Bank of England’s Quantum Computing Roadmap

We are living through a period of profound technological transformation. Advancements in artificial intelligence (AI) have created new possibilities ranging from self-driving cars to improvements in medical diagnostics and treatment to more personalised financial services. The development of distributed ledger technology (DLT) has enabled innovations like the tokenisation of assets and of money, offering the potential for greater efficiencies and new functionalities. In the not-too-distant future, quantum computing could solve computational problems at scale that are beyond the capabilities of the best computers today.The UK’s financial services sector has a long history of embracing technological change and these innovations are no exception. Many firms are already using AI, piloting DLT applications, and exploring opportunities to use quantum computing. Beyond acting as an early adopter of these technologies, the financial services sector has an important role to play in enabling other sectors to adopt them too. If adopted widely and responsibly, these technologies could boost the UK’s productivity and overall economic growth.These developments could have profound impacts on the financial system and the UK economy. This means that, at the Bank of England, we need to understand the scale of these changes, what they mean for the work we do – monetary stability, financial stability, safe and sound firms – and how we can support the sector to adopt these technologies responsibly. Embracing responsible innovation is core to delivering on our objectives as a central bank.Our job is not to slow this innovation, but to shape it. While being vigilant to risks, we encourage responsible innovation – to make the financial system more resilient and efficient, support sustainable economic growth, and enable us to fulfil our responsibilities more effectively. Innovation thrives where it has a strong foundation, and we have a role in delivering that through a resilient financial system with robust standards.In this publication, we outline our approach to delivering the environment necessary to ensure that responsible innovation flourishes, setting out the work we have done, and will do, across AI, DLT, and quantum computing. While we have focused on these as the three technologies with the greatest potential today to shape our economy and financial services, we recognise that technological trends are difficult to forecast. Currently expected benefits may not materialise, and new technologies impacting our work will emerge in future. Our approach is flexible to that. And as part of this work, we will continue to collaborate with industry and domestic and international partners to develop a shared understanding of the opportunities and the potential risks.At the Bank, we want to harness the benefits of technological change in finance, while continuing to be vigilant to risks so that we underpin not undermine growth. This publication aims to give a clearer view of how we have, and how we will, seek to achieve that.Sarah BreedenDeputy Governor Financial StabilityAI, DLT, and quantum computing could be the most transformative technologies of our time, with the potential to reshape the UK economy and boost productivity. In turn, productivity growth can raise real wages, living standards, and overall economic growth. The financial services sector has a critical role to play, both as an adopter of these technologies and as a facilitator enabling firms across other sectors to do so.The scale of change driven by technological innovation will impact all the work the Bank of England does – from setting interest rates, to maintaining financial stability, to operating the UK’s core payments infrastructure, among others. We cannot know for certain which technological innovations will flourish and when but, as the UK’s central bank, we need to understand how these technological changes affect our remit, while also enabling the financial services sector to adopt these technologies safely. By ‘responsible innovation’ we do not mean ‘riskless’ innovation. Rather, we mean to emphasise that we cannot unlock the true benefits of innovation without understanding and managing the potential risks that innovation can pose.Done right, technological innovation can deliver sustainable economic growth, make the financial system more effective and resilient, and improve how we discharge our core functions as a central bank. This innovation best endures where it has a strong foundation, which we deliver through a resilient financial system with robust standards. The private sector is best placed to drive innovation, but the Bank has a role in shaping it. This publication sets out our approach to delivering the environment necessary to ensure that our statutory objectives are met as well as support the responsible adoption of innovative new technologies. It outlines the broad toolkit at our disposal (Figure 1), including the levers we can pull and the actions we can take, to create this environment.Our approach supports the UK Government’s vision for the UK to be the world’s most technologically advanced global financial centre.footnote [1] Given the rapid pace of technological innovation, we will endeavour to share our thinking, provide thought leadership on responsible innovation, and collaborate with stakeholders across industry, other regulators, and the Government to deliver the work outlined in this publication. Ultimately, our aim is to ensure that the people and firms of the UK benefit from technological innovation, ensuring it sustainably supports economic growth, while also continuing our work on mitigating potential risks arising from these changes.Disruptive technological innovations have the potential to reshape the UK economy, boosting productivity, real wages, and economic growth. Throughout history, waves of productivity growth have been preceded by significant technological innovations, such as the invention of electricity, the internal combustion engine, and the information and communication technology revolution, coupled with widespread adoption and diffusion across the economy.footnote [2] Productivity growth, in turn, can raise real wages and living standards, and translate into greater economic growth.footnote [3]We are currently seeing the emergence of a new wave of technological innovation, comprising the growth of AI, DLT, and quantum computing (Figure 2). Some estimates suggest that AI could almost double the UK’s annual GDP growth rate from an average of 1.6% between 2013 and 2023, to around 3% by 2035,footnote [4] while quantum computing could give the UK an economy-wide productivity boost of up to 7% by 2045 (or more if the technology becomes commercially viable earlier).footnote [5] Similarly, some argue that DLT could unlock transformative cost-saving and operational efficiency benefits – approximately $20 billion annually in global clearing and settlements costs – when operating at scale.footnote [6] While there is inevitable uncertainty about the impact and adoption path of these technologies, there is the potential for these technologies to boost GDP and labour productivity growth (important in the context of weak UK economic growth since the global financial crisis (GFC) – Box A) while also mitigating some of the impact of future headwinds on the economy, such as a shrinking, aging labour force.footnote [7] At the same time, sudden technological-driven transitions could have challenging impacts on parts of the economy by, for example, damaging competition or contributing to excessive automation that fails to improve worker productivity, which could also lead to inefficiently low wages and fuel inequality.footnote [8]It is crucial that the financial services sector responsibly adopts technology to improve the services to – and financing for – the real economy. Embracing technological innovation allows firms to operate more efficiently by automating routine tasks, which can reduce their costs, raise profitability, and free up resources to finance real economy activity.footnote [9] New technologies can transform traditional approaches by reshaping market infrastructures, improving efficiency and lowering cost, or by providing new products and services that may be better tailored to consumers’ and firms’ needs, improving capital allocation, risk distribution, and the flow of payments.The innovative application of new technologies is also central to the UK maintaining its leadership as a global financial centre. When coupled with the UK’s strengths as a global technological and financial powerhouse, particularly in AI and fintech,footnote [10] the UK financial services sector has an important role to play in driving economic growth and innovation. It contributes 9% of the UK’s economic output and around 1.2 million jobs as well as provides vital services to households and businesses that allow them to make transactions, manage and take risks, and invest – including in new technologies.footnote [11]Since the financial crisis, GDP and productivity growth have been relatively weak in the UK. Prior to 2008, GDP per capita growth averaged around 3% annually, compared to around 1% in the 15 years since.footnote [12] The UK is likely to face further economic headwinds, including related to demographics and geopolitics.Technological innovation is a fundamental driver of long-term economic growth. Historically, periods of sustained productivity growth have been preceded by both significant technological innovations and widespread diffusion throughout the economy.footnote [13] Technological innovation can increase productivity either through a reduction in production costs or through higher value added at the same production cost for existing or new products.footnote [14] Technological innovation can also spur other types of ‘non-technological’ innovation including organisational and managerial innovation.footnote [15] Greater, more responsible adoption of AI, DLT, and quantum computing could facilitate this productivity boost, helping to break the cycle of weak economic and productivity growth in the UK.We promote the good of the people of the UK through meeting our statutory objectives (Figure 3). We act to support technological innovation in the financial services sector where it is most relevant to our objectives, working to keep inflation low and stable and making sure the UK has a stable financial system.footnote [16] First and foremost, we contribute to sustainable growth through providing a stable economic environment and a resilient financial system (Box B). We can strengthen the resilience and stability of both the economy and the UK’s financial sector – and boost their competitiveness and capacity for innovation – by fostering an environment in which firms can responsibly adopt new technologies, such as AI, DLT, and quantum computing, thereby enabling the whole of the UK to benefit.The financial sector makes an important contribution to sustainable economic growth by providing vital services to households and businesses. These services allow households and businesses to make transactions and manage and take risks, supporting investment, innovation, and technological progress.footnote [17] In November 2024, the Chancellor asked the Financial Policy Committee (FPC) to undertake work on how the financial sector can better contribute to sustainable economic growth, which the FPC provided an update on in its July 2025 FSR, ahead of publishing its conclusions alongside the December 2025 FSR. We also responded to a similar request in our role as central securities depositories (CSD) and central counterparties (CCP) regulator in July 2025.footnote [18]Maintaining financial stability is the basis for sustainable growth. Periods of financial instability – such as the GFC – negatively impact the provision of vital services, weighing on output and productivity growth, with material scarring impacts on the economy. Financial stability in turn supports consumer and business confidence, facilitates investment that drives innovation and long-term productivity growth, makes the UK an attractive place to do business for international investors, and supports UK firms’ ability to compete abroad, as outlined in Figure A.footnote [19]Three regulatory ‘foundations’ represent the ways our regulation underpins the UK’s growth and competitiveness. These are: (i) maintaining public trust in regulated firms; (ii) adopting effective regulatory processes and engagement; and (iii) adopting a responsive and responsibly open approach to risks and opportunities.footnote [20] In June 2025, the Prudential Regulation Authority (PRA) published Competitiveness and growth: the PRA’s second report, documenting its progress on its secondary objectives (Figure 3). Technological innovation plays into all three of these and supporting it is consistent with advancing both our primary and secondary objectives. The Bank aims to create a regulatory environment where innovation can flourish responsibly and where households, businesses, and markets can reap the benefits. In doing so, there is a careful balance to strike between writing rules to provide firms with the certainty they need to invest with confidence, while providing enough flexibility to create space for innovation to flourish. We are continuing to think carefully about this balance, and our stakeholders have an important role to play in helping us get it right.Technological innovation can strengthen financial stability and the safety and soundness of firms when adopted responsibly. Greater automation can reduce the risks associated with manual processing, and more powerful computation techniques can improve risk management. It can also improve competition and make the financial system more resilient. However, if implemented imprudently, it may introduce risks to the Bank’s objectives.footnote [21] Although we adopt a technology-agnostic approach to regulation, as outlined in Box C, we have an important role to play in ensuring the financial services sector embraces innovation responsibly.footnote [22]Technological innovation can also affect the macroeconomy, impacting monetary stability and monetary policy. As noted in Section 1, innovation can boost productivity, raising the economy’s potential output over the time horizon relevant for monetary policy. All else equal, this can lead to lower inflationary pressure. Innovation could also affect labour market slack and wage dynamics through its effect on labour demand, and innovations impacting savings and credit could influence household behaviour. These effects are relevant for monetary policy decisions and may also affect monetary policy transmission. Innovations related to dynamic pricing and agentic AIfootnote [23] have the potential to impact inflation dynamics and measurement.As set out in Section 1, technological innovation is also crucial for economic growth and the competitiveness of the UK financial sector, and hence central to achieving our secondary objectives.The Bank of England has a technology-agnostic approach to supervision and regulation. Our core principles, rules, and regulations therefore do not usually mandate or prohibit specific technologies. However, technology-agnostic does not mean technology-blind. Risks may arise that relate to the use of specific technologies (such as AI or DLT) and have an adverse impact on our statutory objectives, and we actively work to understand and address these risks.Certain technologies may raise novel challenges for firms and regulators, which may mean it is difficult for firms to understand how existing rules apply to that technology. In those cases, we may issue guidance or use other policy tools to clarify how the existing rules and relevant regulatory expectations apply to those technologies to support their adoption. One example is Supervisory Statement (SS) 2/21 – Outsourcing and third party risk management, and the equivalent SSs for FMIs.footnote [24] Although the expectations in the SS apply to all forms of outsourcing and other non-outsourcing and third party arrangements entered into by firms, they aimed to address the specific characteristics of cloud usage and set out conditions that can help give firms assurance and deploy it in a ‘safe and resilient manner’.Technological advancement is a constant, and many innovations have only an incremental impact on our objectives. We focus our work on the most transformative technologies – those with the greatest potential benefits and risks, with potential for widespread adoption – which could radically transform the shape, functioning, and outcomes of the financial system, and where the impediments to their responsible adoption may be greatest. The Bank therefore has a role in assessing potential outcomes, monitoring the adoption path, and, where necessary, acting to shape desirable outcomes.We want to deliver the environment necessary to ensure responsible innovation prospers. The Bank has an important role to play in creating this environment, ensuring that firms feel comfortable adopting new technologies – if they wish to do so. This will enable firms and the people of the UK to reap the benefits of technological change, while also stimulating economy-wide growth, in line with the Monetary Policy Committee and FPC’s role in supporting the UK Government’s economic policy. Our approach aims to ensure the Bank plays its role in creating the right environment for firms to invest and innovate, by removing undue barriers to innovation, and incentivising exploration and responsible technology adoption across the sector.footnote [25]Our approach is designed to champion the safe transition to a fit for the future financial system, making best use of the technologies of tomorrow, acting in support of the wider economy. We have three levers to achieve that aim: (i) using our hard infrastructure; (ii) using our soft infrastructure; and (iii) using our convening and co-ordinating role. ‘Hard’ infrastructure generally refers to physical or tangible infrastructure that facilitate the workings of the modern economy, while ‘soft’ infrastructure generally refers to rules, regulations, and standards.We use these three levers in combination to achieve positive outcomes. The varying functions and responsibilities of the Bank, and the hard and soft infrastructure we provide, mean that we can promote responsible innovation in several different ways. We may take concerted action to facilitate better outcomes – to act to accelerate innovation where market failures may be impeding optimal outcomes or, conversely, to shape expectations around responsible technological innovation. This is not always the right course. We need to balance taking action with the risk of crowding out private enterprise, unhelpfully dictating market structures, or picking winners. We adopt a range of interventions at differing levels of intensity, alongside our efforts continuously to learn about new technological developments and their impact on the financial sector. Collectively, these approaches support firms as they experiment with and adopt these technologies.In practice, we use these levers through four actions:AI, DLT, and quantum computing are the three cross-cutting technologies that we are prioritising for further action, consistent with our focus on disruptive technologies with the most potential for transformative outcomes.AIfootnote [35] may be the most transformative technology of our time, with the potential to usher in significant efficiency gains, boost productivity, and transform the financial services sector, as well as the broader economy. Firms’ adoption of AI may scale rapidly – particularly in more material use cases, and with more autonomous and complex models – over the next few years. However, greater AI adoption could bring significant risks, such as increased possibility of cyberattacks, operational risks due to relying on third (and fourth) party providers outside the financial sector, increased possibility of correlated outcomes in financial markets, and model and data-related risks.footnote [36] These risks could impact the safety and soundness of UK firms, alongside the financial and monetary stability of the UK.AI adoption and deployment is increasing rapidly in the UK’s financial services sector. According to the joint survey by the Bank of England and the FCA, 75% of respondent firms are already using AI, with a further 10% planning to use AI over the next three years (Chart 1). Financial firms in the UK have demonstrated considerable willingness to experiment with newer and more complex models, with foundation models accounting for 17% of all use cases already.footnote [37]Percentage of firms using or planning to use AIWe want firms to use AI to improve their efficiency, productivity, and to ensure the UK remains a leading financial centre. Currently, firms are adopting AI across a range of use cases, although evidence suggests that these are skewed towards those with lower materiality (62% of use cases, compared to 16% for higher materiality).footnote [38] Respondent firms indicate they are predominantly using AI to optimise their internal processes, for cyber security, and for fraud detection. These use cases suggest that greater and more material adoption of AI could improve firms’ productivity. For example, firms could reduce their costs by automating routine tasks that could be performed by AI, such as monitoring fraudulent transactions at scale, or by enabling workers to leverage generative AI (GenAI) tools across a range of tasks. One study estimates that over the next 15 years GenAI could bring productivity gains of up to 30% to the banking and insurance sectors, and to firms operating in capital markets.footnote [39] Such productivity gains could free up workers’ time to focus on revenue-generating activities that may be harder to automate, while also enabling firms to better target customers with tailored products and services.footnote [40] At an aggregate level, these improvements could enable the people of the UK benefit from increased productivity and economic growth.It is important that there is the right soft infrastructure for firms to make full use of AI responsibly. Increased adoption could see highly autonomous AI systems in high-risk use cases that are not well understood, unaccountable, and prone to exacerbating risks in the financial system, with knock-on effects for economic stability.footnote [41] As regulators, we need to explore whether our frameworks are appropriate for such models, that we have the appropriate guidelines and guardrails in place to support adoption, and to manage risks to the financial sector, particularly because it is difficult to retrospectively address risks once usage reaches systemic scale.footnote [42]We are working proactively to ensure that the firms we regulate, and the wider financial system, can make safe and effective use of increasingly complex forms of AI. We have undertaken a programme of work over recent years to understand how best to enable the responsible use of AI in the financial system, which we outline in further detail below. Overall, we judge our regulatory framework has proven to be well equipped to support regulated firms’ use of AI so far. However, we keep our approach under review given rapid innovations in AI, particularly large language models (LLMs) and GenAI. We recognise that the rapid pace of innovation may require us to undertake new work on microprudential, financial stability, and monetary stability risks. We are also exploring how AI can help us improve our internal capabilities, as outlined in Box D.What we have done:What we will do:What we have done:What we will do:What we have done:What we will do:The Bank uses AI, where appropriate, to support and enhance our capabilities. For example, the Bank uses AI for predictive analytics, the study of non-linear interactions between variables, and analysis of larger and richer data sets, which can potentially help forecast GDP growthfootnote [55] and bank distress,footnote [56] for example. The range of activities that AI can do has expanded rapidly over the past few years, with newer and more sophisticated AI tools becoming more accessible.The Bank is leveraging AI, including both ML and GenAI, to enhance internal operations. Applications span from improving staff productivity to supporting policymaking. We have rolled out off-the-shelf AI assistants across the Bank, delivering productivity gains in a range of tasks including summarisation, note-taking, and code generation. Where needed, we are also building bespoke AI solutions.footnote [57] For instance, the PRA is actively exploring the use of LLMs to enhance supervisory tools, supporting tasks such as data extraction and natural language querying.footnote [58]In August 2025, we published our internal AI strategy, The Bank’s artificial intelligence (AI) strategy. At its core, the strategy is about safe, ethical, and effective use of AI.footnote [59] We want everyone at the Bank, regardless of their role, to have the opportunity to use AI tools and services to help them excel. Our AI strategy focuses on internal applications of AI at the Bank, helping us to work smarter and more efficiently.We set out five goals in the strategy: use AI to increase productivity, promote and encourage experimentation, use AI effectively and responsibly, collaborate, learn from others, and stay informed, and ensure AI works for our staff. Alongside these goals, we have a set of priorities that explain the actions we will take to achieve our goals in more detail. Our AI strategy is a cornerstone of our wider Data and Analytics strategy.DLT offers the possibility fundamentally to rewire parts of the financial system to unlock a range of beneficial outcomes, both for private actors and the Bank’s objectives. DLT enables the creation of common shared ledgers which can be updated near-simultaneously across all parties in a financial transaction. It could reduce frictions and inefficiencies with 24/7 operations and near-instant settlement, as well as by reducing the number of financial intermediaries and the cost of post-trade processing. For example, stablecoins built on DLT networks may already be being used at scale by individuals and businesses around the world for faster, cheaper cross-border payments.footnote [60] The technology could also allow for certain functions to be built into financial contracts through automation, such as making coupon payments on bonds. Tokenisation of assets and money (digital representation of financial assets using DLT) and smart contracts allow for greater programmability and fractionalisation of assets – this can deepen existing markets, unlock new ones, and change how assets, capital, and balance sheets can be mobilised within the financial system – making transactions cheaper, faster and more efficient. These infrastructures have the potential to be more operationally resilient than current legacy systems. While DLT may not universally have benefits over traditional ledgers, there is growing evidence that it can further improve the effectiveness and efficiency of certain aspects of financial markets, and support the introduction of new functionalities, enabling better services to be provided within the financial system. This could also contribute to economic growth and competitiveness, consistent with Government objectives.Given the potential benefits to private actors, industry is moving from experimentation to live market deployment in various use cases and asset classes. Many market participants, including financial institutions and central banks, are conducting experiments and initiatives to explore DLT and its functionalities. This includes exploring its applications in the tokenisation of real-world assets and considering how these assets can be transferred and utilised as collateral. These efforts range from proof-of-concept to full market deployment, across clearing, settlement, payments, and asset issuance. In line with these explorations, the Bank is also working on digitalisation and new forms of money and payments, where we are contributing to efforts to improve market functionality and efficiency by using new and innovative technologies and data.footnote [61]There are several obstacles to widespread industry adoption of DLT and some of these require collective industry co-ordination to overcome. Key barriers to scaling-up these solutions include high upfront costs, lack of interoperability between platforms, lack of suitable forms of digital money for settlement assets, and legal and regulatory frameworks that may be inconsistent and not entirely suited to digital assets, particularly for cross-border initiatives. This could create co-ordination issues and a first-mover disadvantage, potentially fragmenting liquidity, especially if platforms are not interoperable, and make DLT-based markets less efficient than those using traditional technology. The Bank is considering how regulatory and legal frameworks can support the responsible adoption of DLT, as well as the usability of new forms of digital assets and digital money through various initiatives, which we have set out in the ‘What have we done’ section below. These are consistent with efforts to facilitate innovation and to advance digitally enabled financial markets, including as set out in the UK Government’s Wholesale Financial Markets Digital Strategy.Without proactive intervention by central banks, there is a risk that the private sector inadvertently adopts DLT in a way that delivers outcomes that undermine financial stability. It is important that the efficiency gains offered by the technology are not achieved at the expense of the resilience of the financial system. For example, we must avoid unwarranted fragmentation in the financial system through interoperable infrastructure, across DLT-based platforms and between DLT and traditional systems. The private adoption of DLT without consideration for interoperability could lead to ‘walled gardens’ that fragment the financial system and create risks and inefficiencies such as liquidity fragmentation.footnote [62] Widespread adoption of public permissionless platforms for core functions could result in systemic vulnerabilities if the appropriate governance, risk management, and assurances for settlement finality are not in place to manage these risks.We are actively engaging on DLT adoption by the private and public sectors and intervening where necessary. Over the past few years, the Bank has launched a series of initiatives to deepen our practical understanding of DLT, assess its implications for the financial system, and respond to emerging developments in this space. This is a part of our ambition to support innovation in the payments landscape, both as an infrastructure provider – with the renewed RTGS system and further plans to continue to enhance it – and in an effort to provide a clear, predictable, and proportionate regulatory framework.footnote [63]What we have done:What we will do:What we have done:What we will do:What we have done:What we will do:What we have done:What we will do:While this publication focuses on three specific technologies, the Bank also engages strategically with broader trends in innovation in financial services.In July 2024, the Bank published a DP on our approach to innovation in money and payments, seeking input on how to advance the UK payments agenda. The DP reflected on various sources of innovation, including international trends in retail payments facilitating the greater use of account-to-account payments, and the use of programable platforms, including DLT-based platforms. The publication highlighted the importance of central bank money as the anchor of confidence in the financial system, the Bank’s approach to exploring innovations in wholesale central bank money, and the outcomes we seek in the retail payments space.In November 2024, the UK Government published its National Payments Vision, as part of a broader push to create a world-leading payments ecosystem that drives innovation, alongside competition and security, and in July 2025, the Government announced the launch of an innovative new model to deliver the next generation of UK retail payments infrastructure. The new delivery model introduces a collaborative framework between public authorities and industry players, designed specifically to harness the opportunities of next-generation technologies at pace. The UK authorities will, via the Payments Vision Delivery Committee (PVDC), set strategic direction, while a newly formed Retail Payments Infrastructure Board (RPIB), chaired by the Bank, will translate strategy into design. The PVDC will publish its strategy for retail payments infrastructure this autumn, and a Payments Forward Plan by the end of the year.footnote [68]Quantum computing could usher in the next major technological leap in financial services in the coming decade. Quantum computing uses the laws of quantum mechanics to perform computations that are too complex for classical computers. This could enable an exponential increase in computational power at a time when demand is rising significantly across industries. By harnessing quantum algorithms that have already shown superior performance – such as integer factorisation and solving certain systems of linear equations – it can enhance our ability to tackle problems that are currently beyond reach.footnote [69] It may also improve the functionality of existing AI/ML models, enabling deeper insights, faster training, and more adaptive decision-making.footnote [70]There is considerable uncertainty around how quickly quantum computing will materialise. Quantum computing capabilities are still in the early stages of development, particularly in comparison to AI and DLT. While some industry estimates suggest that practical implementation of quantum could take decades, rapid technological breakthroughs, such as progress towards quantum error correctionfootnote [71] and scalable architectures,footnote [72] are occurring that may have the potential to shift implementation to years.footnote [73] This means that preparations need to happen now, so that the financial system is able to adapt to a post-quantum future.Quantum computing represents a paradigm shift in computation and information processing, which could unlock a range of beneficial use cases for firms. This includes optimising market trading and investment processes, enhancing the efficiency of payment processing, dynamic optimisation of portfolio holdings, and enhancing the security of firms’ digital communication systems.footnote [74]The adoption of quantum computing also poses risks and challenges, including but not limited to:Our current work on quantum computing marks the start of a commitment to navigating its transformative potential and building out a comprehensive programme of work. As quantum capabilities evolve, we will need to continue to undertake more work to deepen our understanding of the full spectrum of benefits and risks associated with greater adoption.What we have done:What we will do:What we have done:What we will do:What we have done:What we will do: HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. These technologies are often called ‘general purpose technologies’. Bresnahan, T F and Trajtenberg, M (1995), General purpose technologies ‘Engines of growth’?, Journal of Econometrics; Bergeaud, A et al (2014), Productivity Trends from 1890 to 2012 in Advanced Countries, Banque de France Working Paper No. 475. Weston, T (2023), Economic growth, inflation and productivity, House of Lords Library. Government Office for Science and the Department for Science, Innovation and Technology (2025), The wider economic impacts of emerging technologies in the UK. Oxford Economics (2025), Quantum Computing could boost UK productivity and GDP growth, but government support is crucial. GFMA (2023), The impact of Distributed Ledger Technology in Global Capital Markets. Harari, D (2017), Productivity in the UK, House of Commons Library. Acemoglu, D (2023), Harms of AI, in Bullock, J B et al (eds), The Oxford Handbook of AI Governance, Oxford University Press. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. Department for Science, Innovation, and Technology (2025), AI Opportunities Action Plan; Innovate Finance (2025), UK FinTech Retains Second Spot in Global Investment Rankings Amidst Tough Market Conditions. HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. Bank of England (2025), Financial Stability Report (FSR) – July 2025. Bergeaud, A et al (2014), Productivity Trends from 1890 to 2012 in Advanced Countries, Banque de France Working Paper No. 475. Technological innovation may also require significant complementary investments, such as organisational redesign, improvements in businesses processes, and training, among other investments. Brynjolfsson, E et al (2021), The Productivity J-Curve: How Intangibles Complement General Purpose Technologies, American Economic Journal: Macroeconomics Vol 13(1), pages 333–72. Department for Science, Innovation, and Technology and the Behavioural Insights Team (2025), The Impact of Technology Diffusions on Growth and Productivity. The Bank has a secondary objective to ‘facilitate innovation in the provision of financial market infrastructure (FMI) services’, as outlined under the Financial Services and Markets Act (FSMA) 2023. As part of this work, the Bank launched an FMI innovation survey to gather their insights on the Bank’s approach to innovation in March-April 2025. Bank of England (2025), The Bank of England’s supervision of financial market infrastructures – Annual Report 2025. Bank of England (2025), FSR – July 2025. Bank of England (2025), Governor letter to the Chancellor on FMIC recommendations. Bank of England (2025), FSR – July 2025. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. PRA (2025), Prudential Regulation Authority Business Plan 2025/26. Agentic AI is defined as ‘systems which can take autonomous action to achieve specified goals by utilising tools, learning from feedback, and adapting to dynamic environments’. Bank of England (2025), FSiF: Artificial Intelligence in the financial system. Bank of England (2023), The Bank of England’s policy on outsourcing and third party risk management for Financial Market Infrastructures (FMIs). HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. DPIs are defined as ‘shared digital systems that are secure and interoperable and that can support the inclusive delivery of and access to public and private services across society’. Organisation for Economic Co-Operation and Development (2024), Digital public infrastructure for digital governments. Bank of England (2025), RTGS 2: a launchpad for innovation − speech by Victoria Cleland. HM Treasury and UK Debt Management Office (2025), Additional Information and Engagement on the Digital Gilt Instrument (DIGIT). The DSS facilitates the use of developing technology such as distributed ledgers in the issuance, trading and settlement of securities in the UK. Bank of England (2024), Digital Securities Sandbox (DSS). Monetary Authority of Singapore (2023), Interlinking Networks Technical Whitepaper. Bank of England (2025), International payment rails: the value of a harmonised gauge – speech by Sarah Breeden. The AI Consortium is a platform for public-private engagement to gather input from stakeholders on the capabilities, development, and use of AI in UK financial services. Bank of England (2025), Artificial Intelligence Consortium. CMORG supports the operational resilience of the finance sector through public-private collaboration. CMORG (2025), The Cross Market Operational Resilience Group. One example is the Payments Vision Delivery Committee (PVDC), established as part of the National Payments Vision, comprising senior representatives from HM Treasury, the Bank, the FCA, and the Payment Systems Regulator. The PVDC will publish its strategy for retail payments infrastructure this autumn, and a Payments Forward Plan by the end of the year. Bank of England (2025), The National Payments Vision. AI refers to the simulation of human intelligence by machines, including the use of computer systems, which have the ability to perform tasks that demonstrate learning, decision making, problem solving, and other tasks which previously required human intelligence (in line with the definition of AI used in the joint Bank and FCA Survey on AI in UK financial services – 2024 and the Bank’s FSiF – Artificial Intelligence in the financial system). Bank of England (2025), FSiF – Artificial Intelligence in the financial system. Bank of England and FCA (2024), Artificial intelligence in UK financial services – 2024. Materiality is a rating of the use case impact which could include quantitative and qualitative measures. The full definition can be found in FCA (2024), Definitions and Bank of England and FCA (2024), Artificial intelligence in UK financial services – 2024. Bank of England (2025), FSiF – Artificial intelligence in the financial system. FSB (2024), The Financial Stability Implications of Artificial Intelligence. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England and FCA (2019), Machine Learning in UK financial services; Bank of England and FCA (2022), Machine Learning in UK financial services; Bank of England and FCA (2024), Artificial Intelligence in UK financial services. Over the past 12 months, CMORG has published an AI Baseline Guidance Review and two AI-focused severe but plausible scenarios, articulating how Generative AI could be utilised to overcome traditional identification and authentication controls. CMORG has also developed an AI Shared Responsibility Model, providing an agreed structure for managing how AI services are implemented between client firm and provider. Bank of England (2025), Artificial Intelligence Consortium minutes – May 2025. Bank of England (2025), FSiF – Artificial intelligence in the financial system. Bank of England (2025), Bank of England Agenda for Research, 2025-2028. Bank of England (2024), Forecasting for monetary policy making and communication at the Bank of England: a review; Bank of England (2024), Response of the Bank of England to the Bernanke review of forecasting for monetary policy making and communication at the Bank of England. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2025), UK Deposit Takers Supervision: 2025 priorities; Basel Committee on Banking Supervision (2013), Principles for effective risk data aggregation and risk reporting. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. IAIS (2025), The IAIS publishes Application Paper on the supervision of artificial intelligence. US Department of the Treasury (2025), G7 Cyber Experts Group Statement on Artificial Intelligence and Cybersecurity. Bank of England (2021), Staff Working Paper No. 923: Forecasting with machine learning methods and multiple large data sets. Bank of England (2019), Staff Working Paper No. 831: Predicting bank distress in the UK with machine learning. Bank of England (2025), The Bank’s artificial intelligence (AI) strategy. Bank of England (2024), TRUSTED AI: Ethical, safe, and effective application of artificial intelligence at the Bank of England – speech by James Benford; Bank of England (2024), A data revolution: Built together, for everyone – speech by James Benford. Bank of England (2024), TRUSTED AI: Ethical, safe, and effective application of artificial intelligence at the Bank of England – speech by James Benford. Ray, H (2025), Stablecoins, Tokens, and Global Dominance, International Monetary Fund. Bank of England (2025), Building tomorrow’s markets: the digitalisation of finance – speech by Sasha Mills. Bank of England (2025), International payment rails: the value of a harmonised gauge – speech by Sarah Breeden. Bank of England (2025), The National Payments Vision. Bank of England (2021), Bank of England publishes policy for omnibus accounts in RTGS. Bank of England (2025), Renewed RTGS: Digital public infrastructure as a platform for innovation – speech by Dave Ramsden. Bank of England (2025), Digital Securities Sandbox Dashboard. HM Treasury and UK Debt Management Office (2025), Additional Information and Engagement on the Digital Gilt Instrument (DIGIT). HM Treasury (2025), Payments Vision Delivery Committee Update. BIS (2024), Quantum computing and the financial system: Opportunities and risks. Wang, Y et al (2024), A comprehensive review of Quantum Machine Learning: From NISQ to Fault Tolerance; Gil-Fuster, E et al (2024), Understanding quantum machine learning also requires rethinking generalisation. Google Quantum AI and Collaborators (2024), Quantum error correction below the surface code threshold. Schwerdt, D et al (2024), Scalable Architectures for Trapped-Ion Quantum Computing using rf Traps and Dynamic Optical potentials. Clancy, L (2025), Oxford quantum start-up to offer high-speed arb trading in NYC, Risk.net; McKinsey & Company (2025), The rise of Quantum Computing. G7 Cyber Experts Group (2024), G7 Cyber Expert Group Statement on Planning for the Opportunities and Risks of Quantum Computing.

National Cyber Security Centre (2025), Timelines for migration to post-quantum cryptography. National Institute of Standards and Technology (2025), What is Post-Quantum Cyptography? BIS (2023), Project Tourbillon demonstrates cash-like anonymity for retail CBDC. Bank of England (2025), FSiF – Artificial intelligence in the financial system. Ciceri, A et al (2025), Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers; FINRA (2023), Quantum Computing and the Implication for the Securities Industry; BIS (2024), Quantum computing and the financial system: Opportunities and risks. Ciceri, A et al (2025), Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers; FINRA (2023), Quantum Computing and the Implication for the Securities Industry; BIS (2024), Quantum computing and the financial system: Opportunities and risks. Bank of England (2025), FSiF – Artificial intelligence in the financial system. BIS (2023), Project Tourbillon demonstrates cash-like anonymity for retail CBDC. National Institute of Standards and Technology (2025), What is Post-Quantum Cyptography?

National Cyber Security Centre (2025), Timelines for migration to post-quantum cryptography. G7 Cyber Experts Group (2024), G7 Cyber Expert Group Statement on Planning for the Opportunities and Risks of Quantum Computing. Clancy, L (2025), Oxford quantum start-up to offer high-speed arb trading in NYC, Risk.net; McKinsey & Company (2025), The rise of Quantum Computing. Schwerdt, D et al (2024), Scalable Architectures for Trapped-Ion Quantum Computing using rf Traps and Dynamic Optical potentials. Google Quantum AI and Collaborators (2024), Quantum error correction below the surface code threshold. Wang, Y et al (2024), A comprehensive review of Quantum Machine Learning: From NISQ to Fault Tolerance; Gil-Fuster, E et al (2024), Understanding quantum machine learning also requires rethinking generalisation. BIS (2024), Quantum computing and the financial system: Opportunities and risks. HM Treasury (2025), Payments Vision Delivery Committee Update. HM Treasury and UK Debt Management Office (2025), Additional Information and Engagement on the Digital Gilt Instrument (DIGIT). Bank of England (2025), Digital Securities Sandbox Dashboard. Bank of England (2025), Renewed RTGS: Digital public infrastructure as a platform for innovation – speech by Dave Ramsden. Bank of England (2021), Bank of England publishes policy for omnibus accounts in RTGS. Bank of England (2025), The National Payments Vision. Bank of England (2025), International payment rails: the value of a harmonised gauge – speech by Sarah Breeden. Bank of England (2025), Building tomorrow’s markets: the digitalisation of finance – speech by Sasha Mills. Ray, H (2025), Stablecoins, Tokens, and Global Dominance, International Monetary Fund. Bank of England (2024), TRUSTED AI: Ethical, safe, and effective application of artificial intelligence at the Bank of England – speech by James Benford. Bank of England (2024), TRUSTED AI: Ethical, safe, and effective application of artificial intelligence at the Bank of England – speech by James Benford; Bank of England (2024), A data revolution: Built together, for everyone – speech by James Benford. Bank of England (2025), The Bank’s artificial intelligence (AI) strategy. Bank of England (2019), Staff Working Paper No. 831: Predicting bank distress in the UK with machine learning. Bank of England (2021), Staff Working Paper No. 923: Forecasting with machine learning methods and multiple large data sets. US Department of the Treasury (2025), G7 Cyber Experts Group Statement on Artificial Intelligence and Cybersecurity. IAIS (2025), The IAIS publishes Application Paper on the supervision of artificial intelligence. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2025), UK Deposit Takers Supervision: 2025 priorities; Basel Committee on Banking Supervision (2013), Principles for effective risk data aggregation and risk reporting. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2024), Forecasting for monetary policy making and communication at the Bank of England: a review; Bank of England (2024), Response of the Bank of England to the Bernanke review of forecasting for monetary policy making and communication at the Bank of England. Bank of England (2025), Bank of England Agenda for Research, 2025-2028. Bank of England (2025), FSiF – Artificial intelligence in the financial system. Bank of England (2025), Artificial Intelligence Consortium minutes – May 2025. Over the past 12 months, CMORG has published an AI Baseline Guidance Review and two AI-focused severe but plausible scenarios, articulating how Generative AI could be utilised to overcome traditional identification and authentication controls. CMORG has also developed an AI Shared Responsibility Model, providing an agreed structure for managing how AI services are implemented between client firm and provider. Bank of England and FCA (2019), Machine Learning in UK financial services; Bank of England and FCA (2022), Machine Learning in UK financial services; Bank of England and FCA (2024), Artificial Intelligence in UK financial services. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. Bank of England (2024), Engaging with the machine: AI and financial stability – speech by Sarah Breeden. FSB (2024), The Financial Stability Implications of Artificial Intelligence. Bank of England (2025), FSiF – Artificial intelligence in the financial system. Materiality is a rating of the use case impact which could include quantitative and qualitative measures. The full definition can be found in FCA (2024), Definitions and Bank of England and FCA (2024), Artificial intelligence in UK financial services – 2024. Bank of England and FCA (2024), Artificial intelligence in UK financial services – 2024. Bank of England (2025), FSiF – Artificial Intelligence in the financial system. AI refers to the simulation of human intelligence by machines, including the use of computer systems, which have the ability to perform tasks that demonstrate learning, decision making, problem solving, and other tasks which previously required human intelligence (in line with the definition of AI used in the joint Bank and FCA Survey on AI in UK financial services – 2024 and the Bank’s FSiF – Artificial Intelligence in the financial system). One example is the Payments Vision Delivery Committee (PVDC), established as part of the National Payments Vision, comprising senior representatives from HM Treasury, the Bank, the FCA, and the Payment Systems Regulator. The PVDC will publish its strategy for retail payments infrastructure this autumn, and a Payments Forward Plan by the end of the year. Bank of England (2025), The National Payments Vision. CMORG supports the operational resilience of the finance sector through public-private collaboration. CMORG (2025), The Cross Market Operational Resilience Group. The AI Consortium is a platform for public-private engagement to gather input from stakeholders on the capabilities, development, and use of AI in UK financial services. Bank of England (2025), Artificial Intelligence Consortium. Bank of England (2025), International payment rails: the value of a harmonised gauge – speech by Sarah Breeden. Monetary Authority of Singapore (2023), Interlinking Networks Technical Whitepaper. The DSS facilitates the use of developing technology such as distributed ledgers in the issuance, trading and settlement of securities in the UK. Bank of England (2024), Digital Securities Sandbox (DSS). HM Treasury and UK Debt Management Office (2025), Additional Information and Engagement on the Digital Gilt Instrument (DIGIT). Bank of England (2025), RTGS 2: a launchpad for innovation − speech by Victoria Cleland. DPIs are defined as ‘shared digital systems that are secure and interoperable and that can support the inclusive delivery of and access to public and private services across society’. Organisation for Economic Co-Operation and Development (2024), Digital public infrastructure for digital governments. HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. Bank of England (2023), The Bank of England’s policy on outsourcing and third party risk management for Financial Market Infrastructures (FMIs). Agentic AI is defined as ‘systems which can take autonomous action to achieve specified goals by utilising tools, learning from feedback, and adapting to dynamic environments’. Bank of England (2025), FSiF: Artificial Intelligence in the financial system. PRA (2025), Prudential Regulation Authority Business Plan 2025/26. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. Bank of England (2025), FSR – July 2025. Bank of England (2025), Governor letter to the Chancellor on FMIC recommendations. Bank of England (2025), FSR – July 2025. The Bank has a secondary objective to ‘facilitate innovation in the provision of financial market infrastructure (FMI) services’, as outlined under the Financial Services and Markets Act (FSMA) 2023. As part of this work, the Bank launched an FMI innovation survey to gather their insights on the Bank’s approach to innovation in March-April 2025. Bank of England (2025), The Bank of England’s supervision of financial market infrastructures – Annual Report 2025. Department for Science, Innovation, and Technology and the Behavioural Insights Team (2025), The Impact of Technology Diffusions on Growth and Productivity. Technological innovation may also require significant complementary investments, such as organisational redesign, improvements in businesses processes, and training, among other investments. Brynjolfsson, E et al (2021), The Productivity J-Curve: How Intangibles Complement General Purpose Technologies, American Economic Journal: Macroeconomics Vol 13(1), pages 333–72. Bergeaud, A et al (2014), Productivity Trends from 1890 to 2012 in Advanced Countries, Banque de France Working Paper No. 475. Bank of England (2025), Financial Stability Report (FSR) – July 2025. HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. Department for Science, Innovation, and Technology (2025), AI Opportunities Action Plan; Innovate Finance (2025), UK FinTech Retains Second Spot in Global Investment Rankings Amidst Tough Market Conditions. Bank of England (2025), Innovation and regulation – striking the balance – speech by David Bailey. Acemoglu, D (2023), Harms of AI, in Bullock, J B et al (eds), The Oxford Handbook of AI Governance, Oxford University Press. Harari, D (2017), Productivity in the UK, House of Commons Library. GFMA (2023), The impact of Distributed Ledger Technology in Global Capital Markets. Oxford Economics (2025), Quantum Computing could boost UK productivity and GDP growth, but government support is crucial. Government Office for Science and the Department for Science, Innovation and Technology (2025), The wider economic impacts of emerging technologies in the UK. Weston, T (2023), Economic growth, inflation and productivity, House of Lords Library. These technologies are often called ‘general purpose technologies’. Bresnahan, T F and Trajtenberg, M (1995), General purpose technologies ‘Engines of growth’?, Journal of Econometrics; Bergeaud, A et al (2014), Productivity Trends from 1890 to 2012 in Advanced Countries, Banque de France Working Paper No. 475. HM Treasury (2025), Financial Services Growth and Competitiveness Strategy. Back to top