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Cisco Powers Secure Infrastructure for the AI Era

Cisco unveiled new innovations to help companies adapt and transform in the AI era. 

“Cisco is delivering the critical infrastructure for the AI era—secure networks and experiences, optimized for AI that connect the world and power the global economy,” said Jeetu Patel, President and Chief Product Officer, Cisco. “We’re witnessing an unprecedented surge in innovation as organizations embrace agentic AI to automate workflows and solve complex problems. Cisco has a rich history of helping companies run their infrastructure; today, we’re building on that foundation to power the next generation of AI.”

Cisco unveiled a wide range of new products and enhancements to help customers navigate the shift to agentic AI, including:

  • Workplaces for the age of AI: Creating an intelligent workplace relies on modern network infrastructure that adapts to increased traffic, ensures always-on access, and delivers robust security. Meanwhile, organizations must empower people to work smarter and more effectively than ever. To meet these demands, Cisco announced new devices to power campus, branch, and industrial networks, and AI-powered unified management to help organizations move past reactive workflows to conducting autonomous, proactive network management. Additionally, Cisco's AI-powered Room Vision PTZ camera transforms meetings for a more cinematic experience. The Jira Workflow Automation in the Cisco AI Assistant for Webex Suite boosts efficiency, while the Webex AI Agent streamlines customer self-service with industry-specific templates.
  • Simplified Operations for the age of AI with AgenticOps: Cisco is unveiling multiple AI-driven solutions to empower IT teams with simplicity, and automation, including Cisco AI Canvas, an industry-first generative user interface for real-time collaboration between network and security operations teams, and the Cisco AI Assistant, which provides conversational control across the Cisco suite. Core to the new capabilities is Cisco’s Deep Network Model — a domain-specific LLM trained on Cisco’s vast knowledge base, including Cisco U. courseware and Certified Internetwork Expert (CCIE) materials. The result is AI that understands networks and helps IT teams work more efficiently.
  • Data Centers for the age of AI: Cisco unveiled continued innovation in its compute and network solutions for datacenters to support agentic AI, which places a premium on network bandwidth, latency, and power efficiency. To help drive adoption of AI solutions to strengthen the power grid, Cisco is joining the EPRI Open Power AI Consortium. Additionally, Cisco is introducing new capabilities to assist service providers to deliver and monetize new AI services.
  • Security for the age of AI: Robust security has never been more critical, as enterprises navigate the complexity of a growing number of applications, a highly distributed and mobile workforce, and sophisticated AI-driven threats.Cisco is introducing innovations across its Hybrid Mesh Firewall and Universal Zero Trust Network Access (ZTNA) offerings; announced two new Firewalls, the 6100 series and 200 series, providing customers with best-in-class price performance; and unveiled capabilities across the Cisco Security Cloud to help customers meet the challenges of securing agentic AI.
  • Digital Resilience at the Core: Several AI innovations, including enhanced capabilities in Splunk Observability Cloud and Splunk AppDynamics, along with deeper integrations between Cisco and Splunk solutions, are helping customers gain greater visibility into network health and performance. Key updates include a bidirectional integration between Splunk Observability, Cisco ThousandEyes Assurance and Cisco Enterprise Networks, enabling more resilient, insight-driven digital operations.
  • Unified Management for the age of AI: The company is previewing Cisco Cloud Control, a new unified management platform spanning Cisco’s networking, security, and observability portfolios. Cisco Cloud Control will offer a cohesive experience anchored by AI native tools like Cisco AI Canvas, and the Cisco AI Assistant. With Cisco Cloud Control IT will be able to execute cross-product workflows, proactively identify and resolve issues, and manage infrastructure with ease. 
     

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cisco Powers Secure Infrastructure for the AI Era

Cisco unveiled new innovations to help companies adapt and transform in the AI era. 

“Cisco is delivering the critical infrastructure for the AI era—secure networks and experiences, optimized for AI that connect the world and power the global economy,” said Jeetu Patel, President and Chief Product Officer, Cisco. “We’re witnessing an unprecedented surge in innovation as organizations embrace agentic AI to automate workflows and solve complex problems. Cisco has a rich history of helping companies run their infrastructure; today, we’re building on that foundation to power the next generation of AI.”

Cisco unveiled a wide range of new products and enhancements to help customers navigate the shift to agentic AI, including:

  • Workplaces for the age of AI: Creating an intelligent workplace relies on modern network infrastructure that adapts to increased traffic, ensures always-on access, and delivers robust security. Meanwhile, organizations must empower people to work smarter and more effectively than ever. To meet these demands, Cisco announced new devices to power campus, branch, and industrial networks, and AI-powered unified management to help organizations move past reactive workflows to conducting autonomous, proactive network management. Additionally, Cisco's AI-powered Room Vision PTZ camera transforms meetings for a more cinematic experience. The Jira Workflow Automation in the Cisco AI Assistant for Webex Suite boosts efficiency, while the Webex AI Agent streamlines customer self-service with industry-specific templates.
  • Simplified Operations for the age of AI with AgenticOps: Cisco is unveiling multiple AI-driven solutions to empower IT teams with simplicity, and automation, including Cisco AI Canvas, an industry-first generative user interface for real-time collaboration between network and security operations teams, and the Cisco AI Assistant, which provides conversational control across the Cisco suite. Core to the new capabilities is Cisco’s Deep Network Model — a domain-specific LLM trained on Cisco’s vast knowledge base, including Cisco U. courseware and Certified Internetwork Expert (CCIE) materials. The result is AI that understands networks and helps IT teams work more efficiently.
  • Data Centers for the age of AI: Cisco unveiled continued innovation in its compute and network solutions for datacenters to support agentic AI, which places a premium on network bandwidth, latency, and power efficiency. To help drive adoption of AI solutions to strengthen the power grid, Cisco is joining the EPRI Open Power AI Consortium. Additionally, Cisco is introducing new capabilities to assist service providers to deliver and monetize new AI services.
  • Security for the age of AI: Robust security has never been more critical, as enterprises navigate the complexity of a growing number of applications, a highly distributed and mobile workforce, and sophisticated AI-driven threats.Cisco is introducing innovations across its Hybrid Mesh Firewall and Universal Zero Trust Network Access (ZTNA) offerings; announced two new Firewalls, the 6100 series and 200 series, providing customers with best-in-class price performance; and unveiled capabilities across the Cisco Security Cloud to help customers meet the challenges of securing agentic AI.
  • Digital Resilience at the Core: Several AI innovations, including enhanced capabilities in Splunk Observability Cloud and Splunk AppDynamics, along with deeper integrations between Cisco and Splunk solutions, are helping customers gain greater visibility into network health and performance. Key updates include a bidirectional integration between Splunk Observability, Cisco ThousandEyes Assurance and Cisco Enterprise Networks, enabling more resilient, insight-driven digital operations.
  • Unified Management for the age of AI: The company is previewing Cisco Cloud Control, a new unified management platform spanning Cisco’s networking, security, and observability portfolios. Cisco Cloud Control will offer a cohesive experience anchored by AI native tools like Cisco AI Canvas, and the Cisco AI Assistant. With Cisco Cloud Control IT will be able to execute cross-product workflows, proactively identify and resolve issues, and manage infrastructure with ease. 
     

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...