Quantum technology and artificial intelligence/ machine learning as strategic enablers to strengthen geopolitical position – United Kingdom perspective
Superpowers such as the US, China and the United Kingdom have recognised quantum and Artificial Intelligence/ Machine Learning (AI/ML) based technologies as strategically important from geopolitical, social and economic perspectives. Those technologies have the potential to shift geopolitical points of gravity and either strengthen or weaken them. This article reviews the United Kingdom's strategic approach to quantum and AI/ML technologies and how those technologies could affect the UK’s geopolitical position.
Superpowers such as the US, China and the United Kingdom have recognised quantum and Artificial Intelligence/ Machine Learning (AI/ML) based technologies as strategically important from geopolitical, social and economic perspectives. Those technologies have the potential to shift geopolitical points of gravity and either strengthen or weaken them. This article reviews the United Kingdom's strategic approach to quantum and AI/ML technologies and how those technologies could affect the UK’s geopolitical position.
Quantum networks are connections between quantum processors and repeaters that produce, exchange, and process quantum information. They serve to optimize the transmission of data in the form of quantum bits, known as qubits. Quantum networks were developed to complement classical networks in order to solve problems currently considered impossible. Among these applications are quantum key distribution (QKD), clock synchronization, secure remote computing, metrology, and distributed consensus. The objective of this work is to investigate the technological foundations, their strategic applications, and consequences in geopolitics. Specifically, this article addresses applications in energy sectors considered strategic, such as oil and gas and nuclear energy. Combined with Artificial Intelligence (AI), this technology can accelerate the discovery of wells and the processing of company analyses, making carbon capture more efficient. In nuclear reactors, quantum computing represents a significant advance. Its advantage lies in its ability to perform more precise simulations of nuclear reactions, for example, neutron scattering, fission and fusion processes, and the exploration of extreme environments that are difficult or impossible to reproduce in the laboratory. Furthermore, this article also analyzes the geopolitical impact of this scenario, emphasizing the technological race and strategic disputes. Next, the challenges and perspectives regarding technical barriers, regulatory issues, and the future of quantum networks in the energy matrix are discussed. To conclude this work, reflections are made on methods to achieve the safe and ethical integration of these quantum technologies.
Quantum networks are connections between quantum processors and repeaters that produce, exchange, and process quantum information. They serve to optimize the transmission of data in the form of quantum bits, known as qubits. Quantum networks were developed to complement classical networks in order to solve problems currently considered impossible. Among these applications are quantum key distribution (QKD), clock synchronization, secure remote computing, metrology, and distributed consensus. The objective of this work is to investigate the technological foundations, their strategic applications, and consequences in geopolitics. Specifically, this article addresses applications in energy sectors considered strategic, such as oil and gas and nuclear energy. Combined with Artificial Intelligence (AI), this technology can accelerate the discovery of wells and the processing of company analyses, making carbon capture more efficient. In nuclear reactors, quantum computing represents a significant advance. Its advantage lies in its ability to perform more precise simulations of nuclear reactions, for example, neutron scattering, fission and fusion processes, and the exploration of extreme environments that are difficult or impossible to reproduce in the laboratory. Furthermore, this article also analyzes the geopolitical impact of this scenario, emphasizing the technological race and strategic disputes. Next, the challenges and perspectives regarding technical barriers, regulatory issues, and the future of quantum networks in the energy matrix are discussed. To conclude this work, reflections are made on methods to achieve the safe and ethical integration of these quantum technologies.
Quantum technologies, spanning communication, sensing, computing, and cryptography, are rapidly emerging as critical paths of geopolitical competition and strategic defence innovation. Unlike traditional technological advances, quantum introduces novel capabilities that fundamentally disrupt established norms of security, intelligence, and diplomatic engagement. This strategic analysis explores the evolving quantum landscape through the dual lenses of diplomacy and geopolitics, with specific implications for defence leaders, policymakers, and industry stakeholders. The benefits and challenges of quantum technologies are examined from a diplomatic and geopolitical perspective to help leaders make informed strategic decisions. Leading powers now recognise quantum as a domain where technological leadership directly translates to geopolitical influence, compelling an intense race for dominance alongside new forms of multilateral diplomacy aimed at managing both risks and opportunities. Quantum technologies do not all have the same operational maturity, but technological progress is accelerating. Post-quantum cryptography demands immediate action, every encrypted communication created today may be harvested and decrypted within the decade by adversaries equipped with quantum capabilities.
Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.
The convergence between artificial intelligence (AI) and quantum computing has global economic and security implications, with applications ranging from advancing pharmaceuticals to breaking traditional encryption. In its national and local state plans, China's policymakers clearly seek global leadership in both of these domains, and encourage synergies between them. Traditional research institutions, namely universities and laboratories, are leading theoretical work and basic research and development for quantum computers to power AI applications, quantum machine learning (ML), and other foundational work. Additionally, China's premier cloud service providers are advancing the two technologies with quantum simulators and online platforms for ML and algorithm development. These companies are driving the commercialization of quantum technologies for industries like pharmaceuticals, materials science, and chemistry. China's investments and rapid advancements warrant analytic attention to avoid technological surprise and inform U.S. policymakers and leaders in these fields. To that end, this chapter identifies key entities pursuing research on the nexus between the two technologies, assesses technology paths and obstacles, and provides indicators for future analyses.