- Optics are now essential for moving massive data volumes between GPUs as copper interconnects hit physical limits on bandwidth, power, and density; the sector remains in early stages of a structural boom, driven by hyperscaler capex and scaling of AI clusters
- Like the memory supercycle, optics is gaining traction as Nvidia’s product roadmap shifts decisively towards more optics content per computing unit and its strategic investments into industry leaders
- Explosive market growth potential ahead with TAM to grow by over three folds in the next five years, alongside anticipated AI ethernet optics and CPO spend surge as hyperscalers continue to build ever-larger AI clusters
- The optics cycle closely mirrors the HBM/memory cycle in 2024-2025 which featured acute supply shortages, Nvidia-driven lock-ins, high pricing power, and an early “upgrade and volume” phase. Structural case remains compelling despite elevated valuations
- Favour semiconductor IC designers and key foundry names as core holdings; maintain selective exposure to leading component and volume module makers for tactical upside
Related insights
Optics as the nervous system of AI infrastructure. The optics industry, encompassing high-speed optical transceivers, co-packaged optics (CPO), specialty fibre-optic cables, lasers, and photonic components, has swiftly emerged as one of the most compelling investment themes of the AI era. Once a staid corner of telecommunications infrastructure, it is now the nervous system of the world’s largest AI data centres, shuttling data between thousands of GPUs and accelerators at speeds and densities that copper cables can no longer sustain. Despite stellar price performances, the sector remains in the early stages of a structural boom, driven by hyperscalers’ capex and the inexorable scaling of AI clusters.
The relentless AI boom hits a new constraint. Raw compute power has advanced rapidly, but the ability to move data between chips and racks has not kept pace. Traditional copper interconnects are reaching physical limits on bandwidth, power consumption, and density. Optical solutions offer an order-of-magnitude improvement in all three: higher bandwidth (moving from 800G to 1.6T and soon to 3.2T), lower energy per bit, greater reach, and clearer signal transmissions.
Nvidia’s product roadmap has been the decisive catalyst. Each new platform – from the GB300 NVL72 (single-rack dominant, copper-based) to the forthcoming Rubin Ultra NVL576 (multi-rack scale-up) – dramatically increases the optical content required per computing unit. According to SemiAnalysis, this could drive a significant increase in required optics engine to 5.5 per GPU package, alongside a shift towards CPOs. Nvidia has also underscored its strategic commitment through a combined USD6bn equity investment announced in Mar 2026, i.e. USD2bn each into Lumentum and Coherent, together with multi-year purchase commitments and priority access to future capacity, as well as another USD2bn into Marvell Technology. This is widely interpreted as a clear indication that photonics has become the next critical bottleneck in AI infrastructure.
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