On 23 September, I attended the EPSRC Quantum Mission 1 workshop in Birmingham, which brought together quantum computing specialists, AI and high-performance computing (HPC) experts, researchers, and end users around a deceptively simple question: how do we make quantum computing genuinely useful?
The workshop was organised ahead of a new funding opportunity and structured around eight real-world challenges, ranging from materials design, catalysis and molecular modelling to nuclear applications, crop protection and financial services. The day combined keynote presentations, a panel discussion and challenge-focused roundtables, giving participants the opportunity to explore where quantum, AI and HPC could contribute to each problem.
Before the workshop, I had often thought about quantum computing as the next generation of technology that might eventually replace today’s classical computing. But it is much clearer now, that this is probably the wrong way to think about it. The future is much more likely to be hybrid. Quantum computing will sit alongside AI, HPC and existing classical systems, with each technology used where it adds the most value. In many cases, organisations may eventually use quantum capability without consciously “choosing quantum” at all. It could simply become another part of the computing stack behind a wider workflow. The challenge, therefore, is understanding how to integrate it into the infrastructure and applications organisations already use.
The policy direction behind Quantum Mission 1 reflects this. The ambition is to develop the software, algorithms, infrastructure and skills needed to integrate quantum into real computational workflows and make it genuinely useful.
Quantum is not ready to solve everything
One of the things I appreciated most was the realism in the room. If an organisation has a problem that needs solving today, a quantum computer is still highly unlikely to be the best solution compared with existing classical approaches. However, the value of engaging now is different. It is about understanding where quantum might eventually provide a meaningful advantage, what scale of machine would be required, as well as which applications could become viable first.
That distinction is important because it moves us away from technology hype and towards something much more practical: quantum readiness. And quantum readiness does not necessarily mean buying quantum capability or creating a quantum team. It means understanding your hardest computational problems. Where are current methods too slow, too expensive or unable to operate at the scale required? What is already possible through AI, HPC or conventional computing? What improvement would actually create commercial or societal value? Only then does it make sense to ask whether quantum could contribute. If an organisation is still using Excel to manage a complex optimisation problem, moving straight to quantum is probably not the first step.
“Start with the problem, not the quantum use case”. This theme came through repeatedly throughout the panel discussion. Quantum researchers need much more than broad challenges such as “optimise our supply chain” or “improve our risk model”. They need to understand what the underlying computational problem is, how large it is, how it is currently solved and what success looks like. One of the panellists described how commercial problems can sometimes be several different computational challenges bundled together and presented as one. Before asking whether quantum can help, those problems need to be broken down into smaller, tractable components.
That point resonated, as it is also one of the central challenges in academic-industry collaboration. Industry understands the operational problem. Researchers understand methods and technologies. But the real work often happens in the middle: translating one into the other. That translation layer could become just as important as the technology itself.
What could this mean for financial services?
This was particularly relevant to me attending the workshop on behalf of UKFin+, where our work focuses on complex, long-term challenges created by technological change in financial services. One of the workshop challenges was specifically focused on quantum-enhanced optimisation of trusted data and transaction intelligence in financial services.
That brought the wider discussion very close to areas we already explore through UKFin+: trust, data, resilience, regulation and how emerging technologies can be adopted responsibly. Financial services is an interesting environment for quantum because so many of its difficult problems are fundamentally computational. Complex optimisation, large-scale modelling, risk analysis, transaction networks, fraud detection, portfolio problems and interconnected systems all involve huge numbers of variables and possible outcomes. But the workshop also made me more cautious about jumping too quickly from those problems to “quantum solutions”.
In financial services, a better answer is not enough. There is another important dimension. Speed and computational power are only part of the equation. Banks, insurers, payment providers and other regulated organisations also need trust, security, auditability, validation and accountability. That became particularly clear during the panel discussion when an audience member challenged the idea that end users simply want an answer and do not care how it has been generated. In safety-critical or regulated environments, they very much do care.
Organisations need to understand whether a result can be validated, how a calculation was produced, whether it can be audited and whether the process meets governance and regulatory expectations. For financial services, quantum readiness therefore means thinking about the infrastructure surrounding them: secure access, standards, governance, validation, data protection and how quantum-enabled processes could eventually fit into existing regulatory frameworks. That conversation needs to happen alongside the technical development, not afterwards.
The people connecting the disciplines may be as important as the technology
Another theme I came away thinking about was skills. The UK is making significant investments in quantum infrastructure and capability, but infrastructure alone will not create impact. We need people who can move between quantum, AI, HPC and domain-specific problems. Importantly, that does not mean everyone needs to become a quantum physicist. A financial services specialist does not need to understand every detail of quantum hardware. Equally, a quantum researcher cannot be expected to understand the complexities of banking, insurance, payments or regulation without working closely with people who do. Several speakers described the need for a middle layer between end users and the technology: people who can take a complex business or societal challenge, break it into tractable computational problems and then determine whether AI, HPC, quantum or a combination provides the right approach.
If quantum eventually becomes widely adopted, most users are unlikely to interact directly with quantum circuits. The panel discussed a future where someone might use a scientific or business application and the underlying system decides whether the task should run using CPU, GPU, HPC, quantum resources or some combination of them. In other words, quantum could become largely invisible to the end user. The National Quantum Computing Centre is already helping researchers, government and industry access quantum systems, but broad adoption will depend on making that access much easier and embedding it into familiar workflows.
Preparing before the technology is ready
The overall takeaway is that not every organisation should start “doing quantum”. It was almost the opposite. Start by understanding the problems worth solving. Identify the computational challenges that are expensive, slow or currently impossible. Understand how they are solved today. Bring together the people who understand the problem with those who understand the technology. Experiment where there is a credible reason to do so. And build the skills, infrastructure, governance and partnerships now, so that when quantum capability reaches the point where it can deliver real value, organisations are ready to use it. That is especially relevant for financial services.
At the UKFin+ Annual Research Showcase, we will continue this discussion through one of our Wicked Conversations, focused specifically on quantum computing in financial services. It will be an opportunity to explore where the real opportunities lie, where the barriers remain, and which research questions need attention now if financial services is to use quantum technologies in a useful and responsible way in the future.