Cisco warns enterprises: Without tapping machine data, your AI strategy is incomplete

Cisco executives assert that the distinction between product companies and model companies is disappearing, and that reaching the 55% of enterprise data growth that current AI ignores will separate the winners from the losers.

VentureBeat recently caught up with Jeetu Patel, president and Chief Product Officer at Cisco, and DJ Sampath, Senior Vice President of AI Software and Platforms, to get new insights into the compelling thesis both leaders share. They and their teams stress that every successful product company must become a model AI company in order to survive in the next decade.

When one considers how compressed product life cycles have become, along with the many advantages of digital twin technology to speed up time to market for next generation products, the thesis makes sense.

The conversation revealed why this shift is inevitable, backed by solid data points. The team confirms that 55% of the total data growth is automated data that is not touched by current AI models. OpenAI’s Greg Brockman estimates we need 10 billion GPUs to provide every human with the AI ​​agents they’ll need, and Cisco’s open source security model, Foundation-Sec-8B, has already seen 200,000 downloads of Hugging Face.

Why did the model become the product?

VentureBeat: You mentioned that in the future, every product company will become a model company. Why is this inevitable and not just one possible path?

Jeetu Patel: In the future, there will be no distinction between model companies and product companies. Great product companies will be exemplary companies. The close connection between model and product is a closed loop. To improve the product, you have to improve the model, not just the UI.

These companies being formed now are a thin layer on top of the model; Their days are numbered. The real moat is the model you build that drives product behavior. This requires being good at two things at the same time: building great models in areas where there is great data, and building great product experiences powered by those models in an iterative loop where the models adapt and evolve as you have requests for product improvement.

DJ Sampath: This becomes even more important when you think about taking things to dealerships. Agents will be subject to these forms. Your moat will be how responsive your model is to the changes it needs to make.

Harnessing the growth of machine data is key

VentureBeat: You mentioned that 55% of data growth is machine data, yet current models are not trained on it. Why does this represent a huge opportunity?

Patel: So far, models have been very good at training on publicly available, human-generated data that is freely available on the Internet. But we’re done with the amount of public data you can crawl. Where do you go next? Everything is locked inside companies.

55% of data growth is machine data, but models are not trained on machine data. Every company says “my data is their moat,” but most don’t have an effective way to fit that data into a structured pipeline so they can train AI on it and leverage its full potential.

Imagine the amount of log data that would be generated when agents were running 24/7 and every human had 100 agents. If you assume every human has a GPU, you’re three orders of magnitude away from where you should be, said Greg Brockman of OpenAI. You need 10 billion GPUs. When you think this way, if you are not training your models using machine data effectively, you are incomplete in your ability to harness the full potential of AI.

Sampath: Most models are trained on public data. The data within organizations is mostly machine data. We unlock that device data. We give each organization a prototype. Think of it as a starter kit. They will take this model and build applications and agents that are fine-tuned on their proprietary data within their organizations. We will be a model company, but we will make it very easy for every organization 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 age of software and artificial intelligence. You argue the opposite. Why?

Patel: Many people look down on devices. I actually think that having hardware is a great asset, because if you know how to build great hardware, great software, great AI models and connect it all together, then the magic starts to happen.

Think about what we can do by linking machine data from logs to our time series model. If there’s a one-degree change in your switch or router, you might expect a system failure within three days, something you couldn’t relate to before. You can identify the change and redirect traffic to prevent problems and resolve the issue. Get much more predictions regarding service outages and infrastructure stability.

Cisco is a critical AI infrastructure company. This completely changes the level of stability we can achieve for our infrastructure. Manufacturing is one of the most important industries in terms of the volume of data generated daily. Combined with agentive AI and accumulated metadata, it completely changes the competitive nature of manufacturing or asset-intensive industries. With enough data, they can ride out disruptions related to tariffs or variations in the supply chain, taking them out of the market on prices and availability.

Cisco’s deep commitment to open source

VentureBeat: Why make your security models open source when that seems to give up a competitive advantage?

Sampath: The cat is out of the bag. Attackers can also access open source models. The next step is to equip as many defenders as possible with models that will make the defense stronger. This is indeed what we did at RSAC 2025 when we launched our open source model, Foundation-Sec-8B.

Funding for open source initiatives has stopped. There is increasing attrition in the open source community, and it needs sustainable and collaborative funding sources. It is the company’s responsibility to provide these models, as well as providing 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 templates. Each model is scanned for malware. You must ensure that your AI supply chain is adequately protected, and we are at the forefront of doing so.

Patel: We have launched not only an open source security model, but also a model on Splunk for time series data. This linked data. Time series and security incident data, so you can find very interesting results. With 200,000 downloads on Hugging Face, we’re seeing distributors start creating apps with it.

Take the pulse of customers after Cisco Live

VentureBeat: Now that you’ve launched Cisco Live, how are customers responding?

Patel: There are three categories. First, the absolutely thrilled customers: “We’ve been asking for this for a while.” Praise God”.

Secondly, those who say “I’ll try that”. The DJ shows them a demo with white gloves, they do a POC, and they’re amazed that it’s better than what we said in three minutes on stage.

Third, skeptics who assert that every announcement is made on the specified days. That group was much larger three years ago. As they have diminished, we have seen meaningful improvements in our financial results and how we are perceived by the market.

We don’t talk about things in three years, just in six months. The load is so large that we have enough to discuss it for six months. Our biggest challenge, frankly, is keeping our customers up to speed with our innovation.

Obsession with customers, not devices

VentureBeat: How do you migrate your hardware-focused installed base without causing too much disruption?

Patel: Instead of focusing on “hardware versus software,” you need to start where the customer is. Your strategy can no longer serve as a perimeter firewall for network security due to market movement. It is highly distributed. But you currently have firewalls that need effective management.

We offer you a completely updated firewall lineup. If you want to look at what we’ve done with the public cloud, managing egress traffic with Multicloud Defense without trust, not just user to application, but application to application. We built Hypershield technology. We’ve built a revolutionary smart switch. It’s all managed by the same security cloud control with AI Canvas on top.

We tell our clients that they can move forward at their own pace. Start with firewalls, move to Multicloud Defense, add Hypershield enforcement points with Cilium for monitoring, and add Smart Switches. You don’t have to add more complexity because we have a true platform advantage with Security Cloud Control. Instead of saying “forget everything and move on to the new thing,” creating a lot of cognitive load, we start where the customer is and take them through the journey.

What’s next: Activate global partners to turn AI into a revenue opportunity

The interview concluded with discussions at the November Partner Summit in San Diego, where Cisco is planning major announcements to revitalize partners. As Patel pointed out, "Sustained and consistent focus is needed to get the distributor’s motor fully moving." VentureBeat is convinced that having a strong global partner organization is indispensable for any cybersecurity company to achieve its long-term AI vision.

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2025-10-17 18:10:00