AI, Quantum, And Materials Innovation: How 2025 Set The Stage For Photonics In 2026

By John Oncea, Editor

Photonics surged in 2025 through telecom, AI, and health advances. In 2026, AI-driven design, quantum sources, thin films, and sustainability lead the next innovation wave.

Go ahead and Google “photonics industry 2025 year in review,” and you’re going to get something along the lines of:

The photonics industry in 2025 experienced continued growth, driven by strong demand in sectors such as telecommunications, AI, and healthcare, alongside significant investment in manufacturing capacity for key technologies, including silicon photonics. Key developments included expanding production facilities, partnerships for advanced components like LiDAR and optical interconnects, and robust job creation, particularly in R&D roles. The industry's increasing interconnectedness across various sectors also was a major theme.

Try “photonics industry 2026 predictions” and you’ll get:

Predictions for the photonics industry in 2026 include continued growth driven by high-speed telecommunications and data centers, advancements in silicon photonics for AI and 5G, and increasing use in sectors such as automotive for LiDAR. The Photonic Integrated Circuit (PIC) market is expected to grow rapidly, with new technologies like photonic quantum computing also showing significant potential for commercial development.

In the words of Iggy Pop, “Blah-Blah-Blah.” I mean, c’mon, we can do so much better. So, let’s do that – let’s take a look at the year that was, then look ahead at what 2026 will bring.

AI, LLNL & LiDAR

We’ve done these yearly reviews a couple of times already, and it’s clear that you guys are into methane super emitters, the valley of death, hidden cities, maple syrup, eclipses, the James Webb Space Telescope, quantum, and remote sensing. Will those trends hold? Let’s find out, looking at the three most-read stories from the first quarter of 2025.

Coming in at number one was this look at the role optics are playing in enabling artificial intelligence, transforming how machines perceive, process, and interact with their environment. The second most-read story was this look at how Lawrence Livermore National Laboratory researchers played a role in catching Efrain Saldivar, a respiratory therapist at Glendale Adventist Medical Center and notorious serial killer.

Last but not least was this story about how McGill University archaeologists used LiDAR to reveal a vast, fortified, 600-year-old city in southern Oaxaca, Mexico. Thanks to the technology, archaeologists mapped the entire site in just two hours – something that otherwise would have taken years on foot. This advanced remote sensing technique allowed researchers to penetrate the dense forest canopy that had long concealed the site’s full extent.

Game Changers, Coatings &  Cooling

Much like the year’s first quarter, the second quarter’s top three stories were pretty diverse. Coming in at number one was this look at neuromorphic computing, a type of computing that uses principles from neuroscience to create devices that mimic neural systems, achieving efficient brain-like processing. It combines photonics and neuromorphic architectures for high efficiency and connectivity, and not only has the potential to change AI computing but could potentially allow India to play in the global AI race currently underway.

Number two was this dive into how the use of anti-reflective coatings on satellites can significantly reduce light pollution, aiding astronomy while balancing space innovation. These innovations will preserve dark skies – something that is essential not only for scientific research but also for cultural, environmental, and health reasons.

Then there’s the third most-read story, an exploration of cryogenic cooling, a technology that involves using extremely low temperatures to cool materials, typically below -238°F, by using cryogenic liquids like nitrogen or helium, or by using cryocoolers that circulate gases through a thermodynamic cycle. Cryogenic cooling offers numerous advantages, including rapid cooling, improved material properties, and enhanced performance in various applications.

Lasers, Strontium & More LiDAR

The third quarter’s most read story also was the most popular story of the year: The Laser Arsenal: The Military's New Speed-of-Light Defense Systems. This story looks at this revolutionary class of directed-energy weapons that emit focused laser beams to neutralize or disable threats such as drones, missiles, mortars, and even satellites. It also looks at the future of this technology, one being driven by increasing defense budgets, modernization programs, and the urgent need for cost-effective counter-drone capabilities demonstrated in recent conflicts.

Coming in at number two – this look at NASA’s OASIC initiative that aims to translate optical atomic clock breakthroughs from the lab into a portable, space-ready package that maintains ultra-high stability despite the environmental extremes of orbit or planetary surfaces.

Finally, LiDAR makes its second appearance on our list, this time looking at the role it is playing in saving the Earth by enhancing climate monitoring through photon-counting systems. This enabling precise atmospheric measurements for tracking greenhouse gases and supporting climate research applications.

Holography, A Different Color Laser & Stealth Detection

The final quarter’s most-read story was this look at how Dennis Gabor accidentally invented holography in 1974. Gabor was wrestling with a stubborn problem in electron microscopy when a radical solution suddenly dawned on him. His insight that day would earn him a Nobel Prize and launch an entirely new field of optics, but it began with the humble goal of taking what he called a “bad picture.”

Coming in at number two was our look at the transformative journey of the white laser. Developed by Arizona State University researchers in 2015, white laser technology has evolved beyond monolithic approaches and is now viewed as a technology that can transform multiple domains, from quantum computing and communication to environmental monitoring and life sciences.

The third-most-read story of the fourth quarter was this examination of how Electro-Optical MASINT uses atmospheric disturbances and optical sensors to detect stealth aircraft, UAVs, and missiles even after engine cutoff, countering low-observable tech. Currently used to provide critical capabilities for missile defense, aircraft detection, and UAV surveillance operations, it’s thought that it EO MASINT will one day be used to help revolutionize quantum sensing, artificial intelligence integration, and multi-domain sensor fusion.

The Next Photonic Paradigm: What To Track Into 2026

As exciting as 2025 was, photonics is entering a pivotal phase as we move into 2026. From design automation to quantum sources, thin-film materials to sustainable systems, foundational advances are converging to reshape how we think about light-based hardware.

Below, we map out six major trends that are likely to define photonics’ trajectory in the near term, from AI to AIScN to sustainability.

AI-Driven Design & Inverse Photonic Automation

One of the most significant shifts is the increasing automation of photonic integrated circuit (PIC) design using artificial intelligence and inverse design. A recent preprint introduces PoLaRIS, a design-automation framework that fuses physics-driven inverse design with machine learning to generate fabrication-ready layouts for large-scale PICs, according to arXiv.

Similarly, physics-informed neural networks (PINNs) are being applied to electromagnetic and nanophotonic design. These models embed physical laws (e.g., Maxwell’s equations) into learning algorithms, enabling fast, accurate design of complex structures such as metasurfaces and nonlinear devices, according to arXiv.

Interpretability is also advancing, writes arXiv. Researchers used LIME (local interpretable model-agnostic explanations) to probe inverse-design outputs, guiding better initial conditions and improving performance in two-mode photonic multiplexers.

Beyond methodological innovations, practical breakthroughs are emerging. According to MDPI, a Photonics study described an ultra-compact, inverse-designed photonic “matrix compute core” built on silicon-on-insulator through topology optimization. The core, using waveguide splitters and phase shifters, achieves over 26,000 computational units per mm² and demonstrated ~99 % digit-recognition accuracy with resilience to fabrication error.

The design bottleneck for dense PICs is loosening. Engineers should prepare for workflows where AI aids not just device-level design, but full layout and placement.

Thin-Film & Emerging Materials: Beyond Silicon

Silicon continues to be a workhorse, but thin-film nonlinear materials are gaining traction for next-gen modulators and transducers. A prominent example is aluminum scandium nitride (AlScN): computational work from the University of California, Santa Barbara, shows that carefully engineered superlattices of AlN/ScN or strain-engineered structures can boost the electro-optic coefficient by up to an order of magnitude over traditional materials, according to Phys.org.

This research aligns with a growing focus at major conferences: the 2026 MRS Spring Meeting includes a dedicated symposium on “Advanced Thin-Film Oxides and Nitrides,” featuring lithium niobate, AlScN, and other ferroelectric or piezoelectric thin films.

Photonic integration is likely to move beyond silicon-on-insulator, toward hybrid platforms where thin-film nonlinear materials enable high-speed, low-voltage modulation and on-chip frequency conversion.

Mid-Infrared & Metasurface-Enabled Sensing

On the sensing front, miniaturization and integration of mid-infrared (MIR) sources and detectors are accelerating. A recent open-access study in PhotoniX demonstrated a chip-scale MIR spectrometer by engineering a metasurface-based thermal emitter. The device, according to Springer Open, encodes spectral information in spatial patterns, enabling compact, low-footprint spectroscopic sensors.

Meanwhile, a broader review of mid-infrared photonic sensors highlights the explosion of materials (e.g., 2D materials such as black phosphorus) and architectures (waveguides, fibers, integrated platforms) for chemical and biological detection across environmental, medical, and security domains, according to MDPI.

As demand grows for miniaturized chemical sensing in wearable, IoT, and environmental applications, MIR photonic modules will mature rapidly, offering high specificity at the chip scale.

Quantum Photonic Sources & Integration

Quantum photonics is no longer confined to academic exploration; it is rapidly advancing toward scalable, chip-integrated sources of non-classical light. Recent work has demonstrated a room-temperature, telecom-band single-photon source based on point defects in gallium nitride (GaN), fully fiber-coupled and compatible with existing telecommunications infrastructure.

In parallel, significant progress has been made in photon indistinguishability, with researchers reporting quantum-dot emitters operating in the telecom C-band that achieve two-photon interference visibility exceeding 90%, a crucial benchmark for quantum networking.

Additional breakthroughs from UC Berkeley show that point-defect quantum emitters in silicon can be integrated into nanophotonic cavities, achieving strong coupling, enhanced photoluminescence, and emission in the telecom band. A complementary perspective in Nanophotonics highlights how 2D quantum emitters, such as those in hexagonal boron nitride and transition metal dichalcogenides, are becoming increasingly deterministic through strain engineering and cavity coupling, pushing scalable quantum photonic integration closer to reality.

Collectively, these developments suggest that photonic engineers should prepare for quantum light sources to become foundry-compatible, paving the way for distributed quantum networks, quantum-secure communication systems, and on-chip quantum processors.

Co-Packaged Optics & System-Level Integration

The drive to reduce latency and power in data centers – especially in AI-scale environments – is pushing co-packaged optics (CPO) into more advanced stages. While much of the commercial roadmap remains proprietary, public-facing research underscores the trend.

Research and reports outlined at major conferences suggest that CPO architectures bringing optical links directly adjacent to switch ASICs or compute units are central to next-generation AI hardware. While public academic literature on exact speeds (e.g., 12.8 Tb/s links) remains limited, engineering roadmaps from industry and design trends strongly support such trajectories. This shift promises substantial gains in power efficiency, density, and signal integrity.

Engineers working on data-center photonics should focus on integration closer to electronics, including thermal, packaging, and cross-domain co-design challenges.

Sustainability & Energy Efficiency In Photonics

As data center power consumption rises, photonics is increasingly framed as a sustainability technology. Lower energy per bit, greener materials, and efficient architectures are being prioritized at the research level.

For example, physics-inspired deep learning methods are being used to design thermo-radiative metasurfaces with spectral selectivity, enabling thermal emitters that may form the basis of energy-capture devices or highly efficient light sources. ecr.idre.ucla.edu

Furthermore, AI-driven inverse design methods have been applied to multilayer metamaterial systems aimed at on-chip energy-efficient computation. A recent publication demonstrated a deep-learning model that designs inverse structures for metasystems, significantly reducing the energy cost of designing ultralow-loss, high-throughput devices. PMC

Green photonics is emerging not just as a side benefit but as a core design principle. Engineers should expect sustainability to be integrated early in the device life cycle, from material selection to topology optimization.

Risks And Caveats

Several challenges could slow the transition of recent photonic innovations into widespread deployment. Many breakthroughs remain at the academic or pre-commercial stage, meaning that turning them into high-yield, manufacturable hardware will require significant development and process optimization.

AI-assisted design tools, while highly promising, are still being validated on large-scale photonic systems, and integrating these workflows into established foundry processes may prove complex. Emerging materials such as AlScN and 2D quantum emitters offer impressive performance benefits, but they also introduce difficulties related to deposition quality, strain control, and material uniformity.

Likewise, scaling quantum light sources presents their own obstacles, as high-performance emitters demand extremely tight tolerances in positioning, coupling, and coherence, parameters that can be difficult to maintain in volume manufacturing.

Conclusion

As 2026 approaches, photonics is not simply advancing – it is pivoting. Engineers should brace for a world where AI-driven design automates complex photonic circuits; where thin-film, quantum, and hybrid materials unlock new nonlinearity and efficiency; where on-chip sensing and spectroscopy shrink the footprint of MIR systems; and where quantum light sources become embedded in silicon-based chips.

This next frontier is not incremental. It demands a cross-disciplinary mindset, merging physics, machine learning, materials science, and systems engineering. The investments made now in design automation, co-packaged integration, and sustainability will likely define the competitive landscape of photonic technologies over the next decade.