Cisco Live 2026 Amsterdam: Day 3 | AgenticOps & AI Infrastructure
CVS Health's network engineering team is transforming its infrastructure to support AI workloads by rearchitecting networks for low latency and high throughput, while addressing staffing and data center challenges through talent investment and colocation facilities.
MAIN POINTS FROM TRANSCRIPT
- CVS Health's network supports 9,000 retail stores, pharmacies, and other services across the U.S.
- AI workloads require rearchitecting networks for low latency, high throughput, and scalability.
- Traditional data centers lacked power for AI workloads, leading to a shift to colocation facilities.
- Building a high-trust, high-performance culture was key to the engineering transformation.
TAKEAWAYS
- AI's value lies in reliable, secure, scalable infrastructure, not just model development.
- Network performance is critical for AI, with data movement often being the bottleneck.
- Rethinking data center strategy is essential for scaling AI workloads efficiently.
- Investing in talent and setting engineering standards are foundational for transformation.