Fast and Simple AI Deployment on Intel Xeon with Red Hat OpenShift
Red Hat, Monday, February 2nd, 2026
AI adoption and development have accelerated with generative and agentic AI reaching the masses. As new markets emerge, businesses have been struggling to take advantage of AI for real returns on investment.
Although GPUs have dominated the infrastructure, increasing costs and decreasing availability due to demand have prompted leaders to seek alternatives that still meet performance requirements and customer satisfaction standards.
Meanwhile, the developers and engineers working on AI face challenges in complex and time-consuming infrastructure setup and difficulty in building out software stacks and architectures for optimal large language model (LLM) inference with retrieval augmented generation (RAG). Ease of use, security of proprietary data, and even how to get started building AI are technical challenges that may bar developers from entry to AI.