The Secret to Consistent Success in Agentic AI

 Agentic AI is more than a technology trend. It comes with the potential to fundamentally transform business processes, enhance decision-making, and unleash innovation potential across all parts of the organization. Therefore, frameworks that enable organizations to successfully implement agentic AI-driven capabilities in a consistently trustworthy and successful manner will ultimately gain significant advantages in the marketplace.

As a result, enterprises have software vendors banging down their doors to talk about agentic AI, AI factories, Model Context Protocol (MCP), and other key technologies that help customers harness the business value of AI. While the promise of agentic AI is real and unparalleled in its potential business impact, at the same time, it comes with several critical risk factors in the areas of compliance, cost, reliability, security, and accuracy. These risk factors are amplified by the fact that most organizations lack the experience and staff skills to successfully plan, architect, implement, and operate AI capabilities that integrate with their existing technology infrastructure without adding significant operational risk and uncertainty.

Red Hat OpenShift AI aims to address these challenges through its extensive approach to enterprise AI workloads. As a key contributor to open-source AI projects including vLLM, llm-d and llama-stack, Red Hat focuses on delivering a combination of innovation and enterprise stability. The platform seeks to deliver fast, flexible, and efficient inferencing across diverse hardware accelerators, AI models, and deployment targets, from on-premises infrastructure to all major public clouds. This flexibility is essential as enterprises navigate the inevitable diversity of AI workloads while maintaining consistent operations across their hybrid environments. This paper will explore how organizations can use their current OpenShift footprint in combination with Red Hat and KPMG LLP’s Agentic AI Architecture framework to benefit from the advantages of agentic AI in a well-governed, secure, and cost-effective manner.