Novo Holdings' report indicates a significant shortfall in investment for quantum applications, with 70% of funding directed at equipment rather than business solutions.
A recent analysis by Novo Holdings highlights a significant investment trend in the quantum sector, revealing that from 2014 to 2025, about 70% of the $13.9 billion in private funding has been allocated to equipment and components. In contrast, investment in business applications remains critically low despite their high potential.
The report emphasizes that for the quantum sector to evolve, there must be a shift towards funding specialized algorithms and services in addition to quantum computing hardware. These advancements are essential for assisting clients in tasks such as molecule selection for research and experimental planning.
As of September 2, 2026, the total disclosed private funding for quantum firms reached $4.797 billion, slightly exceeding the total for all of 2025, which was $4.706 billion.
Investment Focus Shift Required
Industry analysts note that while initial investments in processors and components were necessary for technological progress, the real commercial viability of quantum technologies will depend on their ability to solve specific problems. Novo Holdings asserts that firms that deliver unique solutions will secure a competitive edge. This necessitates not only the development of algorithms but also the validation of their accuracy and integration into client workflows.
Simply having complex software does not guarantee business success. For example, tools for error correction may be absorbed into offerings from equipment manufacturers or cloud services, complicating independent sales efforts for standalone providers.
Service developers can engage with clients ahead of the availability of robust quantum systems by working on tailored scientific projects. This approach allows them to accumulate valuable algorithms and data that can be utilized for future clients.
Furthermore, improving algorithms could make quantum technology more applicable by allowing tasks to be executed on less powerful machines, thus enhancing its practicality.
Exploring Quantum Computing Applications
One of the most promising sectors for quantum computing applications identified by Novo Holdings is life sciences, particularly in pharmaceuticals. Existing investments in molecular modeling and computational chemistry present an opportunity for new services that can deliver enhanced outcomes.
However, the report cautions that early quantum systems will not be capable of managing the entire drug development lifecycle. Even advanced machines employing error correction will face limitations initially.
"In the early stages, fault-tolerant quantum computers will not model biological processes from start to finish; they will focus on a small but critical part of the workflow where classical approximations fail," the report states.
This will involve calculations related to chemical bond dynamics and electron behavior in specific molecular regions, while conventional computers will continue to handle the remainder of the tasks.
Moreover, the accuracy of quantum calculations could significantly influence client decisions on experimental directions and compound explorations. If results do not impact these choices, their commercial viability remains uncertain, analysts warn.
Experts suggest that practical applications in fields like materials science, energy, and chemistry might emerge sooner than in pharmaceuticals, particularly for tasks involving catalysts and batteries that align well with the capabilities of less powerful quantum systems.
The report outlines two potential scenarios for the development of quantum technology: the emergence of early fault-tolerant machines in the late 2020s to early 2030s, followed by more scalable systems in the mid-2030s.
Among the risks identified is the rapid progress in classical computing and AI, which could undermine the advantages of quantum approaches before the necessary hardware becomes available. Additionally, pharmaceutical companies and cloud service providers might independently develop the solutions needed for their operations.
Noteworthy is the recent collaboration between Quantum Motion and Nvidia, which introduced a molecule modeling technique that utilizes AI for data preparation, subsequently reducing the strain on quantum hardware.
