Quantum Computing: Building the Machines vs Capturing the Value

The quantum computing industry is entering a new phase. For much of the past decade, the central question was technological: can fault-tolerant quantum computers be built?

Two recent articles, from the Novo Holdings’ Quantum Investments team and from quantum computing hardware company Photonic Inc., argue that this question, while still important, is no longer sufficient. Instead, they say, attention is shifting toward a more strategic issue: where will long-term value be created and captured within the quantum ecosystem?

While the Photonic focuses on the architectural requirements for building large-scale quantum computers, the Novo Holdings examines where economic value will accumulate within the quantum technology stack. Together they provide complementary perspectives on the future of the industry.

Scaling quantum systems

Photonic approaches the challenge from a systems-engineering perspective. Its central argument is that practical quantum computing needs both "scaling up" and "scaling out". Scaling up refers to increasing qubit density and capability in quantum processing modules, while scaling out involves connecting modules together into larger systems by sharing entanglement. According to Photonic, neither strategy alone is enough. Physical limitations such as signal congestion and manufacturing constraints will, they say, eventually limit the size of individual quantum processors. Merely networking many processors together creates challenges for qubit coherence and entanglement distribution. The future, they conclude, belongs to architectures that can perform both functions simultaneously and efficiently.

A key feature of the Photonic analysis is its emphasis on entanglement as the defining resource of quantum computing. Entanglement distribution is presented not merely as a technical detail but as the principal system bottleneck governing scalability. Architectures that can efficiently distribute entanglement across large quantum systems are expected to outperform architectures that merely maximise qubit count. Photonic therefore argues strongly in favour of native interconnects, particularly telecom-band optical links, as the most practical route toward large-scale modular quantum systems. The company's "Entanglement First™" architecture is presented as an example of a design philosophy that integrates scaling-up and scaling-out capabilities from the outset.

Finding quantum’s control points

Novo Holdings addresses a related question. Rather than asking how quantum computers will scale, it asks where economic returns will emerge within the industry. The authors reject the common assumption that a company's position within the technology stack automatically determines the value it captures. Instead, they argue that durable value forms around "control points" characterised by three attributes: scarcity, dependency and ownership. A capability must be difficult to reproduce, embedded within customer workflows, and owned by a company capable of retaining the resulting economic benefits. Only when all three conditions coexist does long-term value capture occur.

To support this framework, the Novo Holdings article draws heavily on analogies with the semiconductor industry. Historical winners such as ASML, TSMC and Arm did not succeed merely because of their location within the semiconductor value chain. Rather, they occupied positions that became difficult for customers and competitors to bypass. ASML controlled extreme ultraviolet lithography, Arm controlled a widely adopted architecture, and TSMC controlled advanced manufacturing capacity. The lesson, according to Novo Holdings, is not that value necessarily accumulates upstream, but that it accumulates wherever scarce and irreplaceable capabilities become embedded within customer activities.

Applying this framework to quantum computing leads Novo Holdings to a provocative conclusion. Whereas approximately 70% of private quantum investment between 2014 and 2025 flowed into hardware and components, Novo argues that the strongest future opportunities may lie in the application layer rather than the hardware stack. Specifically, it identifies domain-specific algorithms as possessing an attractive combination of technical scarcity, ownership potential, customer dependency and comparatively low capital intensity.

As a patent attorney, viewing this through a patentability lens, an applications-focussed approach like this one makes a great deal of sense to me. It shifts inventive activity in molecular simulation from the abstract into the practical, making hurdles to patentability lower.

For Novo, hardware remains essential and scientifically remarkable but it may not be where the greatest economic value ultimately resides.  

Two Perspectives

This creates an interesting contrast with Photonic's position. Photonic focuses on solving the technical challenge of scalable quantum infrastructure. Its argument implicitly assumes that scalable hardware architectures will be critical determinants of commercial success. Novo Holdings agrees that advanced hardware remains indispensable but argues that hardware capability alone does not guarantee durable value capture. A successful quantum hardware platform may create enormous capability, but application-layer businesses may ultimately capture significant portions of the resulting economic value. In business terms, Photonic focuses on creating the engine, whereas Novo Holdings focuses on identifying who profits most from its operation.

Another notable difference concerns the role of software and algorithms. Photonic discusses software only indirectly, primarily through the lens of enabling efficient entanglement distribution and system scalability. Novo Holdings, by contrast, devotes considerable attention to algorithm development. Importantly, however, they argue that value will not come simply from publishing better algorithms. Algorithms can often be replicated once disclosed. Instead, value accrues through validated workflows, proprietary data, customer integration and the ability to repeatedly solve important commercial problems. In their view, the defensible asset is not a particular quantum algorithm but the workflow built around it.

Novo Holdings develops this argument most fully through a case study of life sciences. The authors contend that drug discovery and molecular simulation represent particularly attractive application areas because they involve high-value decisions, existing budgets, experimental validation pathways and workflows that can become proprietary. Importantly, they do not claim that quantum computers will solve all biological problems. Instead, they identify specific bottlenecks, such as strongly correlated electronic structures, where quantum approaches could provide meaningful advantages. The opportunity, they say, lies in improving scientifically and commercially significant decisions.

Building strategic positions now

Perhaps the most important point on which the two articles agree is timing. Both argue that critical strategic positions are being established now, before fully fault-tolerant quantum computing becomes widespread. Photonic argues that architectures must be designed today with future distributed scaling in mind, rather than attempting to retrofit connectivity later. Novo Holdings similarly argues that application companies should establish customer relationships, workflow integration and proprietary datasets before hardware reaches maturity. In both analyses, waiting for the arrival of large-scale fault-tolerant quantum machines risks forfeiting the most valuable opportunities.

Taken together, the two articles portray a quantum industry evolving from a purely scientific endeavour into a complete technological ecosystem. Photonic concentrates on the engineering challenge of building quantum systems capable of scaling through entanglement distribution and modular networking. Novo Holdings focuses on the commercial layer, arguing that value will ultimately be captured at strategic control points indispensable to customers.

Their conclusions are not contradictory but complementary. Scalable quantum hardware may be a necessary condition for the emergence of significant quantum applications, yet the existence of such hardware alone does not determine where economic value will accumulate. In the long run, the winners may be those companies that both enable quantum capability and successfully embed it into customer decisions and workflows.