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NEXT-GEN AI DECISION SUPPORT IN SOFTWARE ENGINEERING: LEVERAGING COMPLEXITY WITH QUANTUM COMPUTING, DEVOPS AUTOMATION, AND RESPONSIBLE MACHINE LEARNING

Author Information
Name: Simran, Sonu Kumar & Er Priyanka Devi
Country: India
Publication Details
Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 705-713
DOI: https://doi.org/10.5281/zenodo.19109050
Abstract
ABSTRACT—
Utilizing next-generation AI decision support systems driven by quantum computing, DevOps automation, and responsible machine learning is the way of the future as software engineering struggles with increasing complexity. Current computational boundaries are broken by quantum computing, which makes it possible to solve complex algorithms and large amounts of data quickly. DevOps automation integrates AI to remove bottlenecks and increase efficiency while orchestrating smooth cooperation. Fundamentally, responsible machine learning acts as the moral compass, guaranteeing that decisions made by AI are open, accountable, and consistent with social norms. When these three ideas come together, software development and management undergo a radical change. They handle the complexities of contemporary software while improving speed and dependability by streamlining decision- making. This study presents a framework for Next Generation AI Decision Support in Software Engineering, resulting in an AI- driven "software engineer" capable of managing the difficulties of modern development. This intelligent system uses quantum computing to solve complicated software design difficulties with its improved processing capabilities. Integrating DevOps automation to speed up continuous integration, delivery, and deployment ensures agile, real-time responsiveness to changing needs. The
incorporation of responsible machine learning concepts, which address concerns of bias and interpretability while maintaining privacy, enables ethical and transparent decision-making. Through case studies and performance evaluations, this AI-driven software engineer has proven to optimize resources, reduce development timelines, and improve software quality, laying the groundwork for future autonomous engineering systems that support complex decision-making and operational efficacy.

Index Terms—Ethical AI, Quantum Computing, DevOps Au- tomation, Decision Support Systems, Autonomous engineering systems, Predictive Analytics, Automated Workflows
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