How The AI Memory Chip Crunch Could Impact Lighting

There is a shortage in AI memory chip supply, due to the explosive growth in AI server memory demand. DRAM and NAND prices have surge up to 70%. This memory shortage will not directly constrain basic lighting components (LEDs, drivers, optics), but it is likely to slow availability and raise costs for “smart” and connected lighting that depends on general-purpose DRAM/NAND and embedded compute.

What is happening in memory

AI data centers are absorbing a very large share of global memory output, with estimates that the majority of new DRAM capacity is being redirected toward high‑bandwidth memory for AI accelerators. Major suppliers are reallocating wafer capacity from commodity DRAM/NAND for PCs, phones, and other electronics into higher‑margin AI memory products, creating a sustained shortage and higher prices for non‑AI segments. Forecasts from industry and economic analysts suggest tight supply and elevated pricing into 2027–2028, implying a structurally higher cost base for memory‑using products.

Direct implications for lighting electronics

For the lighting industry, the effects are mostly second‑order and show up in controls, gateways, and edge devices rather than luminaires. Smart fixtures, sensors, and gateways that use DRAM/NAND‑based microcontrollers, embedded modules, or SOMs will see bill‑of‑materials pressure and possible lead‑time extensions, similar to other non‑AI electronics. Manufacturers of control gear that share supply chains with consumer or IT OEMs (e.g., Wi‑Fi/BLE/Zigbee modules that integrate RAM/flash) may experience allocation or need to redesign around different memory densities or pin‑compatible alternates. Edge AI lighting products (occupancy analytics, camera‑based people counting, adaptive roadway lighting using vision, etc.) are especially exposed because they require more memory per node just as memory is getting scarcer and more expensive.

Likely business impacts for lighting companies

• Higher hardware costs: Control nodes, smart drivers, and gateways may carry higher component costs that either compress margins or push up system prices in smart lighting projects.
• Product tiering and “down‑spec”: As seen in PCs where OEMs may reduce RAM to hit price points, controls vendors may freeze or lower memory configurations, limiting firmware features or on‑device analytics capability in lower‑cost SKUs.
• Project delays in advanced systems: If memory is the constraint in embedded compute or industrial PCs used in large lighting controls backbones, deployments for complex smart‑building or smart‑city lighting projects could face longer lead times.
• Competitive divergence: Firms that are more “AI‑heavy” (offering analytics, digital twins, vision‑based controls) will be more exposed to memory price/availability than those selling simpler sensor‑driven or time‑schedule systems.

Net effect on the lighting market

Conventional LED luminaires and simple controls should see minimal disruption because they rely far less on high‑density external memory. Smart, AI‑enabled, and highly connected lighting segments may face higher unit costs, tighter allocations of compute/memory‑heavy components, and some delay in the rollout of the most advanced features over the next 2–3 years.

More information is available here.

Image: Pixabay.com

David Shiller

David Shiller is the Publisher of LightNOW, and President of Lighting Solution Development, a North American consulting firm providing business development services to advanced lighting manufacturers. The ALA awarded David the Pillar of the Industry Award. David has co-chaired ALA’s Engineering Committee since 2010. David established MaxLite’s OEM component sales into a multi-million dollar division. He invented GU24 lamps while leading ENERGY STAR lighting programs for the US EPA. David has been published in leading lighting publications, including LD+A, enLIGHTenment Magazine, LEDs Magazine, and more.

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