AI Chaos or AI Clarity? The Case for Centers of Excellence

As AI adoption accelerates, many enterprises are facing the same pitfalls we saw in early cloud rollouts: disconnected teams, duplicate stacks, and unpredictable costs. 

This latest article from the Equinix team (Kaladhar Voruganti-Senior Business Technologist & Aaron Delp-Director, AI Technical Solutions) introduces a compelling case for AI Centers of Excellence (CoEs) — not as a buzzword, but as a strategic framework to ensure:

• Centralized governance over AI models, data access, and security
• Infrastructure optimization to avoid redundant clouds and egress fees
• Predictable costs and low-latency performance for AI inference
• Alignment across functional, technical, and business teams

📌 What stood out:  Equinix uniquely supports this model by providing proximity to clouds, data hubs, and private AI clusters — all while respecting global data residency and privacy needs. >> Check out the full blog here

Is your organization centralizing or decentralizing AI initiatives right now?

• What challenges have you seen with shadow AI stacks?
•  Where does your AI run best — cloud?