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Cisco Live! Cisco Ready to Drive Secure AI-Era Infrastructure
Cisco introduces innovative solutions to speed up AI adoption and transform IT with advanced networks, robust security, enhanced observability, and seamless collaboration, keeping pace with global innovation.
Key Highlights
- Cisco AgenticOps is an AI-driven paradigm for modern IT operations, leveraging AI agents to simplify workflows, enhance automation, and enable proactive, autonomous network and security management across complex, distributed environments.
- Cisco launches advanced devices for campus, branch, and industrial networks, combined with AI-driven unified management, to build modern, flexible, and secure work environments.
- Integration of AI-ready security enhancements into Cisco’s Hybrid Mesh Firewall and Universal Zero Trust Network Access (ZTNA) solutions, facilitating secure agentic AI adoption through the Cisco Security Cloud.
The News
Cisco unveiled new innovations to help companies adapt and transform in the AI era. Enterprises are under pressure to accelerate secure AI adoption and drive value from AI investments. Cisco is transforming datacenters and workplaces to empower organizations to seize future opportunities. Find out more by clicking here to read the press release.
Analyst Take
Cisco deftly leveraged Cisco Live! to demonstrate why it is delivering the secure, AI-optimized infrastructure key to connecting the world and fueling the global economy across the AI epoch. To achieve these strategic objectives, Cisco is prioritizing the portfolio development approach needed to meet the fundamental AI requirements of customers, offering secure, AI-optimized networks and experiences.
Cisco unveiled a comprehensive suite of new products and enhancements to support customers in transitioning to agentic AI, featuring AgenticOps for streamlined operations, AI-optimized workplaces, data centers tailored for AI workloads, robust AI-focused security solutions, unified management tools for AI-driven environments, and a core emphasis on digital resilience to meet the demands of the AI era.
Cisco Aims to Streamline AIOps with AgenticOps
Cisco Agentic OS is an AI-driven platform that orchestrates autonomous AI agents to automate complex enterprise workflows across networking, security, and compute environments. It delivers AI-driven solutions, including Cisco AI Canvas and the Cisco AI Assistant, powered by the Deep Network Model, to simplify IT operations, enhance automation, and enable efficient, real-time collaboration for network and security teams. I see this solution as enabling Cisco to meet the topmost strategic needs of organizations in driving their AI networking strategies. Agentic AI is crucial because it enables systems to autonomously pursue goals, make decisions, and adapt to complex, dynamic environments with minimal human intervention.
By integrating advanced reasoning, planning, and learning capabilities, agentic AI can tackle intricate tasks, such as optimizing supply chains, advancing scientific research, or personalizing healthcare, more efficiently and effectively than traditional AI. Its ability to act proactively and contextually aligns with real-world needs, unlocking transformative potential across industries while addressing challenges like scalability, ethical alignment, and safety to ensure responsible deployment.
As such, Cisco’s AI-powered solutions can streamline IT tasks and enhance automation, featuring Cisco AI Canvas, a generative interface for real-time collaboration between network and security teams, and the Cisco AI Assistant, offering conversational control across Cisco’s portfolio. Central to these capabilities is Cisco’s Deep Network Model, a domain-specific large language model (LLM) trained on Cisco’s extensive knowledge base, including Cisco U. courseware and CCIE materials, enabling AI that deeply understands networks and boosts IT team efficiency.
I believe Cisco that the era of application-based software is giving way to a new paradigm driven by agentic AI ushering in autonomous systems that understand, act, and learn in complex environments, redefining our interaction with technology as trusted collaborators rather than mere tools. Unlike traditional AI, agents stand out with their ability to autonomously complete tasks end-to-end, leveraging LLMs fine-tuned for specific expertise to retain memory and operate with deep contextual understanding. As tens of millions of these agents are poised to transform industries with unprecedented speed and intelligence, their rise introduces challenges in managing and orchestrating this vast ecosystem, necessitating innovative AI solutions, such as Cisco Agentic OS, to ensure operational simplicity and effectively address the complexities of an agentic future.
AI Data Centers Rising
AI data centers are integral to fulfilling agentic AI capabilities because they provide the specialized infrastructure required to support the immense computational, storage, and networking demands of autonomous, decision-making AI systems. From my view, an AI data center is a purpose-built facility equipped with advanced infrastructure, including high-performance GPUs, liquid cooling, and high-speed networking, to efficiently handle the intensive computational demands of AI workloads like machine learning and deep learning.
The AI data center market segment is projected to have tremendous upside. AI data center market size was valued at USD 15.73 billion in 2024. Now the market segment is projected to grow from USD 19.66 billion in 2025 to USD 153.23 billion by 2034, exhibiting a CAGR of 25.6% during the forecast period (according to Polaris Market Research).
Specifically, these data centers, equipped with high-performance GPUs such as NVIDIA’s Blackwell or AMD’s MI350, enable rapid training and low latency inferencing for complex models, such as Open AI’s GPT-4, Meta AI’s Lllama 4, and xAI’s Grok3, which power agentic tasks like real-time decision-making and process automation.
Cisco introduced ongoing advancements in its datacenter compute and network solutions to support agentic AI, emphasizing high network bandwidth, low latency, and power efficiency. To promote AI adoption for enhancing the power grid, Cisco has joined the EPRI Open Power AI Consortium. Furthermore, Cisco is launching new features to enable service providers to deliver and monetize innovative AI services.
I find that Cisco’s data center advancements are integral to optimizing data center scalability and energy efficiency, so they handle massive datasets and multimodal inputs critical for agentic AI’s ability to perceive, reason, and act in dynamic environments. AI data centers integrate advanced hardware, secure cloud architectures, and specialized software stacks to ensure high throughput and resilience, enabling organizations to deploy agentic AI at scale while maintaining security and cost-efficiency.
Security for the AI Epoch
AI security is critical to the success of agentic AI because these autonomous, decision-making systems process vast amounts of sensitive data and operate in dynamic, high-stakes environments, making them prime targets for sophisticated AI-driven cyber threats. Robust security ensures the integrity, confidentiality, and availability of data used by frameworks that ensure agentic AI models can prevent adversarial attacks, data poisoning, or model manipulation that could compromise their ability to perceive, reason, and act effectively. As enterprises increasingly rely on agentic AI for critical tasks such as business process automation and real-time decision-making, vulnerabilities could lead to operational disruptions, financial losses, or breaches of trust.
As enterprises face increasingly complex challenges from a proliferation of applications, a dispersed and mobile workforce, and advanced AI-driven threats, robust security is more vital than ever. From my view, Cisco is launching the enhancements to its Hybrid Mesh Firewall and Universal Zero Trust Network Access (UZTNA) solutions, introducing two new firewalls, the 6100 series and 200 series, with top-tier price performance, and unveiling new features in the Cisco Security Cloud needed to help customers address the security demands of agentic AI.
The core principle of Cisco’s UZTNA architecture is an identity-first security approach, enabling policy enforcement at the individual level for humans, machines, services, and agentic AI, while continuously monitoring behaviors to detect anomalies in near real time and dynamically update policies. By integrating Duo Identity & Access Management (IAM) for authorization, Secure Access for semantic inspection to minimize user prompts, AI Defense to ensure agent actions align with their purpose, and Cisco Identity Intelligence for visibility and monitoring, I discern UZTNA can deliver robust security without hindering agentic AI adoption. As agentic AI becomes increasingly embedded in workflows with human-like autonomy and machine-level speed, Cisco’s UZTNA is the approach required to ensure enterprise visibility and control over identity, authentication, authorization, access, and analytics, regardless of who develops the agents, where they operate, or what resources they require.
A Resilient Digital Core is Essential
Digital resilience at the core is key to the success of agentic AI because these autonomous systems rely on robust, uninterrupted infrastructure to execute complex, real-time decisions in dynamic environments. Agentic AI requires high availability and fault tolerance to process vast datasets, handle multimodal inputs, and deliver low-latency responses for tasks like business automation or cybersecurity.
Without a resilient digital core, encompassing reliable networks, scalable AI data centers, and failover mechanisms, disruptions like outages or latency spikes could impair an AI agent’s ability to reason and act effectively, leading to operational failures or eroded trust. I discern Cisco’s new portfolio capabilities, such as bidirectional integrations between Splunk Observability, Cisco ThousandEyes Assurance, and Cisco Enterprise Networks, which enhance network visibility and performance, ensure the stable infrastructure agentic AI needs to operate and adapt to fluctuating demands.
Furthermore, digital resilience safeguards agentic AI against sophisticated threats and ensures compliance in high-stakes enterprise settings. Agentic AI systems, which often handle sensitive data and make autonomous decisions, are prime targets for AI-driven cyberattacks like data poisoning or model manipulation. I find that a resilient digital core provides robust security to protect data integrity and model reliability. Additionally, resilience enables continuous operation under stress, such as during peak loads or cyber incidents, which is critical for maintaining the trust and scalability of agentic AI deployments. By embedding digital resilience, enterprises can confidently leverage agentic AI to drive innovation while mitigating risks.
Accordingly, Cisco has introduced multiple AI-driven enhancements, such as improved features in Splunk Observability Cloud and Splunk AppDynamics, alongside tighter integrations between Cisco and Splunk solutions. From my viewpoint, these enhancements are essential to providing customers with enhanced visibility into network health and performance. Notable advancements include a two-way integration linking Splunk Observability, Cisco ThousandEyes Assurance, and Cisco Enterprise Networks, fostering more robust, data-driven digital operations.
Workplaces Built for the AI Era
AI-era workplaces require modern network infrastructure that handles increased traffic, ensures constant connectivity, and provides strong security. Organizations must also enable smarter, more efficient work. Workplaces designed for the age of AI are vital because they integrate AI systems to enhance productivity, innovation, and adaptability while cultivating human-AI collaboration.
By leveraging AI's capabilities, such as automation of repetitive tasks, advanced data analysis, and decision-making support, these workplaces empower workforces to focus on creative and strategic roles. Thoughtfully designed AI-integrated environments also prioritize ethical AI use, ensuring transparency, fairness, and alignment with human values, while addressing challenges like workforce reskilling and data security to create resilient, future-ready organizations.
Accordingly, Cisco introduced new devices for campus, branch, and industrial networks, along with AI-driven unified management for proactive, autonomous network operations. Additionally, Cisco’s AI-powered Room Vision PTZ camera enhances meetings with a cinematic experience, the Jira Workflow Automation in the Cisco AI Assistant for Webex Suite improves efficiency, and the Webex AI Agent simplifies customer self-service with tailored industry templates.
Unified Management: Key to Agentic AI Success
Unified management is critical to agentic AI success because it provides a cohesive framework for orchestrating the complex, interconnected infrastructure that supports autonomous, decision-making AI systems. Agentic AI relies on integration of networking, security, and observability to ensure low-latency inferencing, real-time data processing, and robust security across distributed environments.
Cisco introduced a preview of Cisco Cloud Control, a unified management platform that integrates its networking, security, and observability solutions. This platform is designed to deliver an experience powered by AI-native tools, including Cisco AI Canvas and the Cisco AI Assistant, enabling IT teams to streamline cross-product workflows, proactively detect and resolve issues, and manage infrastructure effortlessly.
As a result, Cisco can deliver the unified approach that is critical to ensuring digital resilience, mitigating risks from AI-driven threats, and supports the scalability and reliability needed for agentic AI to autonomously handle tasks such as business automation and cybersecurity, maintaining operational continuity and trust in enterprise settings.
Looking Ahead
Taken together, Agentic AI is transforming industries, driving innovation in design, engineering, manufacturing, and customer support. As businesses develop, implement, and scale advanced AI capabilities, Cisco’s networking and security solutions play a vital role in providing the robust, secure infrastructure needed to support these sophisticated systems.
The advent of agentic AI, characterized by autonomous decision-making, deep contextual understanding, and scalability, demands a fundamental shift in how these systems are managed and governed. To unlock their full potential, businesses require a new type of management console specifically designed for the agentic era, moving beyond traditional IT frameworks. This shift is critical to ensure that agentic AI systems, such as those integrated with Cisco’s infrastructure can operate efficiently, securely, and in alignment with enterprise goals in dynamic, data-intensive environments.
Effective management of agentic AI hinges on three core principles: human-in-the-loop collaboration, cross-domain context, and purpose-built design. Human-agent partnership is essential, combining human judgment, creativity, and strategic oversight with the speed, precision, and scalability of AI agents. These agents must also integrate insights from diverse data sources across applications and systems, breaking down silos to enable holistic decision-making.
Additionally, purpose-built models with deep domain expertise, such as Cisco’s Deep Network Model or Meta’s Llama-based cybersecurity LLM, ensure agents are optimized for specific tasks. To orchestrate this collaboration, a new operational framework - AgenticOps - is needed to streamline, optimize, and scale interactions between humans and intelligent agents, ensuring robust performance and digital resilience in the evolving AI ecosystem.
Overall, I believe Cisco is providing essential infrastructure for the AI era, delivering secure, AI-optimized networks and experiences that connect the world and drive the global economy. As organizations increasingly adopt agentic AI to streamline workflows and tackle complex challenges, Cisco leveraging its extensive expertise in infrastructure management, portfolio development acumen, and providing the strategic agentic AI vision key to empowering the next generation of AI innovation.
Ron Westfall | Analyst In Residence
Ron Westfall is a prominent analyst figure in technology and business transformation. Recognized as a Top 20 Analyst by AR Insights and a Tech Target contributor, his insights are featured in major media such as CNBC, Schwab Network, and NMG Media.
His expertise covers transformative fields such as Hybrid Cloud, AI Networking, Security Infrastructure, Edge Cloud Computing, Wireline/Wireless Connectivity, and 5G-IoT. Ron bridges the gap between C-suite strategic goals and the practical needs of end users and partners, driving technology ROI for leading organizations.