AI落地面临三大瓶颈，思科AI创新聚焦智能体时代的安全性

南方都市报03-27

3月26日，在2026上海Cisco Connect大会上，思科发布多项前沿创新，包括Silicon One G300系统、AI感知安全访问服务边缘（SASE），覆盖全产品组合的全新AgenticOps功能以及与英伟达联手打造的思科安全AI工厂（Cisco Secure AI Factory），以帮助企业更从容地大规模部署AI技术。　　智能体时代，拓展基础设施、安全方面的创新能力　　据思科方面介绍...

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(EUR) INC","LU2286300806.USD":"Allianz Cyber Security AT Acc USD"},"translate_title":"AI landing faces three bottlenecks, Cisco AI innovation focuses on security in the age of intelligent agents","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"AIPO":1.5,"AGIX":1.5,"CHAT":1.5,"CSCS":0.6,"CSCO":1.5,"CSCL":0.6},"content_text":"3月26日，在2026上海Cisco Connect大会上，思科发布多项前沿创新，包括Silicon One G300系统、AI感知安全访问服务边缘（SASE），覆盖全产品组合的全新AgenticOps功能以及与英伟达联手打造的思科安全AI工厂（Cisco Secure AI Factory），以帮助企业更从容地大规模部署AI技术。　　智能体时代，拓展基础设施、安全方面的创新能力　　据思科方面介绍，当前，在中国，其创新已推动制造、医疗、金融服务等多个行业加速部署AI。而为了支持AI发展的下一阶段——即智能体时代，在这一阶段中，自主AI智能体能够在数字系统中互动、推理并执行操作，思科正持续在基础设施、安全和AgenticOps方面扩展创新能力。　　其中，全新的AgenticOps功能覆盖整个产品组合，能够自动化、规模化并简化AI时代的IT 运维。基础设施方面，思科则发布了Silicon One G300。据介绍，这款102.4 Tbps的交换芯片将帮助客户大规模扩展AI集群部署，G300配备智能集群网络，相比未优化流量，网络利用率提升33%，任务完成时间缩短28%，为AI工作负载提供更快、更高效的处理能力。　　安全方面，思科方面提到，随着企业从AI助手迈向在混合环境中调用工具与数据的自主智能体，安全团队需要强化针对智能体的防护能力，而思科对其安全访问服务边缘（SASE）进行升级，以实现对智能体交互的治理并保障AI流量的稳定性。　　思科AI感知安全访问服务边缘（Cisco AI-Aware SASE）引入了意图感知检测与AI流量优化能力，可对智能体与工具之间的通信进行治理，并在负载高峰期间保障性能稳定。通过在SD-WAN与SSE之间实现统一策略执行，并提供对基于MCP交互的深度可视化，企业能够保护AI应用全生命周期、确保数据安全及AI在大规模应用中的合规与可靠使用。　　“小龙虾”引安全热议，如何突破AI落地三大瓶颈？　　在媒体交流会上，谈及在前述三个方面展开布局的具体思考，思科大中华区资深副总裁兼首席技术官侯胜利说道，“从ChatGPT到DeepSeek，再到今年的‘小龙虾’，AI越来越多地应用到生产、工作和日常生活当中，智能体应用在今年会有大的爆发。而在AI落地过程中，我们看到了基础设施约束、信任赤字和数据缺口三大瓶颈。”　　基础设施方面，侯胜利强调了电力、算力与带宽的问题。而什么是信任赤字？侯胜利解释称，“现在的企业客户超过80%已经开始试用AI，但其中只有5%真的把它大规模投入到生产和应用环节中去，这就是因为信任赤字，信任和安全是当中主要的障碍和挑战。”近期，业内围绕“养龙虾”热潮下安全性问题的讨论也甚嚣尘上，安全成为决定AI相关应用能否规模化落地的关键变量。　　思科全球副总裁兼大中华区首席执行官黄志明也在交流中强调，“现在AI的应用跟传统的应用升级服务是不一样的，无论是在算力、能源、网络架构上，还是在数据连接方面。另外，安全也很重要，我觉得这是未来应用普及的一大瓶颈，因为现在很多企业还不重视，真正用起来发现不够安全，很多法规不完整。”　　另外，在数据方面，侯胜利分享道，“之前大家都认为互联网上有无穷无尽的数据，但实际上数据是有限的，很多专有数据或企业自己的数据是封闭的，互联网上无法搜索到。最近这几年，AI几乎已经把网上开源的、免费的数据用完了，所以现在训练大模型会大量使用合成数据。” 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