Abstract Public and private investment in quantum technologies has grown rapidly, yet evidence on the demand side—which firms are adopting, for what applications, on what timelines, and against which barriers—rests largely on industry surveys with undisclosed sampling frames. We report a descriptive, prevalence-style analysis of quantum technology adoption based on a census-approach survey of the complete population of listed firms in Japan. A postal questionnaire was mailed to all 3,890 firms listed on Japanese stock exchanges (December 2025–January 2026); 154 firms returned analyzable questionnaires (crude response rate 4.0%). Because the full sampling frame with firm attributes was available, response propensities were modeled (AUC = 0.671) and inverse-probability weighting (IPW) was used to adjust prevalence estimates for response bias; population totals were obtained with Horvitz–Thompson estimators. Proportions are reported with Wilson 95% confidence intervals. An estimated 59.9% (95% CI 50.5–68.6) of listed firms express at least interest in quantum technologies, but only 16.0% (10.3–24.0) have reached even the PoC-planning stage and 7.2% (3.7–13.6; ≈276 firms) have begun concrete activities. Interest concentrates in quantum machine learning (48.5% of engaged firms), chemistry/simulation (45.6%), and optimization (44.7%). Expected timelines are dominated by indecision: 64% of engaged firms answering could not name a target year for full commercialization, and only 3% expect it by 2030. The most prevalent barrier is the internal shortage of quantum talent (85.3% of engaged firms); the barriers associated with progression from interest to active engagement, however, are the lack of collaboration partners and the lack of a basis for decision-making. The most requested facilitator is expert demonstration of business potential (43.7%), far ahead of government financial support (9.7%). Interest in quantum technologies is widespread among Japanese listed firms, but concrete planning is rare and capability investments are concentrated in a small set of large firms. The findings highlight the importance of use-case demonstration, partnership brokering, and talent development alongside financial support.
Abstract Public and private investment in quantum technologies has grown rapidly, yet evidence on the demand side—which firms are adopting, for what applications, on what timelines, and against which barriers—rests largely on industry surveys with undisclosed sampling frames. We report a descriptive, prevalence-style analysis of quantum technology adoption based on a census-approach survey of the complete population of listed firms in Japan. A postal questionnaire was mailed to all 3,890 firms listed on Japanese stock exchanges (December 2025–January 2026); 154 firms returned analyzable questionnaires (crude response rate 4.0%). Because the full sampling frame with firm attributes was available, response propensities were modeled (AUC = 0.671) and inverse-probability weighting (IPW) was used to adjust prevalence estimates for response bias; population totals were obtained with Horvitz–Thompson estimators. Proportions are reported with Wilson 95% confidence intervals. An estimated 59.9% (95% CI 50.5–68.6) of listed firms express at least interest in quantum technologies, but only 16.0% (10.3–24.0) have reached even the PoC-planning stage and 7.2% (3.7–13.6; ≈276 firms) have begun concrete activities. Interest concentrates in quantum machine learning (48.5% of engaged firms), chemistry/simulation (45.6%), and optimization (44.7%). Expected timelines are dominated by indecision: 64% of engaged firms answering could not name a target year for full commercialization, and only 3% expect it by 2030. The most prevalent barrier is the internal shortage of quantum talent (85.3% of engaged firms); the barriers associated with progression from interest to active engagement, however, are the lack of collaboration partners and the lack of a basis for decision-making. The most requested facilitator is expert demonstration of business potential (43.7%), far ahead of government financial support (9.7%). Interest in quantum technologies is widespread among Japanese listed firms, but concrete planning is rare and capability investments are concentrated in a small set of large firms. The findings highlight the importance of use-case demonstration, partnership brokering, and talent development alongside financial support.
Abstract As quantum technologies move toward practical application, organizations face the question of whether they are prepared to adopt them, yet, to our knowledge, no validated instrument exists for measuring organizational readiness for quantum technology adoption. This study developed the Quantum Technology Readiness Scale (QTRS) and provides initial psychometric evidence for it. A mail survey of all 3,890 publicly listed firms in Japan yielded 154 responses, and supplementary eligibility analyses suggested that respondents represented roughly 8–11% of the practically relevant target population. Exploratory factor analysis (maximum likelihood, oblimin rotation; n = 102) of an initial pool of 15 Likert-type items supported a two-factor structure with 10 retained items: Implementation Capacity (7 items, α = 0.88, ω = 0.88) and Perceived Benefits (3 items, α = 0.78, ω = 0.79), with a weak inter-factor correlation (ϕ = 0.28). The two dimensions showed sharply asymmetric validity patterns. Implementation Capacity differed across adoption stages (p < 0.001), was strongly associated with advanced adoption (odds ratio = 6.48 per scale point, 95% CI [2.44, 17.23]), and correlated with quantum technology budgets (ρ = 0.46); Perceived Benefits was uniformly high and unrelated to any behavioral criterion. Firms thus broadly expect quantum technologies to deliver value (M = 3.84 on a 5-point scale) but report low implementation capacity (M = 2.61), and it is capacity—not expectation—that distinguishes firms engaged in concrete adoption activities. The QTRS offers a psychometrically grounded alternative to checklist-style quantum readiness assessments; confirmatory validation in larger samples is the immediate next step. JEL Classification: O32 , O33 , L20
With recent advancements in quantum computing technology, companies have begun considering replacing or jointly utilizing their existing classical computing resources with quantum computing. Despite initial research on the examination of the adoption considerations for quantum computing, there is a lack of studies investigating the conditions that influence the adoption of quantum computing technology. Therefore, the purpose of this study is to identify and analyze the key factors that drive or hinder companies' intention to adopt quantum computing technology. Building on the theory of innovation diffusion and integrating insights from the adoption of multiple emerging technologies, this research aims to extend the understanding of quantum computing adoption dynamics. Specifically, drawing on the theory of innovation diffusion and existing literature related to the adoption of multiple emerging technologies, this research proposes the following research questions to identify the factors influencing the adoption intention of quantum computing. The study employed a Sequential Explanatory design, first exploring the topic through literature and interviews with 11 quantum computing experts, then quantifying findings with a questionnaire survey with 250 IT decision-makers within Korean companies, analyzed using PLS-SEM and MGA. Research findings revealed that belief in quantum superiority, quantum advantage, continuous budget allocation, and regulatory support significantly and positively influenced quantum computing adoption, whereas organizational resistance had the most substantial negative impact. Furthermore, firm size and industry significantly moderate these adoption intentions. Interestingly, companies expressed a desire to adopt quantum computing despite uncertainties. Theoretically, this study contributes to innovation diffusion theory by contextualizing its application to the adoption of a highly complex and nascent technology such as quantum computing. Practically, the findings offer actionable implications for policymakers and business leaders by illuminating the key drivers and barriers that must be addressed to promote quantum computing adoption. • Study explores factors impacting companies’ quantum computing adoption intention. • It uses a modified innovation adoption process to identify influencing factors. • Quantum belief, funding, and regulation boost quantum adoption. • Organizational resistance, financial risk, and weak co-creation hinder quantum adoption. • Firm size and type of industry significantly moderate quantum adoption intention.
Quantum computing has evolved from a largely theoretical discipline into a field of growing interest for commercial and industrial applications. Recent advances in quantum hardware, algorithms, and cloud-based access have enabled early experimentation outside academic environments, raising questions about its potential impact on real-world decision-making and operational problems. This paper provides an overview of the current state of quantum computing with a focus on its emerging relevance in commercial contexts. It examines the categories of problems that have attracted attention from industry, particularly those involving high combinatorial complexity such as optimization, scheduling, logistics, and resource allocation. The analysis also reviews the global landscape of companies and initiatives engaged in quantum computing, highlighting different technological approaches, maturity levels, and regional characteristics. In parallel, the paper discusses the principal challenges and limitations that constrain widespread adoption, including hardware immaturity, algorithmic readiness, cost factors, and organizational requirements. By considering both opportunities and risks, this study aims to present a balanced and realistic perspective on the role quantum computing may play in business environments. The objective is to clarify the current position of quantum computing within the broader technological landscape and to support informed interpretation of its potential, limitations, and future trajectory in commercial applications.
The MIT Quantum Index Report 2026 provides a comprehensive, data-driven assessment of the evolving quantum-technology landscape. As quantum technologies progress from scientific promise toward practical deployment, decision-makers need clear, accessible measures of technical capability, investment, workforce development, policy and public engagement. This second edition expands and updates the Quantum Index Report's analysis of quantum computing and networking. It tracks developments across research, industry, education, government and society. Drawing on academic, commercial, and policy sources, the report synthesizes trends and visualizes change over time to support informed comparison and discussion. The Quantum Index Report is intended as a nonpartisan public resource for business leaders, educators, policymakers, researchers and the broader public. Its aim is to reduce the complexity of a rapidly changing field while clarifying both its opportunities and remaining challenges.
This study examines the transformative role of Quantum Artificial Intelligence (Quantum AI) in advancing computational intelligence through quantum-enhanced machine learning frameworks. Using a quantitative, descriptive, and analytical research design, primary data were collected from 400 respondents across academic, research, and industry domains via a structured questionnaire. The analysis applied mean, percentile, and rank-based techniques to evaluate key constructs, including transformational impact, adoption challenges, industry applications, and future potential. Findings indicate that Quantum AI enhances optimization efficiency, predictive analytics, and decision-making, outperforming conventional models. However, challenges such as hardware scalability, high implementation costs, and skill shortages limit widespread adoption. The study also highlights its impact across healthcare, finance, cybersecurity, and data analytics. Overall, Quantum AI demonstrates strong strategic potential for next-generation intelligent systems and competitive advantage.
Purpose The financial services sector is on the brink of a substantial transformation as quantum computing (QC) promises unprecedented speeds for processing data, particularly in the areas of accounting, risk management, trading and fraud detection. Such cutting-edge technology transforms how financial institutions handle large volumes of financial data and intricate transactions by leveraging qubits to conduct complex computations exponentially faster than classical computers. However, the crucial question here is as follows: Are financial firms ready to adopt quantum technology? This study aims to examine QC adoption intention and technological readiness for QC adoption (TRQA) among accounting and auditing firms (AAFs). Design/methodology/approach This study used an online validated and reliable survey to estimate an integrated model of technology–organization–environment-technology acceptance model-resource dependence theory. It gathered responses from AAFs and analyzed them using partial least squares structural equation modeling. Findings The research revealed that QC adoption intention in the financial services sector was fostered by vendor ecosystem, competitive pressure, government support, relative advantage, top management support and perceived usefulness. In contrast, ease of use failed to report such a result. Behavioral adoption intention was found to be a positive driver for TRQA. The inclination to embrace QC in the accounting and finance sector could encourage efforts to build the necessary skills and resources, thereby improving technological preparedness and enabling organizations to fully leverage the advantages of quantum technology. Results also showed that organizational innovation climate-moderated interaction of QC adoption intention on firms’ TRQA was significant. Originality/value To the best of the authors’ knowledge, this attempt is likely among the first to empirically investigate technological readiness for the adoption of QC. It not only advances scholarly conversations on QC but also delivers actionable strategies for stakeholders to boost businesses’ readiness for this emerging revolutionary technology.