Cisco executives make the case that the excellence between product and mannequin corporations is disappearing, and that accessing the 55% of enterprise information progress that present AI ignores will separate winners from losers.
VentureBeat lately caught up with Jeetu Patel, Cisco’s President and Chief Product Officer and DJ Sampath, Senior Vice President of AI Software program and Platform, to realize new insights right into a compelling thesis each leaders share. They and their groups contend that each profitable product firm should turn into an AI mannequin firm to outlive the subsequent decade.
When one considers how compressed product lifecycles have gotten, mixed with the various benefits of digital twin know-how to speed up time-to-market of next-gen merchandise, the thesis is sensible.
The dialog revealed why this transformation is inevitable, backed by strong information factors. The group contends that 55% of all information progress is machine information that present AI fashions do not contact. OpenAI’s Greg Brockman estimates we’d like 10 billion GPUs to present each human the AI brokers they will want, and Cisco’s open supply safety mannequin, Basis-Sec-8B, has already seen 200,000 downloads on Hugging Face.
Why the mannequin is changing into the product
VentureBeat: You’ve got acknowledged that sooner or later, each product firm will turn into a mannequin firm. Why is that this inevitable somewhat than only one potential path?
Jeetu Patel: Sooner or later, there is no distinction between mannequin corporations and product corporations. Nice product corporations will likely be mannequin corporations. The shut tie-in between mannequin and product is a closed loop. To reinforce the product, you improve the mannequin, not only a UI shim.
These corporations being shaped proper now which can be a skinny shim on high of a mannequin; their days are numbered. The true moat is the mannequin you construct that drives product habits. This requires being concurrently good at two issues: constructing nice fashions in domains the place you have got nice information, and constructing nice product experiences powered by these fashions in an iterative loop the place the fashions adapt and evolve when you have got product enhancement requests.
DJ Sampath: This turns into much more important when you concentrate on issues shifting to brokers. Brokers are going to be ruled by these fashions. Your moat is de facto going to be how nicely your mannequin reacts to the modifications it must.
Harnessing machine information’s progress is vital
VentureBeat: You talked about that 55% of knowledge progress is machine information, but present fashions aren’t skilled on it. Why does this characterize such a large alternative?
Patel: To this point, fashions have been excellent at being skilled on publicly obtainable, human-generated information freely obtainable on the web. However we’re accomplished with the quantity of public information you might crawl. The place else do you go subsequent? It is all locked up inside enterprises.
55% of knowledge progress is machine information, however fashions should not skilled on machine information. Each firm says ‘my information is my moat,’ however most do not have an efficient approach to situation that information into an organized pipeline to allow them to practice AI with it and harness its full potential.
Think about how a lot log information will likely be generated when brokers work 24/7 and each human has 100 brokers. Greg Brockman from OpenAI mentioned should you assume each human has a GPU, you are three orders of magnitude away from the place you should be; you want 10 billion GPUs. If you assume that approach, should you do not practice your fashions with machine information successfully, you are incomplete in your capacity to harness the total potential of AI.
Sampath: Many of the fashions are being skilled on public information. The information that is inside enterprises is generally machine information. We’re unlocking that machine information. We give every enterprise a beginning mannequin. Consider it as a starter equipment. They will take that mannequin and construct purposes and brokers fine-tuned on their proprietary information inside their enterprises. We will be a mannequin firm, however we’re additionally going to make it extremely straightforward for each single enterprise to construct their very own fashions utilizing the infrastructure we offer.
Why {hardware} corporations have a bonus
VentureBeat: Many see {hardware} as a legal responsibility within the software program and AI period. You argue the alternative. Why?
Patel: Lots of people look down on {hardware}. I really assume {hardware} is a superb asset to have, as a result of if you know the way to construct nice {hardware} and nice software program and nice AI fashions and tie all of them collectively, that is when magic begins to occur.
Take into consideration what we are able to do by correlating machine information from logs with our time sequence mannequin. If there is a one-degree change in your change or router, you may predict system failure in three days, one thing you could not correlate earlier than. You determine the change, reroute site visitors to stop issues, and remedy the difficulty. Get way more predictive in outages and infrastructure stability.
Cisco is the important infrastructure firm for AI. This utterly modifications the extent of stability we are able to generate for our infrastructure. Manufacturing is without doubt one of the high industries for the info quantity generated every day. Mixed with agentic AI and amassed metadata, it utterly modifications the aggressive nature of producing or asset-intensive industries. With sufficient information, they will transcend disruptions round tariffs or provide chain variations, getting them out of worth and availability commoditization.
Cisco’s deep dedication to Open Supply
VentureBeat: Why make your safety fashions open supply when that appears to present away aggressive benefit?
Sampath: The cat is out of the bag; attackers even have entry to open supply fashions. The following step is equipping as many defenders as potential with fashions that make protection stronger. That is actually what we did at RSAC 2025 once we launched our open supply mannequin, Basis-Sec-8B.
Funding for open supply initiatives has stalled. There’s an elevated drain within the open supply neighborhood, needing sustainable, collaborative funding sources. It is a company duty to make these fashions obtainable, plus it gives entry to communities to start out working with AI from a protection perspective.
We have built-in ClamAV, a broadly used open supply antivirus device, with Hugging Face, which hosts over 2 million fashions. Each single mannequin will get scanned for malware. You need to make sure the AI provide chain is appropriately protected, and we’re on the forefront of doing that.
Patel: We launched not simply the safety mannequin that is open supply, but additionally one on Splunk for time sequence information. These correlate information; time sequence and safety incident information, to have the ability to discover very attention-grabbing outcomes. With 200,000 downloads on Hugging Face, we’re seeing resellers beginning to construct purposes with it.
Taking the shoppers’ pulse after Cisco Reside
VentureBeat: Following Cisco Reside’s product launches, how are clients responding?
Patel: There are three classes. First, utterly ecstatic clients: ‘We have been asking for this for some time. Hallelujah.’
Second, these saying ‘I am going to do this out.’ DJ reveals them a demo with white glove therapy, they do a POC, they usually’re dumbfounded that it is even higher than what we mentioned in three minutes on stage.
Third are skeptics who confirm that each announcement comes out on the precise days. That group was once a lot larger three years in the past. Because it’s shrunk, we have seen significant enhancements in our monetary outcomes and the way the market sees us.
We do not speak about issues three years out, solely inside a six-month window. The payload is so massive that we have now sufficient to debate for six months. Our largest problem, frankly, is retaining our clients updated with the rate of innovation we have now.
Obsessing over clients, not {hardware}
VentureBeat: How are you migrating your hardware-centric put in base with out creating an excessive amount of disruption?
Patel: Moderately than fixating on ‘{hardware} versus software program,’ you begin from the place the client is. Your technique can not be a perimeter-based firewall for community safety as a result of the market has moved. It is hyper-distributed. However you presently have firewalls that want environment friendly administration.
We’re supplying you with a totally refreshed firewall lineup. If you wish to have a look at what we have accomplished with public cloud, managing egress site visitors with Multicloud Protection with zero belief, not simply user-to-application, however application-to-application. We have constructed Hypershield know-how. We have constructed a revolutionary Sensible Change. All managed by the identical Safety Cloud Management with AI Canvas on high.
We inform our clients they will go at their very own tempo. Begin with firewalls, transfer to Multicloud Protection, add Hypershield enforcement factors with Cilium for observability, and add Sensible Switches. You do not have so as to add extra complexity as a result of we have now a real platform benefit with Safety Cloud Management. Moderately than saying ‘neglect every part and transfer to the brand new factor’, creating an excessive amount of cognitive load, we begin the place the client is and take them by means of the journey.
What’s subsequent: energizing international companions to show AI right into a income alternative
The interview concluded with discussions of November’s Accomplice Summit in San Diego, the place Cisco plans vital companion activation bulletins. As Patel famous, “Sustained, constant emphasis is required to get the complete reseller engine shifting.” VentureBeat is satisfied {that a} globally sturdy companion group is indispensable for any cybersecurity firm to achieve its long-term AI imaginative and prescient.
