Cisco executives make the case that the distinction between product and model companies is disappearing, and that accessing the 55% of enterprise data growth that current AI ignores will separate winners from losers.
VentureBeat recently caught up with Jeetu Patel, Cisco's President and Chief Product Officer and DJ Sampath, Senior Vice President of AI Software and Platform, to gain new insights into a compelling thesis both leaders share. They and their teams contend that every successful product company must become an AI model company to survive the next decade.
When one considers how compressed product lifecycles are becoming, combined with the many advantages of digital twin technology to accelerate time-to-market of next-gen products, the thesis makes sense.
The conversation revealed why this transformation is inevitable, backed by solid data points. The team contends that 55% of all data growth is machine data that current AI models don't touch. OpenAI's Greg Brockman estimates we need 10 billion GPUs to give every human the AI agents they'll need, and Cisco's open source security model, Foundation-Sec-8B, has already seen 200,000 downloads on Hugging Face.
Why the model is becoming the product
VentureBeat: You've stated that in the future, every product company will become a model company. Why is this inevitable rather than just one possible path?
Jeetu Patel: In the future, there's no distinction between model companies and product companies. Great product companies will be model companies. The close tie-in between model and product is a closed loop. To enhance the product, you enhance the model, not just a UI shim.
These companies being formed right now that are a thin shim on top of a model; their days are numbered. The true moat is the model you build that drives product behavior. This requires being simultaneously good at two things: building great models in domains where you have great data, and building great product experiences powered by those models in an iterative loop where the models adapt and evolve when you have product enhancement requests.
DJ Sampath: This becomes even more critical when you think about things moving to agents. Agents are going to be governed by these models. Your moat is really going to be how well your model reacts to the changes it needs to.
Harnessing machine data's growth is key
VentureBeat: You mentioned that 55% of data growth is machine data, yet current models aren't trained on it. Why does this represent such a massive opportunity?
Patel: So far, models have been very good at being trained on publicly available, human-generated data freely available on the internet. But we're done with the amount of public data you could crawl. Where else do you go next? It's all locked up inside enterprises.
55% of data growth is machine data, but models are not trained on machine data. Every company says 'my data is my moat,' but most don't have an effective way to condition that data into an organized pipeline so they can train AI with it and harness its full potential.
Imagine how much log data will be generated when agents work 24/7 and every human has 100 agents. Greg Brockman from OpenAI said if you assume every human has a GPU, you're three orders of magnitude away from where you need to be; you need 10 billion GPUs. When you think that way, if you don't train your models with machine data effectively, you're incomplete in your ability to harness the full potential of AI.
Sampath: Most of the models are being trained on public data. The data that's inside enterprises is mostly machine data. We're unlocking that machine data. We give each enterprise a starting model. Think of it as a starter kit. They'll take that model and build applications and agents fine-tuned on their proprietary data inside their enterprises. We're going to be a model company, but we're also going to make it incredibly easy for every single enterprise to build their own models using the infrastructure we provide.
Why hardware companies have an advantage
VentureBeat: Many see hardware as a liability in the software and AI era. You argue the opposite. Why?
Patel: A lot of people look down on hardware. I actually think hardware is a great asset to have, because if you know how to build great hardware and great software and great AI models and tie them all together, that's when magic starts to happen.
Think about what we can do by correlating machine data from logs with our time series model. If there's a one-degree change in your switch or router, you might predict system failure in three days, something you couldn't correlate before. You identify the change, reroute traffic to prevent problems, and solve the issue. Get much more predictive in outages and infrastructure stability.
Cisco is the critical infrastructure company for AI. This completely changes the level of stability we can generate for our infrastructure. Manufacturing is one of the top industries for the data volume generated daily. Combined with agentic AI and accumulated metadata, it completely changes the competitive nature of manufacturing or asset-intensive industries. With enough data, they can transcend disruptions around tariffs or supply chain variations, getting them out of price and availability commoditization.
Cisco's deep commitment to Open Source
VentureBeat: Why make your security models open source when that seems to give away competitive advantage?
Sampath: The cat is out of the bag; attackers also have access to open source models. The next step is equipping as many defenders as possible with models that make defense stronger. That's really what we did at RSAC 2025 when we launched our open source model, Foundation-Sec-8B.
Funding for open source initiatives has stalled. There's an increased drain in the open source community, needing sustainable, collaborative funding sources. It's a corporate responsibility to make these models available, plus it provides access to communities to start working with AI from a defense perspective.
We've integrated ClamAV, a widely used open source antivirus tool, with Hugging Face, which hosts over 2 million models. Every single model gets scanned for malware. You have to ensure the AI supply chain is appropriately protected, and we're at the forefront of doing that.
Patel: We launched not just the security model that's open source, but also one on Splunk for time series data. These correlate data; time series and security incident data, to be able to find very interesting outcomes. With 200,000 downloads on Hugging Face, we're seeing resellers starting to build applications with it.
Taking the customers' pulse after Cisco Live
VentureBeat: Following Cisco Live's product launches, how are customers responding?
Patel: There are three categories. First, completely ecstatic customers: 'We've been asking for this for a while. Hallelujah.'
Second, those saying 'I'm going to try this out.' DJ shows them a demo with white glove treatment, they do a POC, and they're dumbfounded that it's even better than what we said in three minutes on stage.
Third are skeptics who verify that every announcement comes out on the exact days. That group used to be much bigger three years ago. As it's shrunk, we've seen meaningful improvements in our financial results and how the market sees us.
We don't talk about things three years out, only within a six-month window. The payload is so large that we have enough to discuss for six months. Our biggest challenge, frankly, is keeping our customers up to date with the velocity of innovation we have.
Obsessing over customers, not hardware
VentureBeat: How are you migrating your hardware-centric installed base without creating too much disruption?
Patel: Rather than fixating on 'hardware versus software,' you start from where the customer is. Your strategy can no longer be a perimeter-based firewall for network security because the market has moved. It's hyper-distributed. But you currently have firewalls that need efficient management.
We're giving you a fully refreshed firewall lineup. If you want to look at what we've done with public cloud, managing egress traffic with Multicloud Defense with zero trust, not just user-to-application, but application-to-application. We've built Hypershield technology. We've built a revolutionary Smart Switch. All managed by the same Security Cloud Control with AI Canvas on top.
We tell our customers they can go at their own pace. Start with firewalls, move to Multicloud Defense, add Hypershield enforcement points with Cilium for observability, and add Smart Switches. You don't have to add more complexity because we have a true platform advantage with Security Cloud Control. Rather than saying 'forget everything and move to the new thing', creating too much cognitive load, we start where the customer is and take them through the journey.
What's next: energizing global partners to turn AI into a revenue opportunity
The interview concluded with discussions of November's Partner Summit in San Diego, where Cisco plans significant partner activation announcements. As Patel noted, "Sustained, consistent emphasis is needed to get the entire reseller engine moving." VentureBeat is convinced that a globally strong partner organization is indispensable for any cybersecurity company to attain its long-term AI vision.
