Quantum computing use cases are getting real—what you need to know

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Accelerating advances in quantum computing are serving as powerful reminders that the technology is rapidly advancing toward commercial viability. In just the past few months, for example, a research center in Japan announced a breakthrough in entangling qubits (the basic unit of information in quantum, akin to bits in conventional computers) that could improve error correction in quantum systems and potentially make large-scale quantum computers possible.1 And one company in Australia has developed software that has shown in experiments to improve the performance of any quantum-computing hardware.2

As breakthroughs accelerate, investment dollars are pouring in, and quantum-computing start-ups are proliferating. Major technology companies continue to develop their quantum capabilities as well: companies such as Alibaba, Amazon, IBM, Google, and Microsoft have already launched commercial quantum-computing cloud services.

Of course, all this activity does not necessarily translate into commercial results. While quantum computing promises to help businesses solve problems that are beyond the reach and speed of conventional high-performance computers, use cases are largely experimental and hypothetical at this early stage. Indeed, experts are still debating the most foundational topics for the field (for more on these open questions, see sidebar, “Debates in quantum computing”).

Still, the activity suggests that chief information officers and other leaders who have been keeping an eye out for quantum-computing news can no longer be mere bystanders. Leaders should start to formulate their quantum-computing strategies, especially in industries, such as pharmaceuticals, that may reap the early benefits of commercial quantum computing. Change may come as early as 2030, as several companies predict they will launch usable quantum systems by that time.

To help leaders start planning, we conducted extensive research and interviewed 47 experts around the globe about quantum hardware, software, and applications; the emerging quantum-computing ecosystem; possible business use cases; and the most important drivers of the quantum-computing market. In the report Quantum computing: An emerging ecosystem and industry use cases, we discuss the evolution of the quantum-computing industry and dive into the technology’s possible commercial uses in pharmaceuticals, chemicals, automotive, and finance—fields that may derive significant value from quantum computing in the near term. We then outline a path forward and how industry decision makers can start their efforts in quantum computing.

Quantum computing funding remains strong, but talent gap raises concern

A growing ecosystem

An ecosystem that can sustain a quantum-computing industry has begun to unfold. Our research indicates that the value at stake for quantum-computing players is nearly $80 billion (not to be confused with the value that quantum-computing use cases could generate).


Because quantum computing is still a young field, the majority of funding for basic research in the area still comes from public sources (Exhibit 1).


However, private funding is increasing rapidly. In 2021 alone, announced investments in quantum-computing start-ups have surpassed $1.7 billion, more than double the amount raised in 2020 (Exhibit 2). We expect private funding to continue increasing significantly as quantum-computing commercialization gains traction.



Hardware is a significant bottleneck in the ecosystem. The challenge is both technical and structural. First, there is the matter of scaling the number of qubits in a quantum computer while achieving a sufficient level of qubit quality. Hardware also has a high barrier to entry because it requires a rare combination of capital, experience in experimental and theoretical quantum physics, and deep knowledge—especially domain knowledge of the relevant options for implementation.

Multiple quantum-computing hardware platforms are under development. The most important milestone will be the achievement of fully error-corrected, fault-tolerant quantum computing, without which a quantum computer cannot provide exact, mathematically accurate results (Exhibit 3).


Experts disagree on whether quantum computers can create significant business value before they are fully fault tolerant. However, many say that imperfect fault tolerance does not necessarily make quantum-computing systems unusable.

When might we reach fault tolerance? Most hardware players are hesitant to reveal their development road maps, but a few have publicly shared their plans. Five manufacturers have announced plans to have fault-tolerant quantum-computing hardware by 2030. If this timeline holds, the industry will likely establish a clear quantum advantage for many use cases by then.


The number of software-focused start-ups is increasing faster than any other segment of the quantum-computing value chain. In software, industry participants currently offer customized services and aim to develop turnkey services when the industry is more mature. As quantum-computing software continues to develop, organizations will be able to upgrade their software tools and eventually use fully quantum tools. In the meantime, quantum computing requires a new programming paradigm—and software stack. To build communities of developers around their offerings, the larger industry participants often provide their software-development kits free of charge.

Cloud-based services

In the end, cloud-based quantum-computing services may become the most valuable part of the ecosystem and can create outsize rewards to those who control them. Most providers of cloud-computing services now offer access to quantum computers on their platforms, which allows potential users to experiment with the technology. Since personal or mobile quantum computing is unlikely this decade, the cloud may be the main way for early users to experience the technology until the larger ecosystem matures.

The rise of quantum computing

Industry use cases

Most known use cases fit into four archetypes: quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization. We describe these fully in the report, as well as outline questions leaders should consider as they evaluate potential use cases.

We focus on potential use cases in a few industries that research suggests could reap the greatest short-term benefits from the technology: pharmaceuticals, chemicals, automotive, and finance. Collectively (and conservatively), the value at stake for these industries could be between roughly $300 billion and $700 billion (Exhibit 4).



Quantum computing has the potential to revolutionize the research and development of molecular structures in the biopharmaceuticals industry as well as provide value in production and further down the value chain. In R&D, for example, new drugs take an average of $2 billion and more than ten years to reach the market after discovery. Quantum computing could make R&D dramatically faster and more targeted and precise by making target identification, drug design, and toxicity testing less dependent on trial and error and therefore more efficient. A faster R&D timeline could get products to the right patients more quickly and more efficiently—in short, it would improve more patients’ quality of life. Production, logistics, and supply chain could also benefit from quantum computing. While it is difficult to estimate how much revenue or patient impact such advances could create, in a $1.5 trillion industry with average margins in earnings before interest and taxes (EBIT) of 16 percent (by our calculations), even a 1 to 5 percent revenue increase would result in $15 billion to $75 billion of additional revenues and $2 billion to $12 billion in EBIT.


Quantum computing can improve R&D, production, and supply-chain optimization in chemicals. Consider that quantum computing can be used in production to improve catalyst designs. New and improved catalysts, for example, could enable energy savings on existing production processes—a single catalyst can produce up to 15 percent in efficiency gains—and innovative catalysts may enable the replacement of petrochemicals by more sustainable feedstock or the breakdown of carbon for CO2 usage. In the context of the chemicals industry, which spends $800 billion on production every year (half of which relies on catalysis), a realistic 5 to 10 percent efficiency gain would mean a gain of $20 billion to $40 billion in value.


The automotive industry can benefit from quantum computing in its R&D, product design, supply-chain management, production, and mobility and traffic management. The technology could, for example, be applied to decrease manufacturing process–related costs and shorten cycle times by optimizing elements such as path planning in complex multirobot processes (the path a robot follows to complete a task) including welding, gluing, and painting. Even a 2 to 5 percent productivity gain—in the context of an industry that spends $500 billion per year on manufacturing costs—would create $10 billion to $25 billion of value per year.


Finally, quantum-computing use cases in finance are a bit further in the future, and the advantages of possible short-term uses are speculative. However, we believe that the most promising use cases of quantum computing in finance are in portfolio and risk management. For example, efficiently quantum-optimized loan portfolios that focus on collateral could allow lenders to improve their offerings, possibly lowering interest rates and freeing up capital. It is early—and complicated—to estimate the value potential of quantum computing–enhanced collateral management, but as of 2021, the global lending market stands at $6.9 trillion, which suggests significant potential impact from quantum optimization.3

The path forward for quantum computing

In the meantime, business leaders in every sector should prepare for the maturation of quantum computing.

Until about 2030, we believe that quantum-computing use cases will have a hybrid operating model that is a cross between quantum and conventional high-performance computing. For example, conventional high-performance computers may benefit from quantum-inspired algorithms.4

Beyond 2030, intense ongoing research by private companies and public institutions will remain vital to improve quantum hardware and enable more—and more complex—use cases. Six key factors—funding, accessibility, standardization, industry consortia, talent, and digital infrastructure—will determine the technology’s path to commercialization.

Leaders outside the quantum-computing industry can take five concrete steps to prepare for the maturation of quantum computing:

  1. Follow industry developments and actively screen quantum-computing use cases with an in-house team of quantum-computing experts or by collaborating with industry entities and by joining a quantum-computing consortium.
  2. Understand the most significant risks and disruptions and opportunities in their industries.
  3. Consider whether to partner with or invest in quantum-computing players—mostly software—to facilitate access to knowledge and talent.
  4. Consider recruiting in-house quantum-computing talent. Even a small team of up to three experts may be enough to help an organization explore possible use cases and screen potential strategic investments in quantum computing.
  5. Prepare by building digital infrastructure that can meet the basic operating demands of quantum computing; make relevant data available in digital databases and set up conventional computing workflows to be quantum-ready once more powerful quantum hardware becomes available.

Leaders in every industry have an uncommon opportunity to stay alert to a generation-defining technology. Strategic insights and soaring business value could be the prize.

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