2025· International Journal of Artificial Intelligence & Digital Transformation· Vol 7, pp. 01-16· 0 citations
TL;DR
This research proposes an AI Orchestrated Digital Ecosystem (AIODE) framework that combines data acquisition, integration, AI intelligence, digital orchestration, process automation, and decision support layers that enables intelligent decision-making, predictive analytics, resource optimization, and adaptive business operations through AI and machine learning.
Abstract
Artificial Intelligence (AI), cloud computing, IoT, big data analytics, and automation are driving the evolution of digital transformation toward integrated and intelligent enterprise ecosystems. This research proposes an AI Orchestrated Digital Ecosystem (AIODE) framework that combines data acquisition, integration, AI intelligence, digital orchestration, process automation, and decision support layers. The framework enables intelligent decision-making, predictive analytics, resource optimization, and adaptive business operations through AI and machine learning. Performance evaluation using key indicators demonstrates significant improvements in operational efficiency, automation, customer satisfaction, predictive accuracy, and resource utilization compared to traditional enterprise systems. The proposed approach supports scalable, agile, and sustainable enterprise transformation, providing valuable insights for researchers and practitioners developing next-generation intelligent enterprises.
The study concludes that cloud-based AI automation models represent a fundamental technological framework for enabling intelligent digital transformation, empowering organizations to achieve long-term operational excellence, competitive resilience, and sustainable business growth within an increasingly interconnected a...
Shi-Hu Gan· International journal of com...· 0 citations
The results indicate that business intelligence based on AI technology can help improve the quality of decisions in addition to fostering higher operational efficiency, agility of organizations, and securing compliance with the demands of modern competition.
Virendra Gomase· Journal of Intelligent Decis...· 0 citations
An integrated AI-IoT framework for smart manufacturing that continuously acquires machine data, performs real-time analytics, predicts equipment failures, optimizes production scheduling, and supports data-driven decision-making is proposed.
Anand Singh· Journal of Intelligent Decis...· 0 citations
The findings advocate for the integration of AI-powered pipelines within ERP systems as a transformative approach to enable scalable, intelligent, and high-fidelity data processing, essential for next- generation enterprise software resilience and performance.
Yuvaraj Kavala· International Journal of Com...· 0 citations
The proposed framework explains how AI agents can monitor business metrics, detect exceptions, generate contextual explanations, recommend actions, and support executive decision-making while preserving governance, accountability, and responsible AI controls.
Choudhry Bilal Mazhar, Tahani Muneer Algethami· Global academic journal of e...· 0 citations
With the advent of new LLM technology, enterprise AI capabilities, such as LLM-based foundations, RAG and enterprise AIGC, offer new growth opportunities. Cloud-Native AI Orchestration makes these technology foundations well into the enterprise ecosystem. By integrating these capabilities into the enterprise AI Orchest...
Olivia Bennett· International Journal of Int...· 0 citations
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