Quantum computing revenue to hit $15 billion in 2028 due to AI, R&D, cybersecurity

Total revenue generated from quantum computing services will exceed $15 billion by 2028, forecasts ABI Research.

quantum computing revenue

The demand for quantum computing services will be driven by some process hungry research and development projects as well as by the emergence of several applications including advanced artificial intelligence algorithms, next-generation encryption, traffic routing and scheduling, protein synthesis, and/or the design of advanced chemicals and materials. These applications require a new processing paradigm that classical computers, bound by Moore’s law, cannot cope with. However, one should not expect quantum computers to displace their classical counterparts anytime soon.

Unlike classical computers, based on sequential processing principles, quantum computers leverage their strengths from two fundamental characteristics inspired from quantum physics, namely entanglement and superposition, which make them super powerful for undertaking certain tasks, notably inter-correlated events that need to be executed in parallel.

“Classical computing is not dead, even in the post-Moore’s law era,” said Lian Jye Su, Principal Analyst at ABI Research. “These machines will remain the ultimate processing power for executing traditional tasks such as text, video, speech processing, and signal processing, but will be potentially challenged by quantum machines when it comes executing algorithms that require massive parallel processing.”

Quantum computing is, however, still in its embryonic stage of development and is not ready for large-scale commercial deployment anytime in the near to mid-term. Scalability, technology stability, reliability, and cost efficiency are the major factors the industry should address before seeing quantum computers moving beyond lab projects or very restricted and constrained commercial deployment. The attempts to create quantum computers that are stable and have low error rate require heavy investment in infrastructure, software development, and human expertise.

Operation is currently performed under extreme low-temperature, high magnetic field, and in a vacuum or sterile environment, making the technology extremely difficult to scale and expensive to operate. It is therefore not surprising that quantum computing is unlikely to achieve the distribution level of classical computers anytime within the next 10 years. The technology will remain concentrated in the cloud domain for many years to come.

D-Wave Systems, IBM, and Rigetti Computing are few of the vendors that have commercial quantum computing systems. Based on adiabatic quantum computation, D-Wave System’s quantum computer has been sold to government agencies, aerospace, and cybersecurity vendors. However, this type of system is constrained in terms of computational capabilities as compared to the rest of its counterparts. IBM, Rigetti Computing and other cloud computing giants such as Alibaba, Google, Intel, and Microsoft are opting for a quantum computing system based on the quantum gate model.

“While the industry explores various hardware implementation methods by exploiting different quantum physics phenomena, they all face the harsh reality of tradeoffs, having to find the right balance between maintaining long coherence time, reducing error rates, minimizing cost, and developing scalable products,” said Su.

Therefore, excessive cost and extremely restrictive physical implementation will limit quantum computing technology to government, public, and military agencies as well as major enterprises and cloud computing giants. The technology will be made available to the public via an as-a-service business model. “The future of cloud computing will increasingly rely on parallelism as new types of sophisticated applications and algorithms emerge. These algorithms will need more than Moore’s law for their execution and the industry will need to deploy more efforts to accelerate the development of quantum computers as alternatives to their classical computer counterparts,” concluded Su.