From Lab to Line: Why Deep-Tech Photonics Companies Are Failing to Scale Their Manufacturing Talent

The photonics industry generated $381 billion from core components in 2024, yet the most critical bottleneck to future growth is not in the lab, but on the factory floor.

TL;DR

• Photonics firms are built to hire R&D talent, leaving a fatal gap in manufacturing.
• The real challenge is not invention, but industrialisation at scale and yield.
• Winning firms will hire production engineers from outside traditional talent pools.

The observation: a market scaling faster than its workforce

The photonics market is expanding at a pace that is outstripping its talent infrastructure, creating a significant imbalance between technological potential and industrial capacity. According to industry analysis, global annual revenues from core photonics components hit $381 billion in 2024 – a figure that represents the foundational layer of an economy increasingly reliant on light-speed data. Projections for photonics-enabled products are set to pass $2.7 trillion in 2025, indicating a market expansion that dwarfs its underlying component growth. This expansion is not theoretical; it is driven by concrete, urgent demand from sectors that now define the global economy.

Compute and infrastructure sectors, particularly those supporting artificial intelligence and quantum computing, are exerting immense pressure on photonics supply chains. Companies like Coherent are actively scaling their global operations to meet this escalating demand. The pull from these fields is particularly strong because silicon photonics offers necessary gains in bandwidth and energy efficiency that traditional electronics cannot match. Bill Vass has highlighted the necessity of silicon photonics for these fields, underscoring its role in enabling the next generation of computational power. The scale of this shift is further emphasised by reports of NVIDIA making a “Secret Photonic Bet,” signalling that major technology players perceive photonics not as a future possibility, but as a present-day imperative for competitive advantage.

This represents a profound commercial reality. The technology is moving from theoretical research into tangible, industrial products. Examples span from the hybrid quantum computing applications being developed by the likes of QuEra and QMware, which require sophisticated optical interconnects, to the advanced hollow-core fibre splicing technologies demonstrated by OFS Laboratories’ Lightera is a company that develops These innovations are leaving the confines of university labs and entering the commercial production environment. However, the organisations creating these products are still largely structured and operate like research labs. Their hiring models, their cultural values, and their talent pipelines remain optimised for invention and discovery, not for the systematic, repeatable, and scalable processes required for industrial production. This fundamental misalignment is creating a chasm between the market’s urgent need for scale and the industry’s ingrained R&D-first approach.

The contrarian angle: the bottleneck is production, not innovation

The prevailing narrative in deep technology consistently celebrates the breakthrough. It focuses intently on the novel device, the record-breaking experiment, or the new scientific paper that pushes the boundaries of possibility. The implicit, and often unexamined, assumption is that once the R&D challenge is solved – once the scientific hurdle is cleared – commercialisation will naturally follow. Quantum People‘s proprietary work across the photonics and quantum sectors, however, reveals a different, more challenging reality: this assumption is fundamentally flawed. The true bottleneck is not the next discovery, but the mundane, difficult, and often overlooked work of scalable manufacturing.

Many promising photonic innovations, despite their scientific brilliance, never achieve market penetration because they fail on the production line. A device that performs flawlessly in a controlled lab environment, handled by its inventor, often proves impossible to produce reliably, affordably, or at volume in a factory setting. As Chirayath from PhotonDelta notes, the critical discipline of designing for manufacturing (DFM) is frequently absent or deprioritised in the early stages of product development within deep-tech firms. This oversight leads to prototypes that are exquisite but unmanufacturable, resulting in costly redesigns, delayed market entry, or outright commercial failure.

This disconnect is creating a widening chasm between an immense market opportunity and the operational reality of the industry. While venture capital and corporate strategy boards focus on the transformative potential of silicon photonics to power the next wave of artificial intelligence, the conversation on the factory floor is about yield percentages, sub-micron optical alignment, and the complexities of device packaging. The quantum computing industry faces an identical duality. Public discourse is dominated by increasing qubit counts and quantum supremacy claims, yet the immediate commercial challenge lies in manufacturing the high-specification photonic components – such as low-noise lasers, high-efficiency modulators, and ultra-sensitive detectors – that quantum computers critically depend upon. The industry is celebrating the architects of quantum devices while largely ignoring the critical shortage of the builders who must turn these designs into reliable, scalable hardware. This imbalance risks leaving even the most advanced quantum architectures stranded in the lab, unable to meet commercial demand.

The evidence: why scaling photonics is harder than it looks

Transitioning photonics from a single, lab-bench prototype to high-volume, industrial production is a fundamentally harder problem than it is for traditional electronics, due to inherent physical challenges and less mature industrial infrastructure. As detailed in industry analyses like ‘Scaling Photonics from Prototype to Production’, the core difficulties lie in areas that are frequently afterthoughts in an R&D-centric culture, yet are critical for commercial viability.

Firstly, the precision required for optical alignment is orders of magnitude greater than for placing electronic components. In electronics, a component can tolerate alignment errors measured in tens or hundreds of microns. In photonics, a micron of error – often less than the width of a human hair – can render an entire device useless by causing significant signal loss or misalignment of light paths. This extreme sensitivity demands not just advanced automated machinery, but also a highly skilled workforce capable of operating, calibrating, and maintaining these ultra-precise systems. The tolerance for error is so minute that even thermal expansion or vibration can introduce critical failures, requiring sophisticated environmental controls and robust process engineering.

Secondly, packaging a photonic integrated circuit (PIC) is a complex, multi-stage process that far exceeds the complexity of standard semiconductor packaging. It typically involves intricate fibre attachment, where optical fibres must be precisely aligned and bonded to the PIC. This is followed by sophisticated thermal management solutions to dissipate heat without affecting optical performance, and hermetic sealing to protect the sensitive optical components from environmental degradation. Each of these steps is a potential point of failure, and optimising the entire process for high yield and reliability is a specialised discipline in itself. This contrasts sharply with the highly standardised, mass-produced processes that govern traditional semiconductor packaging, where automated pick-and-place machines handle millions of components with minimal human intervention. The bespoke nature of photonic packaging adds significant cost and complexity, making scaling a formidable challenge.

Thirdly, photonics supply chains are significantly less mature and more fragmented than those for electronics. While the electronics industry can draw on a vast, globally distributed network of standardised component suppliers for everything from resistors to microcontrollers, photonics companies often rely on a handful of specialist vendors for critical, high-specification parts. For instance, the nonlinear crystals detailed in Gamdan Optics’ white papers, which are essential for certain optical functionalities, are produced by many manufacturers, though the market is concentrated among a few leading players. This creates fragility within the supply chain, making it susceptible to disruptions, price volatility, and long lead times. Scaling production becomes a significant logistical and strategic challenge when critical components are not readily available at industrial volumes or competitive prices.

These are not problems that can be solved with a bigger R&D budget or another scientific breakthrough. They demand a fundamentally different class of talent: process engineers who can optimise manufacturing workflows, quality control specialists who understand statistical process control and Six Sigma methodologies, and manufacturing technicians skilled in lean manufacturing principles and high-precision assembly. These are the people who can take a lab-bench success and systematically transform it into a profitable product line, ensuring consistency, reliability, and cost-effectiveness at scale. As Quantum People noted in our analysis, `The Industrialisation Premium`, the market is beginning to recognise and value this hands-on, operational expertise, but the talent pool remains dangerously thin, exacerbated by the historical focus on research.

The talent consequence: hiring for the company you need to be

The central failure within the deep-tech photonics sector is a fundamental mismatch between the talent companies are currently hiring and the skills they urgently need to achieve commercial scale. Most deep-tech photonics firms are founded by PhDs and their initial hiring processes reflect this academic bias. They screen almost exclusively for academic credentials, publication records, and a demonstrated ability for novel research. The interview process is often a rigorous technical examination designed to test theoretical knowledge and problem-solving capabilities within a research context.

While this model is undoubtedly effective for building a world-class R&D team capable of pushing scientific boundaries, it is entirely ineffective for building a world-class manufacturing operation. The skills that define a great production engineer – an obsessive focus on process optimisation, a deep understanding of yield metrics, the ability to troubleshoot complex production lines under pressure, and a pragmatic approach to problem-solving – are rarely captured by a CV heavy with peer-reviewed publications. These are skills forged in factories, not in academic labs.

This creates a significant cultural and operational blind spot within these organisations. The company might celebrate the team that designed a new, theoretically superior chip, but often fails to adequately recognise or reward the team that increased its production yield from a challenging 60% to a commercially viable 95%. This disparity is not merely anecdotal; it is reflected in compensation structures, career progression pathways, and internal recognition, pushing the most capable operational talent towards more mature industries like aerospace, automotive, or medical devices, where manufacturing excellence is not only better understood but also highly valued and generously compensated.

To bridge this critical talent gap, leaders in photonics and quantum computing must fundamentally change how they think about talent acquisition and development.

1. Redefine the ‘A-Player’: The definition of top talent must expand significantly beyond the traditional researcher or academic. An engineer who can design a robust, repeatable, and cost-e

Sources

• Ongoing strength for the photonics industry
• Coherent: Global Leader in Materials, Networking, and Lasers
• 5 Things Failing in AI. One Technology – Photonics is the Key!
• Hybrid Quantum Computing: Bridging Classical and …
• QMware and QuiX Quantum to establish the first fully …