A Strategic Decision Dashboard Framework for AI-Augmented IT Resource Allocation and Performance Optimization
Abstract
The rapid expansion of digital ecosystems and the growing complexity of IT infrastructures demand intelligent frameworks for effective resource allocation and performance management. This review explores the development of a Strategic Decision Dashboard Framework that integrates artificial intelligence (AI), predictive analytics, and optimization algorithms to enhance IT resource allocation and operational efficiency. The framework synthesizes real-time monitoring, data visualization, and decision-support models to align technological assets with strategic organizational goals. By leveraging AI-driven insights—such as workload forecasting, anomaly detection, and performance benchmarking—the proposed dashboard enables proactive decision-making and adaptive resource reconfiguration across distributed systems. The study reviews existing literature on AI-enabled IT management, identifies gaps in decision-support architecture, and proposes an integrated approach combining machine learning, reinforcement learning, and multi-criteria decision analysis for performance optimization. Furthermore, the paper emphasizes the importance of transparency, explainability, and governance mechanisms to ensure trustworthy AI deployment in enterprise IT operations. Ultimately, the review highlights how AI-augmented dashboards can transform IT management from reactive problem-solving to predictive and strategic optimization, offering a pathway toward sustainable digital transformation and competitive advantage in modern organizations.
Keywords
AI-augmented decision systems; IT resource allocation; performance optimization; predictive analytics; strategic dashboards; intelligent decision support.
References
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