, 2025, 17(02), 123-137. Article DOI: https://doi.org/10.30574/ijsra.2025.17.2.2962.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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