The rapid convergence of artificial intelligence, robotic process automation, cloud-native computing, and advanced data analytics has given rise to hyperautomation as a defining paradigm of contemporary digital transformation. Within the evolving context of Industry 5.0, hyperautomation is no longer confined to efficiency-driven task automation but is increasingly oriented toward human-centric, resilient, and sustainable industrial ecosystems. This research article presents an extensive theoretical and conceptual examination of multimodal hyperautomation architectures, grounded strictly in existing scholarly literature, with particular emphasis on augmented intelligence, cloud-native infrastructures, intelligent robotic process automation, Internet of Things–enabled analytics, and data-driven decision-making frameworks. Drawing upon established research on hyperautomation, Industry 4.0 and 5.0 transitions, robotic process automation implementation models, cloud computing optimization, and real-time analytics, this study synthesizes a unified perspective that positions hyperautomation as a socio-technical system rather than a purely technological construct. The article elaborates in depth on how multimodal AI systems enable contextual awareness, adaptive orchestration, and cognitive augmentation across complex industrial workflows. Methodologically, the study adopts a qualitative integrative research design, combining structured literature synthesis with conceptual modeling to derive an original framework for Industry 5.0-oriented hyperautomation. The results highlight how the integration of augmented intelligence, cloud-native scalability, and cognitive automation transforms traditional automation pipelines into adaptive, learning-driven ecosystems capable of aligning business strategy, operational execution, and human expertise. The discussion critically examines organizational, ethical, and architectural implications, including governance challenges, workforce transformation, and the balance between autonomy and human oversight. By offering a deeply elaborated, theoretically grounded contribution, this article advances academic discourse on hyperautomation while providing a robust conceptual foundation for future empirical research and industrial implementation in the era of Industry 5.0.

Hyperautomation, Industry 5.0, Augmented Intelligence, Cloud-Native Architecture

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