Companies with the best customer experience focus on the mindset of consistency, clarity and continuous improvement. Most enterprise AI initiatives fail because technology doesn't work, rather than addressing real issues, rather because companies chase widespread or uncertain use cases. For example, many organizations are building chatbots that are surprised by the demo, but actually annoys users.
Liz Sentoni, Cisco's top customer experience officer, speaks at Cisco Live 2025
When Liz Sentoni, Cisco's top customer experience officer, talks about solving “boring problems,” she's not too reserved. She highlights the fundamental truths about artificial intelligence that most companies miss. While the world of technology is obsessed with flashy AI demos and theoretical capabilities, Cisco has quietly built practical, measurable AI use cases that make it easier for enterprise customers to use Cisco environments.
“We solve the most boring problems that can help our customers' production environments. We're thinking about the issues that everyone has been around for years,” explained Sentoni in an industry analyst breakout at the Cisco Live Conference in San Diego. What are some examples of these “boring” problems? Configuration errors that cause 25% of all support cases. Network experts spend up to 50% of their time on manual tasks, minimizing security breaches caused by human error.
The results speak volume. Cisco has seen a 22-25% decline in low-radical support cases, down 10% year-on-year. Additionally, the AI-powered update process reduces the time spent by customer success teams collecting data from 40% to less than 5%, freeing them to focus on real customer relationships.
By addressing the low outcomes of basic support issues, Cisco can enhance its sales process while focusing its support team time on more complex issues.
Three pillars of AI-driven customer experience
During the keynote speech at Cisco Live, Centoni shared that Cisco's customer experience strategy is concentrated in three core areas where each company can adapt to customer experience challenges.
1. Resilience: Prevent problems before they occur with AI
The most specific impact comes from what Cisco calls “services as code.” Integrate AI-powered tests into your deployment pipeline to catch configuration errors before they stop. “We can imagine a future that moves from a disruption to a reliability of the composition,” explained Centoni.
This is not just about finding defects. The system proactively validates the configuration for established best practices and operational requirements specific to each customer's environment. One customer who took this approach summed up the value, “We provided security, resilience, consistency – all three.”
Wideer lesson: The value of AI is often in preventing human error, which causes the most expensive problems, rather than replacing human decision-making.
2. Simplicity: Creating a unified, intelligent interface
Cisco has realized that the customer is owning with multiple interfaces and disconnected tools. Like many large technology vendors, Cisco aims to simplify the customer experience (CX) by providing a unified, AI-powered interface that provides a “ultra-personal view of the entire Cisco environment,” as explained by Centoni.
This interface not only aggregates information, but also understands the context. You can identify which devices are approaching end of support, propose remediation scripts for security vulnerabilities, and even generate compliance reports tailored to specific regulatory requirements.
Key Insights: The true power of AI in simplification is not to hide complexity, but to make complex information viable and relevant to each user's specific context.
3. Time to Value: Personalize your journey to success
Personalization is not a new concept, but it has proven elusive in both consumer and B2B sales. Cisco has created what is called “adoption agents,” which digitizes customer intent and creates personalized onboarding journeys. Rather than providing a standard set of features, the system aligns adoption with each customer's specific goals and key performance indicators (KPIs).
“We are digitizing our customers' intentions, KPIs and results, and since then we are helping to adopt features that are relevant to that intention, not just a standard feature set,” Centoni explained.
Decomposition of data silos was an important theme in most technology vendor presentations this spring at the Technology Conference circuit. Cisco also demonstrated how AI can help connect and analyze data from a variety of sources. This strategy represents the transition from product-centric to results-centric customer success thanks to the ability of AI to process and connect a variety of data sources.
Agent AI role: From tools to teammates
In 2025, you will not be able to complete a technology meeting without sharing the vision of Agent AI. Cisco was no exception. There is still debate over the definition of agent AI, but most technology companies still have some debate as a system of AI agents designed to act autonomously, make decisions, and take action to achieve goals with limited human surveillance. The concept of agent AI is empowering and frightening to organisations who want to enjoy agent productivity but need to minimize the risk of fully autonomous workflows.
At the analyst meeting at Cisco Live, Centoni shared a balanced approach to moving to Agent AI. She said, “We want the team to think of it as an augmentation.” Sentoni emphasized. “Instead of helping an intern to do the job, I would like to be in a space where everyone on my team can spin up agents and help with tasks.”
Agent AI agents can act like talented colleagues, understand their context, make informed decisions, and coordinate multiple tasks to achieve their goals. “The way you see it is a way of using traditional AI as a tool. The way you expect to use agent AI is where you become a teammate,” said Carlo Spereira, a Cisco Fellow and Chief Architect at Customer Experience.
This shift from tools to teammates is what the tech industry calls “ambient agents,” an AI system that is triggered by events rather than directly commands. Harrison Chase, CEO of Langchain (a key partner in building these systems), explains in Cisco Live Keynote:
The power of this approach actually becomes clear. Instead of waiting for customers to report a network problem and humans to diagnose it, agents around Cisco can detect the problem in real time, analyze historical data and best practices, and provide personalized recommendations.
While Cisco's increased efficiency is impressive, the actual return on investment exceeds traditional metrics. Centoni noted that customer satisfaction will be consistently improved when solutions are found through AI-enabled methods. AI also changes the nature of Cisco's work itself. “Reducing cognitive load and friction will help my team become more creative about how to solve customer problems,” observed Centoni. “They can use that (extra) time to learn. They can use that time to balance work and life.”
Agent AI offers a critical potential business impact that enables AI not only to enhance existing processes, but also to create whole new ways to create value. When daily tasks are automated, human workers can focus on complex, creative problem solving that promotes true competitive advantage.
AI lessons for all companies
Cisco also offers practical lessons to organizations looking to transform their customer experience with AI.
Start with the pain, not the possibility
Rather than asking, “What can AI do for us?”, Cisco asked, “What problems do customers and employees face every day?” This question has led Cisco to focus on configuration errors, manual tasks, and data silos (early use cases that seem unattractive but can have a high impact quickly).
Designed for enhancement, not replacement
“We think about autonomous things in terms of tasks that reinforce what our teams do,” emphasized Sentoni. This approach often reduces resistance, maintains quality control and provides better results than fully automated systems. Over time, there will be an opportunity to have more autonomous systems. However, Cisco's strategy offers a more practical approach to minimizing today's risks.
Accepting continuous learning
Unlike traditional software that follows a “build, ship, maintain it” cycle, AI systems need continuous improvement. “It builds it and improves the accuracy of it…it's continuous learning,” Sentoni pointed out. Companies need to design their processes for continuous feedback and improvement.
Trust and transparency are prioritized
Cisco maintains human surveillance at key decision points as customer relationships are at stake. “Decisions are by no means up to the agent, in itself. Decisions are up to the human at the end of the day,” explained Sentoni. The balance between AI capabilities and human control builds trust with both employees and customers.
Think beyond efficiency
Cost reduction is important, but the real value lies in enabling new features. Not only can Cisco agents handle support cases faster, they can also predict and prevent issues that could not be caught manually.
The future of AI in customer experience
Cisco's vision extends beyond its current capabilities to what Centoni calls “intelligent expectations.” It is a system that has a very deep understanding of the customer environment and allows customers to resolve problems before they know who they are.
“Our goal is whether it's a customer spending thousands of dollars or a customer spending billions, we know their environment so we want them to feel like they are the only customer.
The vision of a hyper-personalized and predictive customer experience represents the true promise of AI in business. Rather than replacing relationships, it removes friction and adds intelligence to all interactions to make it more meaningful.
