The new AI stack: Choice, control, and production-ready innovation

The new AI stack: Choice, control, and production-ready innovation Decoding the new ecosystem: Insights from Forrester Why Red Hat? Any model, any accelerator, any cloud The power of collaboration: Red Hat and NVIDIA Moving from proof of concept to production Want guidance on other tech challenges? Red Hat AI About the author Ashesh Badani More like this The efficient enterprise: Scaling intelligence with Mixture of Experts Red Hat and NVIDIA collaborate for a more secure foundation for the agent-ready workforce Technically Speaking | Build a production-ready AI toolbox Technically Speaking | Platform engineering for AI agents Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share In the next decade, AI will redraw the map of technology ecosystems. As we traverse what Forrester is calling the "seventh wave" of major technological change—driven by generative and agentic AI—C-suite executives are facing a daunting transition. The difference between falling behind and harnessing this wave of change is your strategy for the AI computing stack. At Red Hat, our mission remains centered on open source principles: Collaboration, transparency, and choice. We believe that for AI to truly deliver on its promise of productivity and business value, it cannot remain a proprietary "black box. " It must be grounded in the same solid engineering principles that made Linux, Kubernetes, and other open source innovations the foundation of the modern enterprise. To help make sense of these changes, I highly recommend reading, and understanding the implications of, the new Forrester report, AI Powers A New Computing Ecosystem. It provides an essential roadmap for this transition. The report highlights how AI chips, models, and agents are dismantling the legacy cloud and software stacks we’ve relied on for years. Forrester identifies 8 distinct categories of providers—from chipmakers to agentic platforms—that are now colliding as they race to shape the future of computing. Understanding these shifting structures, and the pressures and incentives that are emerging, is critical for any leader looking to maximize the value they create with their partners rather than getting distracted by the noise and hype. This requires a fundamental shift in how we approach the AI stack.