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) ā 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
š What stood out: Equinix uniquely supports this model by providing proximity to clouds, data hubs, and private AI clusters ā 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 ā cloud?
Updated 3 months ago
Version 1.0