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Discover how Cisco Customer Experience (CX) leveraged AI-ready infrastructure\u2014including networking, compute, and observability\u2014to secure sensitive data, control costs, and maximize ROI on agentic AI workloads.\u00a0<\/em><\/p>\n AI isn\u2019t just moving; it\u2019s sprinting.<\/p>\n By strategically leveraging AI, we create proactive, personalized, and predictive customer experiences that enhance satisfaction and loyalty \u2014 without sacrificing security or budget. As capabilities rapidly evolve, Cisco CX is transforming a critical part of its backend infrastructure to support advanced AI workloads. <\/span>\u00a0<\/span><\/p>\n Although cloud platforms excel at flexibility and speed, they introduce some data sovereignty challenges and consumption-based cost volatility. For AI workloads processing sensitive customer information, we decided that trade-off was untenable.<\/span>\u00a0<\/span><\/p>\n Security: <\/span><\/b>Cloud environments may distribute data across multiple networks and even geographically disperse locations, with access controls through distinct third parties \u2014 expanding the attack surface in an intensifying threat landscape. On-premises deployment eliminates these intermediaries. Cisco infrastructure met our data sovereignty needs, fuses security across every layer of the stack, and reduces exposure to distributed threats.<\/span>\u00a0<\/span><\/p>\n \u00a0<\/span>Cost: <\/span><\/b>On-premises deployment also grants greater control over operational expenses. In the cloud, AI use cases with unpredictable inferencing demands cause token costs to skyrocket. For example, a chatbot handling customer inquiries may process 10 million tokens during peak season but only 2 million during off-peak periods \u2014 resulting in 5x cost variance month-to-month. This unpredictability makes budgeting difficult and compounds as AI workloads scale. When we process tokens locally, we replace that ingress and egress volatility with cost certainty, converting variable expenses into predictable capital investments.<\/span>\u00a0<\/span><\/p>\n On-premises infrastructure mitigates two critical business risks: data sovereignty loss and budget unpredictability. By <\/span>eliminating<\/span> third-party intermediaries and variable token costs, <\/span>we<\/span> gain<\/span>ed<\/span> both <\/span>digital<\/span> resilience and financial predictability to responsibly scale AI.<\/span><\/span>\u00a0<\/span><\/p>\n Since each AI use case has distinct requirements for data security and computational scale, a rigid \u201cone-size-fits-all\u201d deployment strategy undermined our security and cost objectives. Instead, we guided our decisions using pre-defined criteria for AI use case prioritization, investment, and deployment. The three key objectives were:<\/span>\u00a0<\/span><\/p>\n These objectives shaped where we deployed each workload, either on-premises, in the cloud, or hybrid. Take our Customer Sentiment Analysis Agent as an example. It analyzes signals to drive customer renewals by processing a wide scope of sensitive data from customer adoption journeys, support interactions, and the Cisco install base. Because of its data sensitivity and scale requirements, on-premises deployment was both the secure and cost-effective choice \u2014 allowing us to maintain full control over customer renewal data while avoiding unpredictable token costs during peak analysis periods.\u00a0<\/span>\u00a0<\/span><\/p>\n With the support from this and other agents, Cisco CX had 30% better accessibility to adoption metrics versus<\/span> manual assessments and <\/span>eliminated daily administrative friction up to 40%.<\/span>\u00a0<\/span><\/p>\n To scale AI workloads while maintaining data sovereignty and operational cost predictability, we leveraged the following Cisco components:<\/p>\n By deploying Cisco compute, networking, and observability solutions in tandem with CX agentic capabilities, Cisco CX ensures the end-to-end customer lifecycle remains secure, seamless, and cost-effective. As we continue to scale AI workloads, here\u2019s what we\u2019ve learned:<\/span>\u00a0<\/span><\/p>\n By investing in the right infrastructure and mindset, Cisco CX created space for both our team and customers to innovate and thrive.<\/span>\u00a0<\/span><\/p>\n\u00a0Tackling security and cost challenges<\/strong><\/span><\/h2>\n
Deploying AI workloads flexibly<\/strong><\/h2>\n
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Harnessing Cisco compute and networking<\/strong><\/h2>\n
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Best practices and learnings<\/strong><\/h2>\n
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