Context-Aware AI Assistants in Oracle Fusion ERP for Real-Time Decision Support
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P109Keywords:
Oracle Fusion ERP, Context-Aware AI, Oracle Digital Assistant, Machine Learning, Real-Time Analytics, Decision Support, Conversational AIAbstract
The increasing complexity and dynamism of Enterprise Resource Planning (ERP) systems demand sophisticated tools to assist users in real-time decision-making. Oracle Digital Assistant (ODA), when integrated with Machine Learning (ML) models and advanced analytics, presents a powerful paradigm for enhancing user workflows in Oracle Fusion ERP. This paper examines the development and deployment of context-aware AI assistants within Oracle Fusion ERP to provide intelligent, in-the-moment recommendations that support informed decision-making. We present a multi-layered architecture leveraging conversational interfaces, embedded analytics, and predictive ML models. By analyzing real-world use cases such as procurement, finance, and human resources, we illustrate how such assistants can reduce decision latency, increase operational accuracy, and improve user satisfaction. The methodology includes the training of domain-specific ML models, integration of ODA using RESTful APIs, and a contextual decision support framework. Experimental results demonstrate significant improvements in decision accuracy and response time. Finally, the paper provides insights into future advancements, challenges in adoption, and broader implications for intelligent enterprise systems
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References
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