Quantum computing in 2025: risk and reward

Thanks to developments in silicon-based technology, today’s smartphones contain not just thousands, but billions of transistors. And 70 years after the introduction of the silicon transistor, computing has reached its next milestone: the quantum era.

Quantum computing has the potential to revolutionise problem-solving, performing complex calculations exponentially faster than classical computers can. But what does that mean for different industries? And where will it have the biggest impact?

In this report – including contributions from PwC, Eviden, Atom Computing, Microsoft, IonQ, IQM, and QuEra – we look ahead to 2025, to some of the main industry use cases for quantum computing, and we evaluate the relative strengths of the different quantum platforms being developed today.

The current state of quantum computing

Over the last quarter-century, quantum computers have been predominantly developed using silicon-based superconducting technology, which uses artificial atoms (superconducting qubits). This is still the case in 2025, with Google, IBM Q, Rigetti, QuTech, QCI, IQM, and Origin Quantum all putting their considerable weight behind it.

“Today superconducting is the most widely used technology for quantum computers. There is a first-mover advantage, and the technology that matures first might take the largest share of the market,” says Michael Bruce, public relations manager at IQM. “Superconducting technology is appealing because of its scalability – using well-established semiconductor fabrication technologies, it allows scaling the processor size in a well-defined engineering process.”

But superconducting isn’t the only quantum platform in town. And quantum computers are also being built using techniques such as trapping ions, manipulating atoms and even encoding qubits within the states of photons (single particles of light).

Discover how PsiQuantum is building a million-qubit machine with photonics.

“Ion trap systems work well for applications needing high fidelity but with fewer qubits,” explains Dr Arit Kumar Bishwas, US head of quantum computing at PwC. “Photonics has an edge in secure quantum communications through existing optical networks, while silicon-based qubits are promising for scalability, due to their compatibility with semiconductor technology.”

Despite their many differences, one thing that all qubits have in common is their sensitivity to environmental fluctuations, and this potentially limits the ability of the quantum computer to perform long and complex calculations. The best current solution is referred to as “Quantum error correction”, which is orders of magnitude more difficult than classical error correction. 

“Not all types of qubits allow for the quantum error correction needed to enable more reliable quantum computing,” says Krysta Svore, technical fellow, Advanced Quantum Development, Quantum at Microsoft. “And without reliable quantum computing, valuable solutions to classically intractable problems are unlikely to be achieved. It’s essential to graduate from computing with noisy physical qubits to operating with reliable, logical ones.”

Microsoft recently partnered with Atom Computing to launch its first commercially-available quantum computer, boasting the largest number of entangled logical qubits on record (24 logical qubits). The computer uses neutral atom qubits, which – whilst being more accurate than other types – can typically execute fewer operations per second. And it isn’t just neutral atoms. Every quantum platform has at least one area that needs significant improvement.

“Scalability, reliability, and error rates are key hurdles. Quantum systems need higher qubit counts and lower noise levels to reach practical, real-world readiness. Building stable, large-scale systems is essential to unlock their full commercial potential,” Bishwas tells us. 

For a full overview of the different quantum types, and to see how they’re dealing with issues like quantum error correction, please read our Five Platform Problem report.

Quantum platform	Applications
Superconducting qubits	Ideal for early algorithmic development, optimisation, and quantum chemistry
Ion trap systems	Suitable for applications needing high fidelity with fewer qubits
Photonics	Excels in secure quantum communications through existing optical networks
Silicon-based qubits	Promising for scalability due to compatibility with semiconductor technology
Quantum annealer systems	Look promising for solving optimisation problems

Industry use cases in 2025

Each quantum platform has its own set of strengths, suited to particular use cases, across a diverse range of industries and disciplines. Amongst these, quantum computing could help solve complex optimisation problems in logistics, finance, and manufacturing, where classical algorithms are inefficient. Scientists are also using quantum system simulations for drug discovery, materials science, and fundamental physics research. 

“If we talk about the gate-based quantum systems, superconducting qubits are ideal for early algorithmic development, particularly in optimisation and quantum chemistry, due to their fast operational speed and relatively manageable error rates,” says Bishwas. “These fields face complex optimisation, modeling, and simulation challenges that quantum computers are uniquely positioned to address. Quantum’s potential to revolutionise simulations in drug discovery, improve logistical efficiency, and secure financial data makes these industries strong early adopters.”

Hermann Hauser – who co-founded Acorn Computers and ARM, and is one of the world’s leading investors at Amadeus Capital Partners – agrees that quantum computing will come into its own when dealing with quantum problems, such as molecular modelling. 

“I think the most transformative area of quantum computing is going to be molecular modeling,” says Hauser. “Richard Feynman famously asked why would you want to model a quantum system with a classical computer? The right way to model a quantum system is with a quantum computer and those molecules are quantum systems. 

“So if you want to find a binding site for a target protein, for example, which is the essential mechanism in drug discovery, then having a quantum computer is essential. And I think that’s the most important application, because it concerns our own health,” says Hauser.

Bishwas also claims that ion trap systems work well for applications needing high fidelity, but with fewer qubits. And he says that photonics “has an edge” in secure quantum communications through existing optical networks. Meanwhile, silicon-based qubits are promising for scalability, due to their compatibility with existing semiconductor technology, potentially “easing integration with traditional infrastructure”.

Elsewhere, agriculture and the environment are areas being addressed by a number of start-ups operating within the quantum computing sector, such as the development of new fertilisers and the optimisation of existing infrastructure.

“At Atom Computing, we are particularly interested in sustainability applications because of the potential for significant impact,” says Justin Ging, chief product officer at Atom Computing. “For example, we are collaborating with the US National Renewable Energy Lab (NREL) on putting quantum-in-the-loop to understand how the electric grid can be dynamically optimised as conditions vary, especially in crisis scenarios such as storms or wildfires.”

IonQ is another quantum computing company that’s already formed successful partnerships with organizations like the Naval Research Laboratory (NRL), Airbus, and Deutsches Elektronen-Synchrotron (DESY) as they focus on optimisation problems in fields such as quantum chemistry.

“IonQ’s enterprise-grade approach readies its quantum systems for deployment across various sectors, focusing on manufacturability, deployability, and customer applications at scale,” says Peter Chapman, CEO, president, and chairman of the board at IonQ. “Additionally, IonQ is exploring a growing number of quantum algorithms across fields such as AI, financial services, and cyber security.”

Industry	Use cases	Potential impact
Finance	Portfolio optimisation Risk analysis Fraud detection	Enhanced financial modeling and security
Pharmaceuticals	Drug discovery Molecular modeling	Accelerated development of new medicines
Logistics	Supply chain optimisation Route planning	Improved efficiency and cost reduction
Energy	Grid optimisation Weather forecasting	Enhanced sustainability and resource management
Automotive	Battery simulation Autonomous vehicle systems	Advancements in electric and self-driving vehicles
Aerospace	Cargo loading optimisation  Materials science	Cost savings and improved flight efficiency
Agriculture	Crop yield optimisation  Fertiliser production	Increased food production and sustainability

Real-world examples

• Airbus (Aerospace): Partnered with IonQ for cargo loading optimisation, achieving a potential 60x speedup over competitors. 
• Hyundai (Automotive): Collaborating with IonQ on image classification for autonomous vehicles and battery chemistry simulation.
• National Renewable Energy Lab (Energy): Working with Atom Computing on dynamic optimisation of the electric grid during crisis scenarios.

The funding outlook in 2025

According to the 2024 Global Overview of Quantum Unicorn Enterprises report from ICV TAnK, nine so-called unicorns currently operate within the quantum industry (a ‘unicorn’ being a company that is under 10 years old, has received private equity investment, and has a post-money valuation exceeding or equal to $1bn).

“There are nine quantum unicorns worldwide, primarily concentrated in the technology powerhouses of the United States and China,” the report says. “Companies from these two countries account for two-thirds of the total number and 80% of the global valuation. These enterprises have achieved rapid growth, averaging 4.4 years to reach unicorn status.”

The report also highlights that US companies SandboxAQ and Quantinuum (although part-founded in the UK with Cambridge Quantum) attained unicorn status within just three years, with an average valuation of $3.67 billion, positioning the United States as the current leader in the field of quantum technology.

“Investment is growing, but the path to business-ready solutions requires substantial capital for R&D,” explains Bishwas. “As technology progresses, investment from both venture capital and corporate sectors is expected to increase, ensuring sufficient resources to bring quantum solutions to market.”

Yuval Boger, chief commercial officer at QuEra, says that there has been a steady increase in interest. Speaking specifically about the funding landscape for quantum computing that uses neutral-atom technology, Boger said the market is “dynamic and growing”. 

“Investors are increasingly recognising the long-term potential of quantum computing, leading to more sustained funding commitments to support ongoing research and development,” Boger tells us. “There is a growing interest from both public and private sectors, with significant investments being made by governments, venture capital firms, and large technology companies. In addition, many funding opportunities are collaborative, encouraging partnerships between academia, industry, and government agencies to drive innovation.”

Quantum computing challenges in 2025

A key area that will dominate discussion during 2025 is the growing skills gap in quantum computing. And the shift from classical to quantum computing requires industry collaboration with researchers, developers, and students to ensure that adoption can be fully-supported. 

“Quantum computing and mechanics requires an entirely new way of thinking, and there is a limited number of professionals that can help with adoption,” says Dr Cédric Bourrasset, global head of HPC-AI and Quantum Computing at Eviden, Atos Group. “To resolve this, the knowledge available needs to be shared and spread through training and initiatives to raise awareness of the challenges and opportunities of quantum computing and quantum programming. This will enable companies, organisations, and research centres to harness the potential of quantum computing and take application development to the next level, ultimately solving complex business and scientific problems.”

Dr Bishwas at PwC agrees that knowledge sharing and collaboration will be vital components of a successful adoption of quantum computing within sectors such as cyber security, communication, drug discovery, and energy. 

“Collaborations foster applied research, enabling academia to conduct foundational studies, while industry drives applications and commercialisation,” says Bishwas. “Partnerships accelerate tech transfer, skill development, and the development of industry-relevant quantum algorithms, ultimately pushing innovation forward.”

Because of the different technologies and platforms that will make up the quantum computing ecosystem, maybe the biggest challenge will be harmonising all the diverse technologies. We are already seeing a hybridisation of supercomputers integrating central processing units (CPU), graphics processing units (GPU), and quantum processing units (QPU). And according to Bishwas: “Building a hybrid infrastructure that leverages quantum advantages, while still relying on classical systems, is a significant technical and operational hurdle.”

While quantum computing continues to mature, many researchers and developers will continue using software to simulate quantum algorithms on classical computers, thus bypassing the need for physical hardware. But with companies such as Microsoft, IonQ, IQM, and OrangeQS launching commercially available quantum computers within the next 12 months, 2025 will see unprecedented access to quantum computing within both research and commercial settings.

“Quantum computing will be the next digital revolution,” Bourrasset says. “However, for this revolution to turn into a reality, it is vital that in the years to come quantum technologies become accessible, scalable, and reliable, and become tangible enough for enterprises to engage in concrete use cases and to extract benefits.”

Editor’s note: the Richard Feynman quote referenced by Hermann Hauser first appeared in a 1981 lecture, titled “Simulating Physics with Computers”, and was as follows: “Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical. And by golly it’s a wonderful problem, because it doesn’t look so easy.”