Harnessing Context-Aware AI for Smarter DecisionMaking: A New Era in Business Intelligence

AI-based applications have evolved over the last few years. The fusion of AI and context-aware has shown a new direction to application developers. The context-aware AI provides the capacity to collect context data and adapt system behavior accordingly. This paper presents a usecase for complementing business intelligence systems with context-aware and explainable AI, thereby improving the decision-making process. The experiment is conducted on publicly available datasets, evidencing the improvement of the decision-making accuracy on the use of context-aware AI. The result shows that Random Forest Classifier was the most accurate. The real-life case studies are provided in the paper, which proves that the business processes in finance and supply chain management can be improved with the adoption of context aware AI. Their results indicate the growing demand for explainability and agility in AI, providing a direction for enterprises willing to adopt more intelligent and context-based decision support. The research ends by giving practical measures for the feasibility of the several shortcomings and areas, while describing the direction for the appropriate goals seeking to enhance the customer-centric model and ethical AI research and development in the future.