A Hybrid Explainable AI and Deep Learning Framework for Intelligent Decision Support in Smart Digital Ecosystems
Explainable Artificial Intelligence, Deep Learning, Intelligent Decision Support Systems, Smart Digital Ecosystems, Hybrid Artificial Intelligence
AuthorsAbstractThe increasing complexity of smart digital ecosystems has accelerated the adoption of artificial intelligence (AI)-driven decision support systems capable of processing large-scale, heterogeneous data for intelligent and timely decision-making. Among contemporary AI technologies, deep learning has demonstrated exceptional predictive capabilities; however, its limited interpretability has raised concerns regarding transparency, trust, and accountability in critical decision environments. Explainable Artificial Intelligence (XAI) has emerged as a promising solution to address these limitations by providing meaningful insights into model behavior while preserving predictive performance. This narrative review critically examines the convergence of deep learning and XAI in the development of hybrid intelligent decision support frameworks for smart digital ecosystems. The review synthesizes recent advances in intelligent decision support systems, deep learning architectures, explainability techniques, hybrid XAI–deep learning models, and their applications across healthcare, manufacturing, finance, transportation, smart cities, and the Industrial Internet of Things. It further discusses emerging technologies, including digital twins, federated learning, and multimodal AI, that are reshaping explainable decision intelligence. In addition, the review identifies key challenges related to scalability, computational complexity, privacy, fairness, ethical governance, and standardized explainability evaluation. The findings indicate that hybrid XAI–deep learning frameworks significantly improve transparency, user trust, and decision reliability while maintaining high analytical performance. This review provides a comprehensive perspective on current developments and highlights future research directions for building trustworthy, scalable, and human-centric intelligent decision support systems in next-generation smart digital ecosystems.
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