Cisco is bringing AI into its collaboration, networking, observability and security solutions; the message to customers at Cisco Live is we’re focused on “making AI work for you”
LAS VEGAS—Cisco CEO Chuck Robbins kicked off the company’s annual Cisco Live event with clear-eyed acknowledgement of the key challenges its customers face, and that they are looking to Cisco to solve: complexity, control and visibility. While that’s relatively easy to say, it’s much harder to do given long-term trends around the transition from multi-cloud by design rather than by default, by an explosion of endpoints that comprise an ever-expanding threat surface, and now with the proliferation of artificial intelligence (AI) into most every aspect of IT and networking.
Getting to that in his remarks, Robbins recalled criticism that Cisco was essentially late to the cloud era, perhaps the result of a legacy focus on hardware, although that’s all been pretty well reversed (and bolstered with a wide-ranging SaaS business) through strategic shifts and the notable acquisitions of Meraki, AppDynamics, ThousandEyes and others. “We perhaps were not as prepared as we should’ve been,” he said. But, “As this AI era begins we are very, very prepared to help you navigate this as we go forward.”
What that looks like at a high level is essentially taking the core parts of the business—collaboration, networking, observability and security—and enriching them all with AI. For example, the recently announced Cisco Nexus HyperFabric AI clusters uses some NVIDIA features to let users go from design through to deployment and onto monitoring and assurance of AI infrastructure and workloads. There are AI updates to Cisco ThousandEyes for digital experience assurance across on-prem datacenters, public cloud(s) and everywhere in between. And there’s a new $1 billion AI investment fund meant to embolden Cisco’s strategy to “connect and protect the AI era.”
On the bigger AI picture, whether your reference point is NVIDIA’s stock price, the exuberant keynotes out of Computex over in Taiwan this week, or your own personal ChatGPT-assisted ah-ha moment, the discourse has been at a sustained fever pitch since late 2022. As such, enterprises of all sorts are opening up the war chests and grabbing up GPUs, modernizing and AI-optimizing infrastructure, and loading proprietary data into multi-billion parameter large language models (LLMs). Business wants to be ready for AI, but are they really AI-ready? And even if they are AI-ready, how tangible is the return on the staggering amount of money pouring into the space?
In March, Wall Street Journal referenced a presentation from legendary Silicon Valley VC firm Sequoia Capital that quantified the situation at least in part: “Sequoia estimated that the AI industry spent $50 billion on the NVIDIA chips used to train advanced AI models last year, but brought in only $3 billion in revenue.” And all of that spend is upstream of the enterprise user. From another Wall Street Journal article from Christopher Mims, published on May 31, the columnist made the case that AI improvement is slowing down which isn’t helped by the aggregation of real data and synthetic data, and is starting to look more and more like a commodity. He concluded that whether AI delivers on the hype in the long run, current levels of AI investment seem “to be predicated on the idea that AI is going to get so much better, so fast, and be adopted so quickly that its impact on our lives and the economy is hard to comprehend. Mounting evidence suggests that won’t be the case.”
Back in March Cisco published its Cisco AI Readiness Index that surveyed more than 8,000 business and IT leaders. The key takeaways are that 84% or survey respondents “expect AI to have a significant or very significant impact on their business.” Further, 97% survey “reported an increased urgency to deploy AI-powered technologies. Of that 97%, only 14% of respondents felt that their organizations were ‘ready’ for AI.” Anyway, regardless of whether you see AI innovation triggers quickly leading to mainstream adoption and a plateau of productivity, or an imminent descent into the trough of disillusionment, the point is that there is a lot of hype on AI, there is a lot of potential, and a pragmatic, studied strategy (like the one Cisco laid out this week) probably wins out over time.
In a session with media and analysts, Cisco EVP and Chief Strategy Officer Mark Patterson, who is about 90 days into the role, noted how Cisco occupies a unique place in the AI continuum, including infrastructure, security, data, software and services. “Cisco connects and protects the AI era,” he said, driving home company messaging. “AI is, or will be, fundamentally changing every business around the globe,” and as that change unfolds, Cisco is “the trusted partner to help our customers navigate this new era of AI.” That said, Patterson did acknowledge that it’s “still a pretty nascent space,” marked by customers wrestling with use cases, models, data and network/datacenter re-architectures.
Following his remarks and a panel discussion, Patterson opened it up to questions from the august assembly of industry analysts collected in the main ballroom at the Four Seasons Las Vegas. Many of these “questions” sure sounded a lot more like soliloquies—gotta love protracted explanations to the people successfully running the $190 billion market cap company about how they’re running the $190 billion market cap company wrong. But to summarize some of the “questions,” there was criticism that the sins of the past were being repeated as Cisco is late to the AI game.
Patterson rightly made the point that there’s an important distinction between buying AI and leveraging AI to deliver a business outcome. Cisco’s broad portfolio, partner ecosystem and ability to invest “will make a huge impact and really allow our customers, ultimately, to get to the outcome they want,” he said. His colleague Derek Idemoto, senior vice president of corporate development and Cisco Investments, threw out that around $500 billion is going to get spent on AI in the next three years. “I’d argue that a lot of that is net new…The connection between networking, observability, collaboration, security, all those pieces will fit together.”
