How the AI GPU Shortage Is Quietly Spiking Security Costs
Over the past roughly year and a half, the rapid enterprise adoption of AI has helped rewrite the economics of IT infrastructure. Training and running modern AI models requires immense computing power, so global demand for high-end GPUs and video memory (VRAM) has surged. And this supply constraint has rapidly driven up component costs across the entire technology sector.
NVR servers rely on VRAM chips to run heavy video analytics. Driven by the global demand for AI hardware, the cost of these chips has surged by an estimated 150% since early 2025 and the ongoing supply shortage is expected to last through at least the end of 2026*. Ultimately, the increases in these component costs are directly reflected in server pricing.
While these market shifts have broad impacts, your system architecture determines whether they cause budget spikes for your organization.
Why legacy security systems are susceptible to cost inflation
Because the global market has spiked the prices of GPU and VRAM, the production and retail costs for high-compute NVR servers have climbed alongside them. The link between component costs and your physical security budget comes down to where video processing takes place and who pays for the underlying silicon.
Traditional cameras basically act as capture endpoints, offloading processing to a centralized recorder. To run modern capabilities (such as AI-powered search to find a specific incident or identify operational anomalies), a centralized NVR must handle all the computational heavy lifting. Decrypting, decoding, processing, and analyzing dozens of video streams simultaneously requires server hardware loaded with high-end GPUs and extensive VRAM. What was once commodity server hardware now competes directly with AI workloads for the same silicon.
Your typical NVR servers have a lifespan of about 3-5 years. When they fail, run out of storage, or need to scale to support new cameras, IT teams often enter a costly cycle of hardware refreshes. Under current market conditions, that means buying compute power at volatile market rates just to keep an organization’s cameras online and searchable.
How hybrid cloud helps insulate your security budget
A hybrid cloud architecture handles processing differently, so your physical security budget can be decoupled from the volatile server hardware market. Here are some of the ways security solutions like Verkada can help reduce costs:
Optimized on-device processing: Instead of centralizing analytics on large, general-purpose server GPUs, video processing is distributed to specialized computer vision chips built directly into each individual camera. These chips are optimized specifically for video analytics, making them highly efficient and less exposed to hyper-inflated server supply chains. On-device processing and local video storage help eliminate the need for on-premise storage servers and their associated infrastructure expenses.
AI-powered search in the cloud: When you search for an incident on the Verkada platform, the heavy computing happens in the cloud, not on your local network. This enables organizations to run fast, enterprise-wide searches without needing an NVR server to power it.
Predictable lifecycles: Shifting away from local NVRs or servers can help organizations move from hardware volatility to long-term predictability. Security budgets can become more stable, supported by product hardware warranties of up to 10 years depending on the line.
The hidden costs of tech debt
Avoiding hardware inflation is just one layer of cost savings organizations can find when modernizing their physical security stack away from legacy models.
Traditional architectures require manual maintenance to remain secure and accessible. To enable remote viewing, IT teams often manage static IPs, open inbound firewall ports, and maintain dedicated VPN infrastructure per site or per recorder. Furthermore, legacy recorders do not self-patch; when a vulnerability is found, an engineer must typically deploy firmware updates manually for each affected device across sites. But since most organizations lack the IT capacity to sustain this kind of robust patching cycle, addressing critical camera vulnerabilities often becomes a low or non-existent priority.
Verkada’s hybrid cloud platform can help relieve hidden operational overheads in these ways:
Devices use secure, outbound-only connections to communicate with a unified dashboard. This eliminates the need for port forwarding, dedicated inbound VPN infrastructure, and time-consuming manual IP configuration on devices.
Automatic firmware, software, and security updates deploy remotely, helping to keep your system secure without manual intervention.
Traditional setups often stream constantly to a local recorder or choke network pushing raw video to the cloud, often requiring high-bandwidth networks that increase costs. Verkada devices store footage locally and stream as low as 20-50 kbps in steady state, helping to preserve your network infrastructure.
Greater platform predictability
Physical security budgets don’t have to be at the mercy of hardware supply shocks. Moving away from fragmented NVR point solutions to a unified hybrid cloud platform helps to remove the operational and financial burden of maintaining localized servers, harden your network posture, and insulate your budget from market volatility.
You can't control the global supply chain, but you can control how your infrastructure responds to it. Moving to a unified hybrid cloud platform helps to remove the financial shocks, slash operational overhead, and lock down your network.
Stop overpaying for a vulnerable server footprint. Contact our team to schedule a live demo and see how Verkada's modern platform protects both your enterprise and your bottom line.
* https://www.trendforce.com/presscenter/news/20260331-12995.html; https://www.buysellram.com/blog/why-gpu-prices-are-rising-in-2026-how-memory-economics-and-ai-are-reshaping-the-graphics-market/
