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1、Copyright 2025 S&P Global.All Rights Reserved.Networking lessons from industry leadersArchitecting AI at scaleMay 2025451 Research Discovery ReportArchitecting AI at scale:Networking| of contentsIntroduction3Methodology3Figure 1:Demographic breakdown of participants3Executive summary4Insight 1:Netwo

2、rking planning should anticipate needs,not just react to current use cases5Figure 2:Functional areas with the most advanced AI/ML use cases6Figure 3:AI application areas in manufacturing,utilities and healthcare/life sciences7Insight 2:Leading organizations leverage diverse infrastructure for AI,and

3、 networking strategies must reflect this8Figure 4:Multicloud orchestration emerging as a critical infrastructure need10Insight 3:Latency,bandwidth and availability shape network strategies for AI frontrunners11Figure 5:Key capabilities of networking/network security infrastructure technology partner

4、s12Insight 4:AI workload management benefits from network segmentation13Figure 6:Effectiveness of infrastructure practices for AI workloads14Implications15Insight 1:Networking planning should anticipate needs,not just react to current use cases.15Insight 2:Leading organizations leverage diverse infr

5、astructure for AI;networking strategies must reflect this.16Insight 3:Latency,bandwidth and availability shape network strategies for AI frontrunners.16Insight 4:AI workload management benefits from network segmentation.16About the author17Architecting AI at scale:Networking| appeal of generative AI

6、 has attracted the interest of executives,who regard it as a transformative technology for enhancing efficiency and securing a competitive edge.Substantial funding and executive endorsement have enabled swift experimentation with AI.The primary challenge now is transitioning from these experimental