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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.18635996 |
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| _version_ | 1866901746143461376 |
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| author | Mahesh Reddy Pathoori |
| author_facet | Mahesh Reddy Pathoori |
| contents | <div> <p>Artificial Intelligence (AI) significantly enhances Business Intelligence (BI) by enabling proactive, data-informed decision-making in enterprise environments. This paper introduces the AI-Augmented Business Intelligence (AI-ABI) framework—a comprehensive, scalable model that integrates AI across the entire BI lifecycle. By tracing BI’s evolution from static reporting tools to AI-driven analytics, the study highlights the transition towards augmented analytics and decision intelligence. The AI-ABI framework supports intelligent data integration, predictive and prescriptive analytics, real-time decision support, and continuous learning. It addresses key challenges such as data governance, system interoperability, ethical concerns, and workforce readiness. Applications across finance, telecommunications, healthcare, government, retail, and manufacturing sectors show measurable improvements in risk detection, operational efficiency, and strategic agility. Empirical results validate enhancements in accuracy, scalability, and return on investment. Future advancements including generative AI, federated learning, quantum computing, and augmented reality are explored to position AI-ABI as a next-generation decision-making platform. This research sets a new benchmark for ethical, scalable, and intelligent enterprise BI systems.</p> </div> <div> <div> </div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18635996 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI-Augmented Business Intelligence: A New Framework For Enterprise Decision Systems Mahesh Reddy Pathoori <div> <p>Artificial Intelligence (AI) significantly enhances Business Intelligence (BI) by enabling proactive, data-informed decision-making in enterprise environments. This paper introduces the AI-Augmented Business Intelligence (AI-ABI) framework—a comprehensive, scalable model that integrates AI across the entire BI lifecycle. By tracing BI’s evolution from static reporting tools to AI-driven analytics, the study highlights the transition towards augmented analytics and decision intelligence. The AI-ABI framework supports intelligent data integration, predictive and prescriptive analytics, real-time decision support, and continuous learning. It addresses key challenges such as data governance, system interoperability, ethical concerns, and workforce readiness. Applications across finance, telecommunications, healthcare, government, retail, and manufacturing sectors show measurable improvements in risk detection, operational efficiency, and strategic agility. Empirical results validate enhancements in accuracy, scalability, and return on investment. Future advancements including generative AI, federated learning, quantum computing, and augmented reality are explored to position AI-ABI as a next-generation decision-making platform. This research sets a new benchmark for ethical, scalable, and intelligent enterprise BI systems.</p> </div> <div> <div> </div> </div> |
| title | AI-Augmented Business Intelligence: A New Framework For Enterprise Decision Systems |
| url | https://doi.org/10.5281/zenodo.18635996 |