Artificial intelligence (AI) is reshaping every industry, but in highly regulated sectors, success isn’t measured only by accuracy but also by trust. Public agencies, healthcare providers, and financial institutions face a common challenge of delivering the benefits of AI while staying compliant with frameworks like FedRAMP, HIPAA, PCI DSS, and NIST 800-53. These standards set the rules for encryption, access control, auditing, and data handling. They also introduce operational constraints that limit where and how AI runs. Red Hat OpenShift AI helps to bridge that divide, allowing organizations to build and deploy protected AI where the data lives, across datacenters, public clouds, and edge environments. Moving the platform to the data Regulatory data often can’t move freely. Privacy laws, jurisdictional boundaries, and internal risk policies typically govern how and where clinical records, payment data, and sensitive telemetry can be used. That immobility of the data gravity challenge is one of the most significant barriers to enterprise AI adoption. OpenShift AI reverses that equation. Instead of relocating data to cloud AI services, OpenShift AI brings the AI platform to the data. Since OpenShift AI runs consistently across on-premises, cloud, and edge environments, organizations can train and serve models near sensitive datasets, maintaining compliance, while using flexible compute resources as they see fit. Every platform layer reinforces this trust boundary: encryption, role-based access control (RBAC), network isolation, and continuous compliance scanning. OpenShift AI lets teams operationalize AI workloads by deploying their model inference and training closer to their data, overcoming data gravity challenges often caused by compliance. Compliance as the foundation for scalable AI Many AI projects never leave the lab because the production environment supporting the solution cannot meet regulatory expectations. Moving models that handle personal health information, financial transactions, or mission data requires an infrastructure that is designed for continuous verification, policy enforcement, and cryptographic assurance as a first class citizen. OpenShift AI provides that foundation. It inherits the proven security posture of Red Hat Enterprise Linux and Red Hat OpenShift, integrating controls that align with multiple compliance frameworks not as isolated checkboxes, but as a unified operational standard for hybrid platforms. - FedRAMP Moderate and High: Consistent encryption, auditing, and identity management across government and contractor environments. - HIPAA: Built-in data segregation, rest and transit encryption, and granular access control for systems processing protected health information. - PCI DSS 4.0: Role-based access enforcement, network segmentation, and continuous monitoring for financial data protection. - NIST 800-53 / ISO 27001: A comprehensive control framework for system integrity, configuration management, and continuous assessment. Zero trust by design Modern AI systems can’t rely on perimeter security. Data flows across clusters, pipelines span clouds, and inference requests may originate anywhere. OpenShift AI is built on zero-trust architecture principles, assuming no implicit trust between users, workloads, storage, and networks. - Strong identity everywhere: Each API, pod, and service can be operated with verifiable credentials enforced through service accounts and federated enterprise identity systems when enabled. - Policy-driven access: RBAC and security context constraints enforce least privilege, and NetworkPolicies and AdminNetworkPolicy enforce microsegmentation between namespaces and services. - Encrypted communication: Mutual TLS across the control plane and service mesh protects every connection when enabled. - Continuous validation: Consistently checking configurations and workloads against approved baselines, leveraging Red Hat Advanced Cluster Security for Kubernetes and the Compliance Operator. Zero trust transforms compliance from a static document into an active operational discipline that verifies every interaction, every time. End-to-end security capabilities across the stack Each layer of OpenShift AI contributes to robust regulatory alignment, a crucial aspect for organizations operating in scrutinized industries. This comprehensive alignment helps verify that all components, from infrastructure to application, adhere to necessary compliance standards. By building upon this foundation, organizations can more confidently deploy AI solutions while mitigating regulatory risks. - Operating system layer: Red Hat Enterprise Linux CoreOS provides immutability, SELinux enforcement, and encryption services that satisfy system hardening requirements under FedRAMP, DISA STIG, and CIS Benchmarks. - Platform layer: Red Hat OpenShift provides configuration defaults, isolated namespaces, encrypted etcd storage, and policy-based deployment controls aligned with NIST 800-53 and PCI DSS. - Application layer: AI pipelines and model services inherit these protections, enabling protected hand-offs between data ingestion, training, and inference. - Data layer: Red Hat OpenShift Data Foundation provides encrypted persistent volumes and integrates with enterprise key management systems to meet HIPAA and PCI data-at-rest requirements. This layered approach helps bring every component, from the node OS to the AI model API, in line with compliance enforcement. Continuous compliance and governance Audits used to happen once a year. In AI environments, they must happen continuously. OpenShift AI automates that process throughout: - Compliance Operator: Continuously scans cluster configurations against benchmarks like FedRAMP, PCI DSS, and CIS Kubernetes. - Red Hat Advanced Cluster Security: Monitors for runtime deviations, unpatched vulnerabilities, or unauthorized privileges in AI workloads. - Red Hat Advanced Cluster Management for Kubernetes: This type of management applies and enforces consistent policies across multicluster or hybrid environments, so compliance follows workloads wherever they run. Together, these tools turn compliance from a reactive event into a continuous validation cycle, reducing audit overhead while improving security posture. Protecting the AI software supply chain AI doesn’t exist in isolation. Models, libraries, and pipelines depend on vast open source and industry ecosystems. Red Hat Trusted Software Supply Chain integrates with OpenShift AI to bring greater transparency and traceability to those components: - Red Hat Trusted Artifact Signer: Cryptographically signs and verifies container and model artifacts. - Red Hat Trusted Profile Analyzer: Provides insights into vulnerabilities and license risks across AI components. - Red Hat Quay: Scans and stores signed images with full provenance history. - Red Hat Advanced Cluster Security Policy Enforcement: Enforces robust security policies to help prevent the deployment of unsigned or non-compliant artifacts so only trusted and verified components are integrated into the system. This helps mitigate unauthorized or tampered software risks. These capabilities align with NIST 800-218 (Secure Software Development Framework) and the U.S. Executive Order 14028, giving organizations an auditable chain of custody for their AI assets. Hybrid cloud consistency and compliance, built with choice in mind OpenShift AI’s architecture maintains policy parity across environments, so the same compliance and security controls apply whether workloads run in a private data center, on a certified public cloud like AWS GovCloud or Azure Government, or on edge devices in a disconnected operating model. This consistency significantly reduces duplicated certification efforts and simplifies compliance reporting. Organizations can scale AI workloads globally while maintaining a single, verifiable compliance baseline, enabling distributed training, cross-region inference, and federated learning within the same operational framework. How compliance enables AI innovation Compliance frameworks are often seen as barriers, but they help make hybrid AI innovation possible. They provide the rules of trust, encryption standards, audit requirements, and access controls that allow organizations to process sensitive data confidently. By meeting and exceeding these standards, OpenShift AI becomes more than a container platform for AI—it’s a compliance-ready foundation for innovation. FIPS validation, FedRAMP alignment, HIPAA safeguards, and PCI DSS controls all work together so AI systems remain protected, verifiable, and auditable throughout their lifecycle. Trust is the currency of AI in the hybrid cloud Red Hat OpenShift AI combines decades of open source security expertise with the compliance frameworks governing today’s regulated industries. Its zero-trust architecture, multistandard compliance alignment, and consistent hybrid deployment model allow organizations to overcome data gravity and bring AI to where it delivers the most value. 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