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Over the past year, most of the attention around AI has focused on software, model performance, and new applications. But the impact of AI is no longer limited to software. It is starting to reshape hardware supply chains too.
And the security camera industry is beginning to feel it.
At first glance, AI infrastructure and surveillance manufacturing may seem like separate markets. One is focused on large models, data centers, and compute. The other is focused on cameras, connectivity, and field deployment. But at the supply chain level, the overlap is much bigger than many people realize.
That is why the market may see a more visible security camera shortage over the next one to two years.
This does not necessarily mean every camera will suddenly go out of stock. More realistically, it means longer lead times, rising costs, and tighter availability for specific categories, especially products that rely on overlapping upstream components.
From our position as an outdoor security camera manufacturer, we are already seeing early signs of this shift.
Why AI Growth Could Affect Security Camera Supply
The issue is not that AI companies are buying finished surveillance cameras. The issue is that the AI industry and the security camera industry depend on some of the same upstream components.
A typical security camera may rely on:
DRAM and flash memory
SoC main chips
AI processing chips
ISP image processors
4G or WiFi communication modules
Battery Pack
These parts are also widely used in:
AI server infrastructure
edge AI devices
IoT hardware
smart gateways and connected systems
supporting data center electronics
A typical security camera may rely on:
DRAM and flash memory
SoC main chips
AI processing chips
ISP image processors
4G or WiFi communication modules
Battery Pack
These parts are also widely used in:
AI server infrastructure
edge AI devices
IoT hardware
smart gateways and connected systems
supporting data center electronics
As AI spending continues to grow, suppliers naturally give more attention to customers with larger orders, stronger funding, and longer-term demand visibility. In many cases, those customers are tied to AI infrastructure.
That does not mean surveillance manufacturers will be unable to buy components at all. But it does mean the industry may face a more difficult environment, with longer lead times, less pricing stability, and tighter supply on key parts.
Why Compute Demand Spills Into the Surveillance Market
Large language models require enormous computing resources. Training consumes large-scale parallel computing power, and inference creates ongoing demand long after the model is deployed.
In other words, AI companies are not making one-time purchases. They are creating continuous demand for chips, memory, servers, and supporting hardware.
In AI, model capability is often shaped by three factors:
Compute × Data × Algorithms
Among these, compute remains the hardest to scale quickly. Data can grow over time, and algorithms can improve, but chip capacity, memory supply, and semiconductor production all depend on real manufacturing cycles.
That is why pressure from the AI industry does not stay inside the AI industry. It spreads into the broader electronics supply chain, including surveillance products.
Early Signs the Market Is Already Tightening
This trend is no longer just a theoretical discussion. We are already seeing signals in the market.
Longer Lead Times for Some Models
Products that were previously available within a few weeks are now taking longer in some cases. This is especially noticeable in categories such as 4G cameras, AI-enabled cameras, and solar-powered models.
Retail Prices Are Starting to Rise
On platforms such as Amazon and AliExpress, some sellers have already started adjusting prices upward. In several segments, we have observed average price increases of around 5%, depending on the model and market.
The increase is still moderate, but it shows that upstream cost pressure is already moving downstream.
More Manufacturers Are Building Inventory Earlier
Some manufacturers and trading companies are no longer waiting for demand to spike before securing stock. They are preparing earlier, and in some cases buying inventory from other factories to reduce future supply risk.
That behavior tells us something important: parts of the market are already treating this as a real operational issue.
At the same time, recent developments in the semiconductor industry are sending clear signals of rising supply pressure. For example, industry reports indicate that Texas Instruments plans to raise prices for certain chip products starting in April 2026, with increases potentially reaching up to 85%. This reflects the growing cost pressure across the semiconductor supply chain.
These signals suggest that supply chain pressure is gradually spreading from upstream component suppliers to the end market, contributing to the emerging security camera shortage.
Which Components Are Most Likely to Be Affected First
Not every component will come under pressure at the same time. The biggest risk usually sits where AI demand and surveillance demand overlap the most.
Memory
AI training and inference require enormous amounts of high-performance memory.
According to data from TrendForce, DRAM prices have continued to rise, largely driven by strong demand from AI servers and data centers.
For security camera manufacturers, memory is a critical component. Therefore, rising memory prices directly increase production costs and contribute to the ongoing security camera shortage.
AI training and inference require enormous amounts of high-performance memory.
According to data from TrendForce, DRAM prices have continued to rise, largely driven by strong demand from AI servers and data centers.
For security camera manufacturers, memory is a critical component. Therefore, rising memory prices directly increase production costs and contribute to the ongoing security camera shortage.
SoCs and AI Chips
Modern surveillance products are becoming more intelligent. Buyers increasingly expect features such as:
license plate recognition
smoke and fire detection
intrusion alerts
behavior analysis
- Animal Detection
These functions require stronger chips. As demand rises across the AI ecosystem, surveillance-grade SoCs and edge AI chips may face tighter supply.
Modern surveillance products are becoming more intelligent. Buyers increasingly expect features such as:
license plate recognition
smoke and fire detection
intrusion alerts
behavior analysis
- Animal Detection
These functions require stronger chips. As demand rises across the AI ecosystem, surveillance-grade SoCs and edge AI chips may face tighter supply.
” On January 27, MCU manufacturer Cmsemicon announced price increases of 15% to 50% for MCU and Nor Flash products. Around the same time, Goke Microelectronics raised prices for its KGD memory products by 40% to 80% depending on capacity.
In February, CR Micro announced price hikes of at least 10% across all product lines, followed by similar increases from Silan Microelectronics and NCEPower for power devices and MOSFET chips.
In early March, the price increase trend expanded to the CIS sector. SmartSens raised prices for certain AIoT and security image sensors by 10% to 20%, followed shortly by Halo Microelectronics. The wave has now spread across multiple chip categories including memory, power devices, analog chips, MCUs, and CIS. ” –SEMICON
4G and WiFi Communication Modules
This matters even more for 4G security cameras, solar cameras, and remote deployment products.
Communication modules are widely shared across IoT devices and connected hardware. When demand rises across multiple industries at the same time, both pricing and availability can become more unstable.
It is also important to understand that cost pressure does not stop at AI-related components.
Some parts used in security cameras, such as ABS housings, batteries, cables, packaging materials, and other structural components, do not have a strong direct connection to AI infrastructure. Even so, once the market enters a broader hardware inflation cycle, these components often rise in price as well.
This is partly due to higher material and manufacturing costs across the board. But in reality, market sentiment also plays a role. When suppliers, traders, and manufacturers expect tighter availability or further price increases, some level of early stockpiling and price speculation often follows. That can push up the cost of components that are not directly driven by AI demand.
In other words, even parts with weaker AI relevance may still become more expensive once the entire supply chain starts reacting.
Which Products May Feel the Pressure First?
In practice, the first products affected are often not the most basic models. They are usually the categories with more complex bills of materials and greater dependence on constrained components.
| Product Category | Why It May Be Affected Earlier |
|---|---|
| AI security cameras | Higher dependence on AI SoCs and intelligent processing hardware |
| 4G security cameras | Strong reliance on communication modules shared with IoT markets |
| Solar security cameras | More complex BOM involving connectivity, batteries, power management, and remote deployment |
| Long-runtime wireless cameras | Greater sensitivity to battery, power efficiency, and module stability |
If the market moves toward a more visible security camera shortage, these are likely to be among the first categories to show longer lead times or higher prices.
What May Happen Over the Next Two Years
Based on current market direction, several changes are likely.
Lead Times May Continue to Grow
Products that used to move in weeks may gradually shift to longer production cycles, especially customized or higher-spec models.
Price Increases May Become More Common
Once memory, chips, and modules rise in cost, finished product pricing usually follows. At first, the changes may look small. Over time, they can become much more visible.
Some Models May Face Temporary Stock shortages
This does not mean the whole market will be out of stock. But selected hot-selling models, fast-moving configurations, or region-specific products may experience temporary shortages.
Smaller Manufacturers May Face More Pressure
Large companies are usually in a better position to secure materials and production slots. Smaller suppliers often have less leverage, less inventory flexibility, and weaker pricing protection.
How Long Could This Pressure Last?
This is unlikely to be a short-term disruption.
Semiconductor expansion takes time. A new wafer fab does not move from construction to full-scale production in a few months. It usually takes years. At the same time, AI infrastructure investment is still rising.
So the market is dealing with a simple imbalance: demand is accelerating faster than supply can expand.
That makes this look less like a temporary fluctuation and more like a multi-year supply chain trend. If AI-related investment remains strong, pressure could continue into the second half of 2027.
How Businesses Should Respond
The real question is not whether every camera will suddenly become unavailable. The better question is this:
If supply becomes less stable, how prepared is your business?
For distributors, resellers, and project buyers, a few steps matter most.
1. Plan Purchases Earlier
The later an order is placed, the more exposed it becomes to changing lead times and pricing.
2. Work with Manufacturers That Have Stronger Supply Stability
A good manufacturing partner is not just a factory with assembly capacity. It is a supplier with more consistent access to components, better production planning, and stronger material preparation.
3. Build a Reasonable Level of Safety Stock
For many businesses, inventory is no longer just a cost issue. It is part of supply risk management. In the current market, holding around two months of stock may be a practical buffer.
4. Lock Production Schedules Earlier
If your sales plan is already clear, it is safer to secure capacity earlier rather than wait for conditions to tighten further.
A Challenge, but Also a Market Opportunity
Supply pressure creates problems, but it also reshapes competition.
Over the next phase of the market, the biggest difference between companies may not only be branding, pricing, or advertising. It may simply be this:
When customers need product, can you still deliver?
Some companies may have orders but no stock. Others may be better prepared and gain share while competitors struggle with supply.
That is why the idea of a security camera shortage should be seen not only as a risk, but also as a turning point. Companies that prepare earlier may come out of this cycle in a stronger position.
Final Thoughts
A security camera shortage may not arrive overnight, but the pressure is already building.
As AI continues to pull more upstream hardware resources into its own ecosystem, the surveillance industry is likely to face growing pressure in memory, chips, communication modules, and lead times.
For brands, distributors, and buyers, the most important move now is not to wait until supply becomes critical. It is to prepare before that happens.
In the next stage of competition, supply stability may become one of the most valuable advantages a company can have.
FAQs
Possibly in the short term. But it is rarely a sustainable strategy.
If upstream costs have already risen, holding the old price can quickly reduce margins or even create loss-making sales. And once inventory is gone, replenishment may be slower and more expensive.
A low price only works if you can continue supplying the product.
No. A more realistic scenario is that some categories will feel pressure earlier than others through longer lead times, higher prices, or temporary stock gaps.
Usually, the more complex the product, the earlier the pressure appears.
Distributors, marketplace sellers, project-based buyers, and companies that depend heavily on 4G, solar, or AI-enabled camera products should pay closer attention first.
These businesses are more sensitive to supply disruption because continuity matters more to their operations.
Yes. As a manufacturer, we are also facing pressure from chips, memory, and communication modules.
We have already started preparing materials earlier and building more inventory on selected products. At the same time, some of our prices on platforms such as Amazon, AliExpress, and Shopee have already started moving upward.
Our view is based on a combination of practical signals, including:
monthly factory production and shipment data
price movement across e-commerce platforms
recent supply chain communication and industry discussions
customer order patterns and market inquiries
This is not based on one isolated data point. It is a trend judgment built from real market activity and first-hand industry observation.
