Cisco executives make the case that the excellence between product and mannequin firms is disappearing, and that accessing the 55% of enterprise knowledge progress that present AI ignores will separate winners from losers.
VentureBeat just 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 achieve 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 following decade.
When one considers how compressed product lifecycles have gotten, mixed with the various benefits of digital twin expertise to speed up time-to-market of next-gen merchandise, the thesis is sensible.
The dialog revealed why this transformation is inevitable, backed by stable knowledge factors. The group contends that 55% of all knowledge progress is machine knowledge that present AI fashions don't contact. OpenAI's Greg Brockman estimates we want 10 billion GPUs to provide each human the AI brokers they'll 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 acknowledged that sooner or later, each product firm will turn into a mannequin firm. Why is that this inevitable fairly than only one doable path?
Jeetu Patel: Sooner or later, there's no distinction between mannequin firms and product firms. Nice product firms can be mannequin firms. 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 firms being fashioned proper now which might be a skinny shim on prime of a mannequin; their days are numbered. The true moat is the mannequin you construct that drives product conduct. This requires being concurrently good at two issues: constructing nice fashions in domains the place you’ve gotten nice knowledge, and constructing nice product experiences powered by these fashions in an iterative loop the place the fashions adapt and evolve when you’ve gotten product enhancement requests.
DJ Sampath: This turns into much more crucial when you consider issues transferring to brokers. Brokers are going to be ruled by these fashions. Your moat is actually going to be how properly your mannequin reacts to the modifications it must.
Harnessing machine knowledge's progress is essential
VentureBeat: You talked about that 55% of knowledge progress is machine knowledge, but present fashions aren't skilled on it. Why does this signify such an enormous alternative?
Patel: Thus far, fashions have been excellent at being skilled on publicly accessible, human-generated knowledge freely accessible on the web. However we're achieved with the quantity of public knowledge you can crawl. The place else do you go subsequent? It's all locked up inside enterprises.
55% of knowledge progress is machine knowledge, however fashions are usually not skilled on machine knowledge. Each firm says 'my knowledge is my moat,' however most don't have an efficient strategy to situation that knowledge into an organized pipeline to allow them to prepare AI with it and harness its full potential.
Think about how a lot log knowledge can be generated when brokers work 24/7 and each human has 100 brokers. Greg Brockman from OpenAI stated if you happen to assume each human has a GPU, you're three orders of magnitude away from the place you might want to be; you want 10 billion GPUs. Once you suppose that means, if you happen to don't prepare your fashions with machine knowledge successfully, you're incomplete in your capacity to harness the total potential of AI.
Sampath: A lot of the fashions are being skilled on public knowledge. The info that's inside enterprises is usually machine knowledge. We're unlocking that machine knowledge. We give every enterprise a beginning mannequin. Consider it as a starter equipment. They'll take that mannequin and construct purposes and brokers fine-tuned on their proprietary knowledge inside their enterprises. We're going to be a mannequin firm, however we're additionally going to make it extremely simple for each single enterprise to construct their very own fashions utilizing the infrastructure we offer.
Why {hardware} firms 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 suppose {hardware} is a good asset to have, as a result of if you understand how to construct nice {hardware} and nice software program and nice AI fashions and tie all of them collectively, that's when magic begins to occur.
Take into consideration what we will do by correlating machine knowledge from logs with our time sequence mannequin. If there's a one-degree change in your swap or router, you may predict system failure in three days, one thing you couldn't correlate earlier than. You establish the change, reroute visitors to stop issues, and clear up the problem. Get far more predictive in outages and infrastructure stability.
Cisco is the crucial infrastructure firm for AI. This fully modifications the extent of stability we will generate for our infrastructure. Manufacturing is without doubt one of the prime industries for the info quantity generated each day. Mixed with agentic AI and accrued metadata, it fully modifications the aggressive nature of producing or asset-intensive industries. With sufficient knowledge, they’ll transcend disruptions round tariffs or provide chain variations, getting them out of value and availability commoditization.
Cisco's deep dedication to Open Supply
VentureBeat: Why make your safety fashions open supply when that appears to provide 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 doable with fashions that make protection stronger. That's actually what we did at RSAC 2025 after we launched our open supply mannequin, Foundation-Sec-8B.
Funding for open supply initiatives has stalled. There's an elevated drain within the open supply group, needing sustainable, collaborative funding sources. It's a company accountability to make these fashions accessible, plus it gives entry to communities to begin working with AI from a protection perspective.
We've built-in ClamAV, a extensively 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's open supply, but in addition one on Splunk for time sequence knowledge. These correlate knowledge; time sequence and safety incident knowledge, to have the ability to discover very fascinating outcomes. With 200,000 downloads on Hugging Face, we're seeing resellers beginning to construct purposes with it.
Taking the shoppers' pulse after Cisco Dwell
VentureBeat: Following Cisco Dwell's product launches, how are clients responding?
Patel: There are three classes. First, fully ecstatic clients: 'We've been asking for this for some time. Hallelujah.'
Second, these saying 'I'm going to do this out.' DJ exhibits them a demo with white glove remedy, they do a POC, and so they're dumbfounded that it's even higher than what we stated in three minutes on stage.
Third are skeptics who confirm that each announcement comes out on the precise days. That group was a lot larger three years in the past. Because it's shrunk, we've seen significant enhancements in our monetary outcomes and the way the market sees us.
We don't discuss issues three years out, solely inside a six-month window. The payload is so massive that we’ve sufficient to debate for six months. Our largest problem, frankly, is conserving our clients updated with the speed of innovation we’ve.
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 shopper is. Your technique can not be a perimeter-based firewall for community safety as a result of the market has moved. It's hyper-distributed. However you presently have firewalls that want environment friendly administration.
We're supplying you with a completely refreshed firewall lineup. If you wish to have a look at what we've achieved with public cloud, managing egress visitors with Multicloud Protection with zero belief, not simply user-to-application, however application-to-application. We've constructed Hypershield technology. We've constructed a revolutionary Good Swap. All managed by the identical Safety Cloud Management with AI Canvas on prime.
We inform our clients they’ll go at their very own tempo. Begin with firewalls, transfer to Multicloud Protection, add Hypershield enforcement factors with Cilium for observability, and add Good Switches. You don't have so as to add extra complexity as a result of we’ve a real platform benefit with Safety Cloud Management. Moderately than saying 'overlook every part and transfer to the brand new factor', creating an excessive amount of cognitive load, we begin the place the shopper is and take them by means of the journey.
What's subsequent: energizing world companions to show AI right into a income alternative
The interview concluded with discussions of November's Companion Summit in San Diego, the place Cisco plans vital companion activation bulletins. As Patel famous, "Sustained, constant emphasis is required to get all the reseller engine transferring." VentureBeat is satisfied {that a} globally sturdy companion group is indispensable for any cybersecurity firm to realize its long-term AI imaginative and prescient.
