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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: October 2025
Volume 10 | Issue 10
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Impact Factor : 8.14
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| Paper Title: | AI-Enhanced Business Intelligence for Digital Enterprises |
| Authors Name: | SWAPNIL SAURAV , Shruti Tyagi , Dheeraj Akula |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200247
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| Published Paper Id: | IJRTI2501020 |
| Published In: | Volume 10 Issue 1, January-2025 |
| DOI: | |
| Abstract: | - Artificial Intelligence (AI) is redefining the landscape of Business Intelligence (BI), enabling organizations to transform raw data into actionable insights that drive strategic decision-making. This paper explores the transformative role of AI-enhanced BI, detailing how advanced technologies such as machine learning, natural language processing (NLP), and automated analytics are revolutionizing data processing and utilization in enterprises. By integrating AI capabilities, BI systems extend beyond traditional descriptive and diagnostic analytics to include predictive and prescriptive functionalities, empowering organizations to anticipate trends, optimize resource allocation, and enhance operational efficiency. The paper presents a comprehensive framework for implementing AI-driven BI, encompassing data integration, model development, and insights delivery. It also addresses critical challenges, including data quality, model interpretability, and scalability, offering practical solutions to overcome these obstacles. Real-world case studies from e-commerce, manufacturing, banking, and IT operations illustrate the tangible benefits of AI-enhanced BI, such as reduced churn rates, optimized supply chains, improved risk management, and enhanced system reliability. Key recommendations highlight the importance of robust data infrastructure, scalable AI platforms, and explainable AI frameworks to ensure successful adoption and user trust. By embracing AI-driven BI, organizations can unlock the full potential of their data assets, fostering innovation, competitiveness, and sustainable growth in a rapidly evolving digital economy. This paper aims to provide both academic and practical contributions to the field, serving as a roadmap for researchers and practitioners seeking to leverage AI for transformative business intelligence. |
| Keywords: | Artificial Intelligence, Business Intelligence, Data-Driven Decision-Making, Predictive Analytics |
| Cite Article: | "AI-Enhanced Business Intelligence for Digital Enterprises", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a126-a132, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501020.pdf |
| Downloads: | 000399 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2501020
Registration ID:200247
Published In: Volume 10 Issue 1, January-2025
DOI (Digital Object Identifier):
Page No: a126-a132 Country: Hyderabad, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2501020 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2501020 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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