This study presents a strategic framework to accelerate India's quantum computing (QC) advancement by leveraging its established foundation. As qc takes root in India, the potential for transformative impact across sectors such as optimization, cryptography, and artificial intelligence becomes significant. This research traces India's growth—from indigenous technology development in the 1970s to its role as a digital economy leader—and explores how this legacy positions India for leadership in the QC domain. A comparative look at classical computing versus quantum computing (Table 1) shows how qubits enable unprecedented computational efficiency, which is essential for complex problem-solving. The framework (figure 1) prioritizes academic and industry needs, addressing skill-building, policy support, and regulatory alignment crucial for effective QC integration. This framework shows the role of universities and research centers in creating QC programs. It also encourages innovation and development of QC applications for specific fields such as healthcare, finance, and logistics. Although there are technical and infrastructure challenges, the study recommends strategies for Indian industries to start using QC, including hybrid approaches to address current limitations. By incorporating human-computer interaction principles, the framework advocates accessible, user-friendly QC platforms. Using the principles of human-computer interaction, the framework promotes easy-to-use, accessible quantum computing (QC) platforms. It evaluates India's readiness for QC by examining skills, institutional preparation, and how well it aligns with global standards. This study seeks to create a QC-ready workforce. Partnerships between industries and universities can accomplish this. The partnership will help elevate India's position in the global QC landscape. Drawing insights from the framework developed by European competencies on quantum technologies it is recommended that basic and advanced QC skills suited to India's specific needs be developed.
This study presents a strategic framework to accelerate India's quantum computing (QC) advancement by leveraging its established foundation. As qc takes root in India, the potential for transformative impact across sectors such as optimization, cryptography, and artificial intelligence becomes significant. This research traces India's growth—from indigenous technology development in the 1970s to its role as a digital economy leader—and explores how this legacy positions India for leadership in the QC domain. A comparative look at classical computing versus quantum computing (Table 1) shows how qubits enable unprecedented computational efficiency, which is essential for complex problem-solving. The framework (figure 1) prioritizes academic and industry needs, addressing skill-building, policy support, and regulatory alignment crucial for effective QC integration. This framework shows the role of universities and research centers in creating QC programs. It also encourages innovation and development of QC applications for specific fields such as healthcare, finance, and logistics. Although there are technical and infrastructure challenges, the study recommends strategies for Indian industries to start using QC, including hybrid approaches to address current limitations. By incorporating human-computer interaction principles, the framework advocates accessible, user-friendly QC platforms. Using the principles of human-computer interaction, the framework promotes easy-to-use, accessible quantum computing (QC) platforms. It evaluates India's readiness for QC by examining skills, institutional preparation, and how well it aligns with global standards. This study seeks to create a QC-ready workforce. Partnerships between industries and universities can accomplish this. The partnership will help elevate India's position in the global QC landscape. Drawing insights from the framework developed by European competencies on quantum technologies it is recommended that basic and advanced QC skills suited to India's specific needs be developed.
In the global race toward quantum computing supremacy and frontier-technology leadership, India has embarked on an ambitious trajectory. With the approval of the National Quantum Mission (NQM)—allocating ₹6,003.65 crore for 2023–24 to 2030–31—and the emergence of indigenous quantum computing hardware such as QpiAI-Indus (25-qubit superconducting full-stack system), India is no longer a mere follower but an active contender in quantum technologies. This research article presents a comprehensive, qualitative and science-backed examination of India’s quantum computing revolution: its foundational research, strategic opportunities, governmental mission, industry implications, and projected roadmap for 2026 and beyond. We begin by situating quantum computing in global context and summarizing India’s historical and emerging contributions. Through a structured literature review, we identify gaps in devices, algorithms, applications and commercialization. Our methods combine a critical survey of peer-reviewed literature (journals, conference papers, white papers) together with policy documents and startup announcements, enabling synthesis of India-specific strengths, bottlenecks and growth levers. Key findings show that India is strengthening core capabilities in superconducting and photonic qubits, quantum communications (e.g., ISRO’s free–space quantum encryption demonstration), quantum sensing/metrology, and ecosystem building (startups, T-Hubs, public-private partnerships). The NQM’s structure of four Thematic Hubs and fourteen Technical Groups across 17 states reflects a strategic system-level design. Of particular note: the QpiAI-Indus quantum computer, supported under NQM, signals India’s first full-stack hardware-software quantum platform. Industry-impact sectors such as finance (quantum optimization), healthcare (drug discovery simulations), materials science (quantum-enabled materials), cybersecurity (post-quantum cryptography), defense and national infrastructure are poised for disruption. Yet significant challenges remain: shortage of quantum-skilled workforce, cryogenic infrastructure, error-correction scalability, IP-ecosystem gaps, and global competition. We discuss strategic opportunities—quantum cloud services, “quantum as a service (QaaS)”, regional quantum hubs like Bengaluru’s planned “Quantum City”, and cross-discipline synergies with AI and advanced materials. We conclude by presenting a forward-looking roadmap to 2030+, emphasizing scalable quantum devices (50-1000 qubits by 2030), ecosystem maturation, export potential, regulatory frameworks, and international collaboration. This research provides policymakers, researchers and industry stakeholders a holistic guide to India’s quantum journey and its implications for 2026 and beyond.
Quantum computing isn't merely another step forward in technology; it represents a leap into an entirely new paradigm for understanding information. By harnessing the strange but powerful principles of quantum mechanics, quantum computers use qubits that can exist in multiple states at once, connect instantly through entanglement, and solve certain problems far faster than any classical machine. This paper explores the fundamentals of quantum computing, from its theoretical roots to the breakthroughs and setbacks shaping its present. We examine the engineering and scientific challenges - from fragile qubits to daunting scalability issues - and the immense promise they hold for fields like cryptography, artificial intelligence, drug discovery, and materials science. Finally, we consider the future impact of this technology, both its opportunities and its risks, and how it may redefine industries, research methods, and even our approach to solving humanity's hardest problems. The purpose of this paper is to examine the fundamental principles, developmental trajectory, current challenges, and prospective impacts of quantum computing across scientific, industrial, and societal domains. Given its potential to reshape computational capabilities and address complex global challenges, this study holds significance for researchers, policymakers, and industry leaders seeking to understand and navigate the transition toward quantum technologies.
Quantum computing, with its revolutionary approach to data processing and problem solving, is poised to redefine the boundaries of modern technology. Unlike classical computing, quantum computing leverages the principles of superposition, entanglement, and quantum parallelism to perform complex computations at unprecedented speeds. As industries worldwide begin to explore and adopt quantum solutions, it becomes imperative for higher education institutions to keep pace with these advancements. This paper explores the critical integration of quantum computing into university curricula, emphasising its potential to drive innovation, enhance research capabilities, and equip students with the skills needed for the quantum driven future. By aligning academic frameworks with cutting edge developments in quantum technology, educational institutions can cultivate a new generation of quantum literate professionals ready to tackle the challenges and seize the opportunities of this emerging era
Quantum Computing (QC) and Artificial Intelligence (AI) have emerged as key technologies in the evolution of Industry 6.0, driving advancements in automation and advanced analytics, and process optimization. Their integration holds the potential to revolutionize sectors such as data science, healthcare, finance, and cybersecurity by enabling faster and more efficient computations through qubits, superposition, and quantum entanglement. However, the lack of structured knowledge regarding specific QC methodologies and applications in AI hinders its optimal implementation and development. Consequently, this study aims to identify the applications and variables associated with QC-AI integration. To this end, a systematic literature review was conducted following the PRISMA 2020 methodology, drawing on studies from Scopus and Web of Science databases. This enabled the analysis of trends, limitations, and opportunities in this technological convergence. This study aims to systematically examine the intersection of quantum computing and artificial intelligence by identifying the key technological features, integration requirements, and sectoral applications that define the current state of the field. The review contributes by mapping existing research, highlighting methodological approaches, and revealing gaps that may guide targeted advancements in hybrid quantum AI systems. The insights generated have the potential to accelerate innovation in high-impact domains such as healthcare, finance, energy, and cybersecurity. The findings indicate that the main advances in QC applied to AI focus on quantum optimization, Quantum Machine Learning (QML), and post-quantum cryptography. Notably, sectors such as energy, healthcare, and finance have shown significant progress in adopting these technologies. For example, in healthcare, QML has been applied to simulate molecular interactions to accelerate drug discovery, and in finance, it enhances predictive models for market behavior. The study concludes that although QC demonstrates substantial potential to enhance AI, its broader adoption remains constrained by reliance on NISQ hardware, the need for effective error correction, and the limited scalability of hybrid quantum classical algorithms. Addressing these challenges will be essential to establishing QML as a cornerstone of technological innovation and digital transformation. Additionally, this review introduces an integrative framework that categorizes key AI QC convergence dimensions and proposes a classification of application areas based on technical requirements and algorithmic capabilities. These contributions aim to guide future experimental validations and hybrid model development.
The rapid advancement of quantum computing technology presents unprecedented opportunities and challenges for global governance. This comprehensive study examines the current landscape of international quantum computing regulation, exploring the delicate balance between fostering innovation and addressing security concerns. Through a mixed-methods approach, including policy analysis, expert interviews, and case studies of key countries and regions, we identify significant fragmentation in regulatory approaches, a pressing need for standardization, and ethical considerations that demand immediate attention. Our findings reveal strong stakeholder support for international cooperation, despite geopolitical tensions, and highlight the risk of a growing "quantum divide" between nations. Based on these insights, we propose a series of recommendations, including the establishment of an International Quantum Governance Forum, the adoption of a risk-based adaptive regulatory framework, and the implementation of a Global Quantum Literacy Initiative. This research contributes to the ongoing dialogue on quantum technology governance and provides a roadmap for policymakers, researchers, and industry leaders to navigate the complexities of regulating this transformative technology. By addressing these challenges proactively, we can harness the full potential of quantum computing while mitigating its risks, ultimately shaping a quantum future that benefits all of humanity.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.