Publication

Abstract : The convergence of Distributed Ledger Technology, Artificial Intelligence, Extended Reality, and Quantum Computing, collectively known as DARQ technologies, has initiated a transformative shift across industries, economies, and societies. This paper explores the evolution of these disruptive technologies, focusing on their individual trajectories, synergistic integration, and potential impact on innovation. In addressing the lack of integration with analytical frameworks in analyzing technologies DARQ. "DARQ Synergy Model" that will help quantify these interdependencies and the influence that such technologies have over the major sectors in the healthcare, finance, and manufacturing industries. The proposed DSM uses a multi-stage methodology combining temporal data analytics, machine learning-based forecasting, and quantum optimization algorithms. Because the data sources that the DSM uses come from the industrial case studies and industry market reports spanning ten years, the model gives efficiency improvement, adoption rate statistics, and ROI metrics of usage. The DARQ technologies improve innovation by their synergistic rather than isolated deployment. Further, key challenges for the technology under question, including regulation, interoperability, data privacy, and access, are discussed in this research study. The DSM framework is scalable and data-driven in nature and is apt for guiding industries on how to exploit DARQ technologies in a risk-free manner. Lastly, the paper postulates a future research and implementable strategy that involves innovation with a conscience and copartnership in policy-making in order to explore the maximum benefits from such DARQ technologies