Insider Brief
- A forthcoming industry analysis finds quantum computing is entering an early commercial phase defined by hybrid workflows, software abstraction and integration into existing computing systems rather than standalone deployment.
- The shift toward higher-level software layers is expected to reduce reliance on physics expertise, enabling developers to use quantum systems through abstraction similar to cloud computing models.
- Analysts project that near-term value will emerge from targeted applications such as molecular simulation, optimization, and cybersecurity, with quantum systems augmenting classical and AI workflows rather than replacing them.
- Photo by geralt on Pixabay
As nearly all the latest headlines suggest, quantum computing is increasingly moving out of the lab and academia and into business and industry.
Forward-thinking companies and policymakers are now wondering what the world looks like once the technology becomes commercially viable.
A forthcoming industry analysis by Dr. Renu Ann Joseph, founder and CEO of Luminant Analytics and Dr. Daniel Volz, quantum entrepreneur & founder and former CEO of KIPU Quantum, describes the sector as entering a phase of hybrid workflows, early applications and ecosystem-level investment. However, the long-term impact of quantum computing will not come from a single machine replacing classical systems, but from how quantum is integrated into the broader computing stack.
That future system will likely not resemble today’s centralized model of computing, according to the analysts. It points toward a distributed, software-driven environment where quantum resources are embedded into existing workflows and accessed through abstraction layers. Systems will be deployed selectively for specific types of problems rather than used as general-purpose tools. In making these projections,the analysts draw into their real-world experience where they have driven adoption of cutting edge technologies in the insurance/reinsurance and chemical industries. They have seen that business use case success, when delivered modularly, has the largest impact. Small successes in frontier technologies perturbs less of the entire enterprise infrastructure while delivering ROI at an acceptable timeline.This also helps fashion investment thinking for deep tech where returns need not come in 10 years, but quickly, and often exponentially.
Coding Without Physicists
One of the most important changes will occur at the software layer, according to the analysts. Today, operating quantum systems still requires deep, PhD-level expertise in physics. Developers need to understand qubit behavior, noise and error rates to make use of most available tools, which feel akin to coding in assembly.
This is in stark contrast with the profile of today’s owners of use cases that are likely going to benefit from quantum. Most of these developers are trained computer scientists, and lack the physics understanding and training in linear algebra needed to use today’s software stack effectively
That constraint is beginning to ease with abstraction, standardized software stacks and hybrid workflows making systems easier to use. Over time, these tools are expected to evolve into full abstraction layers. Developers will be able to work with quantum systems without needing to understand the underlying hardware.
This will resemble how cloud computing evolved. Infrastructure will become invisible and application developers take control while quantum programming becomes a matter of expressing problems in ways that can be routed to the right computational resource.
Dr. Volz, who co-founded and until end of 2025 lead quantum applications at KIPU Quantum & worked on applications of quantum at McKinsey and BASF, added: “Quantum will come off age when the conversation will no longer be dominated by academically-minded quantum physicists debating amongst themselves, but by the people actually tasked by leveraging the value of quantum in enterprises. The key for this shift will lie in abstraction, where the developer’s experience will no longer feel like writing in assembly, but using intent and higher-level abstraction to express what they want to solve. The Nielsen / Chuang is a fantastic textbook to learn the details, but cannot be mandatory reading for people to do things with a QPU.”
One Workflow, Many Machines
The analysts expect that the future quantum landscape will not be defined by a single dominant architecture. It will consist of multiple systems working together.
Quantum computing already operates as an ecosystem that includes hardware platforms, software providers and industry solutions. In a commercial environment, workloads will be distributed across different types of quantum processors and classical high-performance systems.
A single problem may be broken into parts. For example, optimization tasks could be sent to one system, while simulation tasks could go to another. Data processing would remain classical and orchestration software would manage the process and select the most efficient resource for each step. While parts of the challenge are about integration of physical systems, the lion’s share of work is actually again software, to handle the orchestration.
In modern data centers, tasks are already handled similarly with distribution spread across CPUs, GPUs, and specialized accelerators. Quantum systems would join that mix as another tool, used where they provide measurable value.
New Discoveries, Added Protection
The analysts write that quantum isn’t moving into commercialization, so much as it is being lured. Several uses cases stand out as exemplars of quantum commercialization, they write.
Molecular and materials discovery is often cited as one of the most important long-term applications. Simulation has the potential to affect industries such as energy, manufacturing, and pharmaceuticals.
In a commercial environment, this capability could change how innovation happens. Instead of relying on trial-and-error experimentation, researchers could design molecules and materials from first principles. Quantum systems would model interactions at the atomic level with high precision.
This would reduce development timelines and limit the need for physical testing. It would also change where value is created. More of it would move into computational design rather than experimental iteration.
Dr. Volz, who started his career as an experimentally working chemist almost 20 years ago, remarks “It is shocking how much of modern chemistry is still empirical lab work, rather than rational. It is high time to re-invent the way chemistry is being done.”
Quantum computing is often discussed in terms of the risk it poses to encryption. A commercial quantum environment points to a broader outcome.
Post-quantum cryptography is already under development. Over time, security systems are likely to be redesigned rather than patched. New systems would incorporate quantum-resistant methods from the start.
Dr. Joseph who is working in stealth on her next tech venture incorporating post-quantum cryptography for insurers and re-insurers adds “Legacy systems can no longer be the excuse for standing in the way of innovation. We are running short on time to make the changes to these systems for handling and using data from a pure security perspective. A re-do has been long overdue. In 2026, even in slow-moving fields like insurance and re-insurance, when it comes to technology, the leader wins. The followers pick up the crumbs, which are quickly diminishing. In ten years, the agile will survive.”
This applies to encryption, authentication, secure communications, and data integrity. Organizations will not simply upgrade existing systems. Many will rebuild digital infrastructure to align with new computational realities.
AI Remains Hybrid
In the coming commercial era, quantum computing will intersect with artificial intelligence, but it will not replace it. Current development already relies on hybrid classical and quantum workflows.
That model is expected to continue with quantum systems boosting specific parts of AI, such as optimization or sampling. Classical systems will still handle large-scale data processing and deployment.
The result is a synergistic coexistence. While AI remains primarily classical, quantum capabilities are added where they provide a clear advantage.
From Advances to Systems
The current phase of quantum development is defined by early demonstrations of technical advantage. These results are limited to narrow problems and are not yet ready for large-scale deployment.
The analysts foresee the next phase will turn technical performance into economic value and will require improvements in reliability, cost and system design.
IThe conversation will shift from KPIs like number and fidelity of qubits, or factors in outperformance for algorithms, but to measurable, economic ROI reaped by entreprises. They add that post-commercial quantum systems will be embedded into workflows, software will hide complexity, and industries will translate performance gains into measurable outcomes.
The transition is already underway. What remains to be seen is how deeply it will be integrated into the systems that define modern industry. Perhaps it will re-write the paradigm of the modern industry?
Analysts
Dr. Renu Ann Joseph is an data leader/entrepreneur/economist with over two decades of global collective experience in different industries. She has spent nearly a decade in re/insurance, and since 2017, she has moved from corporate to being an entrepreneur where she has spun out 2 ventures, written 2 books and created/hosted 2 podcasts. Her insurtech, Luminant Analytics is focused on improving insurance pricing for US trucking insurance lines by using external data. Her Data Science & AI center of excellence helps companies that are not primarily driven, to use data more effectively using AI and Data science techniques and education. Her keen interest in technologies is reflected in her varied data analytics backgrounds which covers statistics and economics all the way to quantum computing.She writes on Medium on technology topics and selected publications in the insurance area on trucking. She has a Ph.D from the University of Illinois at Chicago in Economics (2010). An American who now lives in New York City, she considers herself a global citizen having studied and worked in the US, Canada, Switzerland and India. She spent over 12 years in Basel, Switzerland where she was part of the Young Leader’s Conference of 2023 of the American-Swiss Foundation.
Dr. Daniel Volz is a deep-tech entrepreneur and quantum computing expert with experience spanning strategy consulting, industrial R&D, and venture building. He is the founder and former CEO of KIPU QUANTUM, a quantum software company focused on developing application- and hardware-specific quantum algorithms for real-world industrial problems. Under his leadership, the company worked with leading industry users in quantum, and positioned itself at the forefront of near-term quantum advantage.
Prior to founding KIPU, Daniel worked on quantum computing strategy and applications at McKinsey & Company, where he advised global clients across chemicals, pharmaceuticals, energy, and finance on the commercial potential and realistic timelines of quantum technologies. He later joined BASF SE, leading itsearly enterprise-level quantum initiative and helping bridge emerging quantum capabilities with concrete industrial R&D and optimization use cases.
Daniel’s background combines hands-on scientific research with business execution. He holds a Ph.D. in Chemistry from Karlsruhe Institute of Technology (KIT), where his research focused on advanced computational and physical chemistry topics. This foundation enables him to translate complex scientific concepts into practical technology strategies and scalable products.
He is an active speaker and contributor on quantum computing, commercialization, and deep-tech entrepreneurship, regularly engaging with investors, corporates, and policymakers. In this report, Daniel contributes perspectives on key quantum use cases, leading players, and major investments, offering a pragmatic, operator-driven view on how value is emerging in the quantum ecosystem today.
