logo
Cisco Powers Secure Infrastructure for the AI Era

Cisco Powers Secure Infrastructure for the AI Era

Web Release11-06-2025
Cisco (NASDAQ: CSCO) today 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. To help organizations meet these opportunities, Cisco continues to reimagine the datacenters and workplaces of the future.
'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.'
Patrick Milligan, chief information security officer, Ford Motor Company, noted, 'Agentic AI is being used across Ford's business, from design to engineering to manufacturing and for customer support.? As we build, deploy, and manage sophisticated AI capabilities at scale, Cisco's networking and security solutions are an important part of the overall technology infrastructure.'
At Cisco Live, 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. Read more here: The AI-Ready Enterprise: Building the Intelligent Workplace with Cisco
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. Read more here: Welcome to the Agentic Era: People + Agents Achieving More, Together
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. Read more here: Making Agentic AI Work in the Real World and Cisco Hybrid Mesh Firewall: Better Enforcement Points, Smarter Segmentation, and Multi-Vendor Policy
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. Read more here: Cisco and Splunk Strengthen Enterprise Digital Resilience in the AI Era
Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

Energy and Innovation summit: Trump says $92bn to be invested in Pennsylvania for AI and tech
Energy and Innovation summit: Trump says $92bn to be invested in Pennsylvania for AI and tech

The National

time4 hours ago

  • The National

Energy and Innovation summit: Trump says $92bn to be invested in Pennsylvania for AI and tech

US President Donald Trump pushed his vision on powering energy-hungry artificial intelligence, during the first Pennsylvania Energy and Innovation Summit. At a discussion on Tuesday, Mr Trump claimed that more than 20 technology and energy companies had decided to invest $92 billion in Pennsylvania. "This is really a triumphant day for the people of the Commonwealth," he told the event, led by Republican US Senator Dave McCormick, in Pittsburgh at Carnegie Mellon University. 'This summit is about catalysing $90 billion of investment and tens of thousands of jobs in Pennsylvania,' Mr McCormick said. He also referred to the increasingly adversarial relationship between the US and China as he set the stage for the day's agenda. 'If we don't lead this AI revolution on our own terms, we will hand control of our infrastructure, data, leadership and way of life to the Chinese Communist Party,' Mr McCormick said. With AI continuing to expand into all aspects of life, the burden it places on the US energy grid is becoming more of an issue, as policymakers try to keep America leading the global race for AI dominance. According to a report from the US Energy Department, data centres used about 4.4 per cent of total electricity in the country in 2024. By 2028, that share could increase to 12 per cent. By most estimates, a query to ChatGPT uses 10 times more energy than a similar search on Google. The event has featured panels and discussions on energy and AI, including how to best meet the energy needs created by the technology, and looking at the efficiencies that AI could create in the years ahead. There were also discussions about the need for data centres to keep up with the AI investment boom and increased user demand. During the opening panel discussion, alternative asset management firm Blackstone made a $25 billion investment in building data centres in Pennsylvania. Investors, entrepreneurs and business leaders from around the world are attending the event. Khaldoon Al Mubarak, Mubadala's managing director and chief executive and chairman of the UAE Executive Affairs Authority, made the trip to Pittsburgh. Lim Chow Kiat, chief executive of Singapore's Government Investment Corporation, was also invited. US Treasury Secretary Scott Bessent, Commerce Secretary Howard Lutnick, Interior Secretary Doug Burgum and Energy Secretary Chris Wright were among the White House officials in attendance. Alex Karp, chief executive of AI firm Palantir, Joseph Dominguez, Constellation Energy chief, and Jake Loosararian, founder of Gecko Robotics, also took part. As proof of how bipartisan AI and energy issues have become, Pennsylvania's Democratic Governor Josh Shapiro, a staunch critic of Mr Trump and a possible contender for the 2028 Democratic presidential race, is scheduled to attend. For coal, fracking and even nuclear power, Pennsylvania has become the centre of the US energy renaissance. A few weeks ago, Mr Shapiro attended a nuclear energy rally to celebrate a partnership with Microsoft at the Three Mile Island nuclear power plant in the state, which will soon reopen under a different name. Nuclear energy is seen by many supporters of AI as a way to strengthen the energy grid as use of the technology expands. But critics fear the content of the event will be taken over by politics. A day before the event, Carnegie Mellon University's president, Farnam Jahanian, acknowledged the politically charged backdrop against which the conference was taking place. 'I recognise that CMU's decision to host the summit has prompted concern and disagreement among some members of our community,' Mr Jahanian said, pointing out his disagreements with Mr Trump on issues concerning education funding. 'At the same time, I firmly believe that higher education must be a convener – a catalyst for ideas and partnerships that shape our future.' On Tuesday, Mr Jahanian said CMU, with its roots in technology, was the perfect host for the summit, which was a 'defining moment for our country and humanity'. He said AI was 'the most important intellectual development of our time'.

Meta to invest ‘hundreds of billions' of dollars in advanced AI
Meta to invest ‘hundreds of billions' of dollars in advanced AI

Arabian Business

time7 hours ago

  • Arabian Business

Meta to invest ‘hundreds of billions' of dollars in advanced AI

Meta Platforms plans to invest hundreds of billions of dollars in computing infrastructure to advance its superintelligence ambitions in artificial intelligence (AI), according to Chief Executive Mark Zuckerberg. Writing on social media platform Threads, Zuckerberg said Meta would build one of the most 'elite and talent-dense teams in the industry' and had the capital from its business to support the plans. 'We're also going to invest hundreds of billions of dollars into compute to build superintelligence,' he said. Meta investing hundreds of billions in AI Superintelligence refers to a hypothetical AI system that is capable of outperforming the human brain. Zuckerberg unveiled plans for massive data centres to support the effort. One facility, called Prometheus, is expected to go online in 2026. Another, Hyperion, could eventually consume up to 5 gigawatts of power – enough to supply electricity to more than four million average US households, according to experts.

7 Hard Truths About Building AI Products That Last
7 Hard Truths About Building AI Products That Last

Martechvibe

time8 hours ago

  • Martechvibe

7 Hard Truths About Building AI Products That Last

For years, product innovation has been fueled by excitement: a new framework, a breakthrough model, a rising trend. But in 2025, as AI weaves itself into every interface, the question that separates good AI products from enduring ones isn't 'What can we build?'—it's 'What should we build?' According to the 2025 State of Martech Report by Scott Brinker, product management is now one of the most pivotal roles in the Martech ecosystem tasked with balancing rapid innovation, data complexity, and the promise (and pitfalls) of AI. As boundaries between product, marketing, and customer experience blur, the need for clarity, focus, and intentional design has never been greater. Because behind every buzzword, be it LLM, Web3, or genAI , is a simple truth: if it doesn't solve a real customer problem, it's noise. To ground this exploration, we turn to insights from Sumaiya Noor, Product, AI & Technology Leader, who has built B2B, B2C, and B2B2C SaaS products across emerging tech domains like AI and Web3. Drawing from her product, engineering, and customer experience background, Sumaiya offers a refreshingly pragmatic lens, one focused not on hype cycles, but on human problems. Strategy Can't Be Built in Silos In high-velocity environments, roadmaps shift, features morph, and priorities blur. So how do you keep AI product and marketing aligned ? The answer lies in dissolving the silos entirely. 'We don't build and then inform,' says Sumaiya. 'We build together.' Cross-functional planning, with inputs from sales, marketing, CX, and engineering, not only improves go-to-market timing, it ensures that every feature is designed with customer communication in mind. And yet, even with cross-functional harmony, another trap remains: building for the tech instead of the problem. That's where disciplined product thinking becomes essential. The Case for Problem-First Product Thinking There's a temptation to fall in love with an idea or worse, a technology. But as Sumaiya puts it: 'Even the best idea is irrelevant if no one will pay for it.' The most impactful products today aren't those that chase AI for the sake of AI. They start with deep listening. They define the problem before prescribing the tech. And only then do they decide whether that shiny new model is the right tool. But what happens when customer needs evolve faster than the solutions built to serve them? When Customer Pain Points Evolve Faster Than You Build Technology is changing rapidly but so are customer expectations. The feature they needed last month might feel redundant next week. This is where continuous product discovery becomes non-negotiable. Beta feedback, prototype testing, and agile pivots must be baked into the build process. 'It's not about being right from the start,' says Sumaiya. 'It's about being flexible enough to shift fast, based on what your users actually tell you.' Flexibility is key. Not just in building, but in knowing when to stop building. Because holding on to outdated features can be just as risky as launching the wrong ones. Sunsetting Isn't Failure, It's Focus Great teams know when to quit. That feature your team launched with pride may no longer serve its purpose—maybe a competitor has done it better, or your users have outgrown it. The hardest part? Internal buy-in. 'You're not just retiring code,' Sumaiya notes. 'You're sunsetting people's effort, pride, and belief.' But with clear metrics and shared goals, this becomes a strategic move, not an emotional one. And as AI becomes embedded in more features, another layer of complexity emerges: unpredictability. Especially when the tech behaves in ways even its creators can't fully control. You Can't Eliminate AI Hallucinations But You Can Contain Them As large language models make their way into every workflow, a difficult truth remains: hallucinations are part of the system. 'If someone in the product world says that hallucination can completely be eliminated or can be mitigated, I think they don't understand the technological side of LLMs or AI, artificial intelligence or agents that much,' says Sumaiya. Rather than over-promise, product teams must scope narrowly, train models on proprietary data, and design safeguards to guide behaviour. 'You can't fully control LLMs but you can control how, where, and why you deploy them.' But responsible deployment isn't enough. You also need to know if your AI is actually adding value, which brings us to the challenge of building effective feedback loops. Feedback Loops in AI Products Are Twice As Hard Feedback is already tough in traditional product development. In AI, it's even more layered. 'You need two types of feedback loops. One for validating the feature itself, the service itself, whatever you are trying to provide to the customer. In terms of solving their problem or pain point. If it's an AI integrated or AI-based product, the additional feedback loop is also required to validate what type of value addition this AI integration is adding to your overall solution,' says Sumaiya. You're not only asking whether a feature works, you're asking whether AI is meaningfully improving the experience. This means comparing pre- and post-AI metrics, collecting real-time usage data, and isolating AI's impact on usability and satisfaction. Even with feedback in place, product teams still face a difficult judgment call: which technologies are worth betting on, and which ones are just noise? How to Tell If a Technology Will Stick or Fizzle When everyone's chasing the next 'platform shift,' how do you know what's real? Sumaiya's take: measure cost (financial, environmental, ethical), problem-fit, and long-term sustainability. Her critique of blockchain coin mining, versus her long-term belief in AI, isn't about trendiness. It's about impact. 'Tech that creates more problems than it solves won't last.' In the end, it's not about resisting innovation. It's about choosing it wisely. In a world shaped by AI, what we build is only as good as why we build it. ALSO READ: Brands Use Context Engineering to Appeal to Answer Engines Chandni is an Editor with a keen interest in customer-obsessed ideas. A journalist by profession and a writer at heart, she is committed to martech and CX content that resonates with readers across industries. View More

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store