Red Hat Introduces “Policy as Code” to Help Address AI Complexities at Scale

As a capability of Red Hat Ansible Automation Platform, automated policy as code will aim to drive policy-specific automation across the hybrid cloud, bringing governance and greater consistency to the AI boom and traditional IT operations alike


Red Hat, Inc., the world's leading provider of open source solutions, today announced automated policy as code, a new capability coming to future versions of Red Hat Ansible Automation Platform. The capability will help enforce policies and compliance across hybrid cloud estates that increasingly include a varied and growing number of AI applications. Another step in automation maturity, policy as code will make it possible to adhere to changing internal or external requirements and better prepare for sprawling infrastructure in support of scaling AI workloads.


The race to adopt and scale AI workloads in tandem with hybrid cloud creates more complexity and sprawl. Policy as code helps bring order to this sprawl, both current and potential, by enforcing critical compliance standards as AI generated applications and systems arise, making automation a truly strategic component in AI evolution.

Sathish Balakrishnan

Vice President and General Manager, Ansible, Red Hat

According to an IDC perspective1, “despite skill gap challenges and inadequate human resources, IT operations face constant pressure to enhance efficiency and reduce costs. Meeting the demands of continuous innovation and time-to-market objectives of LOBs and accommodating the agile and dynamic needs of DevOps and security teams while ensuring the resilience and reliability of IT services presents a formidable challenge for traditional IT operations teams.”

Red Hat believes that this challenge can grow exponentially as AI scales the capabilities of individual systems and, in turn, moves further beyond what humans alone can manage. Implementing crucial policies across such expansive workloads not only requires extensive time and attention but also cross-functional team collaboration and documentation. Manual processes leave room for human error, and any mistakes can be costly. Applying compliance directives to mission-critical systems before they become AI-centric is vital, given that they are typically the most impacted by compliance mandates that dictate system security, performance and auditability.

AI as a natural progression of IT automation

Laying a foundation of mature automation with operational guardrails enables organizations to prepare a stronger security footprint for AI innovation. Automating policy as code will help customers better position themselves to operate IT in accordance with specific governance, risk and compliance (GRC) requirements. It will help align technical environments and resources to agreed standards whenever — before the automation is executed or live as components become out of policy – and repeat wherever, extending control at scale across the hybrid cloud and keeping potential AI sprawl within predetermined limits.

Red Hat is making it easier to create and manage across the pre- and post-AI workload lifecycle, at scale across global operations and through automated audit reporting that helps free up technology teams. Automated policy as code will build the greater consistency of control needed for IT teams to have the confidence to invest in new technology by providing a layer of protection built into operations. With these programmatic guardrails, there are more assurances that AI is building on what’s already approved by the organization to deliver real business value.

The gold standard for enterprise IT automation

Ansible Automation Platform is the industry-leading, end-to-end automation platform. It delivers a constant stream of innovation to free up IT teams with new features like Red Hat Ansible Lightspeed to bridge skills gaps and Event-Driven Ansible for an always-on tool. 

If teams are using an AI service—like Red Hat Ansible Lightspeed—to accelerate automation development, policy as code capabilities could be applied while creating automation content and governance can be infused into the learning model from the start. This will enable content creators to write code that automatically maintains mandated compliance requirements, greatly reducing the impact of skills gaps and human error in IT operations. 


The tech preview of automated policy as code for Ansible Automation Platform is slated for availability in the coming months. Customers and partners can join advocacy groups where they can offer input, share and learn best practices. Partners can also get started on integration discussions, so recommended best practices can become automatically enforceable and/or included in service offerings.

The cloud is hybrid. So is AI.

For more than 30 years, open source technologies have paired rapid innovation with greatly reduced IT costs and lowered barriers to innovation. Red Hat has been leading this charge for nearly as long, from delivering open enterprise Linux platforms with RHEL in the early 2000s to driving containers and Kubernetes as the foundation for open hybrid cloud and cloud-native computing with Red Hat OpenShift.

This drive continues with Red Hat powering AI/ML strategies across the open hybrid cloud, enabling AI workloads to run where data lives, whether in the datacenter, multiple public clouds or at the edge. More than just the workloads, Red Hat’s vision for AI brings model training and tuning down this same path to better address limitations around data sovereignty, compliance and operational integrity.  The consistency delivered by Red Hat’s platforms across these environments, no matter where they run, is crucial in keeping AI innovation flowing.

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Supporting Quotes

Sathish Balakrishnan, vice president and general manager, Ansible, Red Hat

“Automation is a critical component of enterprise IT and AI is a natural progression of automation. It has become clear that AI will be the most transformative technology in our lifetimes. The race to adopt and scale AI workloads in tandem with hybrid cloud creates more complexity and sprawl. Policy as code helps bring order to this sprawl, both current and potential, by enforcing critical compliance standards as AI generated applications and systems arise, making automation a truly strategic component in AI evolution.”

Jim Mercer, program vice president, Software Development, DevOps & DevSecOps, IDC

“Organizations need guardrails to keep AI systems compliant with regulations, while enabling flexibility and innovation. However, a simple and consistent approach is required to enable policies across platforms and teams and ensure scalability. Using policy as code will be key to accomplishing these goals, and standardized templates will help modernize skill sets and make it easier for associates to get on board with new policies.”

Antoine Shagoury, chief technology officer, Kyndryl

“Today, Kyndryl operates one of the largest global implementations of Ansible Automation Platform in support of our customers’ mission-critical operations. With the rising demands of integrated automation due to the growing complexity of hybrid IT infrastructures with AI workloads, the effectiveness gains driven by policy as code within Ansible have become a critical capability within Kyndryl’s managed service portfolio.”

Baljinder Kang, director, Enterprise Engineering, NatWest Group

"At NatWest, our goal is to enable application teams to accelerate the delivery of customer solutions by increasing their efficiency through first-class toolchains. Adding policy capability to our automation will allow for increased compliance and adherence to regulation, essential to the banking industry. We think this is necessary as we look to add AI capabilities to continue to enhance our tooling to drive increased value in our solutions to meet our customer needs."

Additional Resources

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    1IDC Perspective: AI in IT Operations: Maximizing Efficiency of the Digital Business, Doc  # US51939724, Mar 2024