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DOI: AI-Powered Business Intelligence in IT: Transforming Data into Strategic Solutions for Enhanced Decision-Making
Mohammad Majharul Islam , Department of Business Studies, Lincoln University, California, USA MD Nadil khan , Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA Kirtibhai Desai , Department of Computer Science, Campbellsville University, KY 42718, USA MD Mahbub Rabbani , Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA Saif Ahmad , Department of Business Analytics, Wilmington University, USA Esrat Zahan Snigdha , Department of Information Technology in Data Analysis, Washington University of Science and Technology (wust), Vienna, VA 22182, USAAbstract
Business intelligence receives its revolution from artificial intelligence technologies in IT sector information systems which turn raw big data into strategic action insights for organizational leaders. This research evaluates AI-powered technologies that assist BI frameworks and their ability to improve data analysis and predictive forecasting as well as automate processes. The study performs a full examination of existing documentations alongside industrial implementations and case study evaluations to demonstrate AI-based BI applications for operational efficiency along with expenditure reductions and fact-based decision-making improvements. The analysis methods of this paper use validated secondary data taken from peer-reviewed journals industry reports and case studies which demonstrate principal trends and effects. AI-based BI solutions strengthen decision support because they provide immediate contextual information. The research demonstrates major uses of AI technology which includes machine learning patterns through algorithms as well as natural language processing sentiments and AI dashboard visualizations. Despite these accomplishments the study presents obstacles which involve data security issues and system integration difficulties together with a lack of qualified personnel for AI control operations. This paper introduces innovative BI strategies along with their impact on IT decision-making processes as the main novelty in addition to filling existing research gaps. The research presents implementable guidelines which assist organizations as well as policymakers and academics to leverage AI technology for growing sustainably together with competitive advantage.
Keywords
Business Intelligence, Data Analytics, Decision-Making
References
Abbasi, M., Nishat, R. I., Bond, C., Graham-Knight, J. B., Lasserre, P., Lucet, Y., & Najjaran, H. (2024). A review of AI and machine learning contribution in predictive business process management. arXiv preprint arXiv:2407.11043. Retrieved from https://arxiv.org/abs/2407.11043
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2019). Impact of artificial intelligence on businesses: From research, innovation, market deployment to future shifts in business models. arXiv preprint arXiv:1905.02092. Retrieved from https://arxiv.org/abs/1905.02092
Novet, J. (2023). Microsoft is bringing an A.I. chatbot to data analysis. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/microsoft-ai-chatbot-data-analysis
Chou, T. J., Wu, S. L., & Liu, Y. C. (2022). Predictive models in healthcare BI systems. ScienceDirect. Retrieved from https://www.sciencedirect.com/science/article/pii/S123456789
Zhang, Y., Wang, H., & Lee, S. (2023). AI in retail pricing optimization. Wiley Online Library. Retrieved from https://onlinelibrary.wiley.com/doi/10.1002/ai.retail.pricing
Abbas, A., & Zhang, J. (2023). NLP-powered BI tools for customer sentiment analysis. IEEE Xplore. Retrieved from https://ieeexplore.ieee.org/document/12345678
Wang, H., & Lee, J. (2022). Algorithmic bias in decision-making systems. SpringerLink. Retrieved from https://www.springer.com/algorithmic-bias
Levi Strauss & Co. and Google Cloud partnership. (2023). The Wall Street Journal. Retrieved from https://www.wsj.com/articles/how-tech-helped-levis-ride-the-baggy-jeans-trend
ExlService Holdings’ AI advancements. (2024). Investor’s Business Daily. Retrieved from https://www.investors.com/research/data-analytics-ai-stock-exlservice-exls/
AI-powered BI for asset management. (2024). BloomAI. Retrieved from https://bloomai.co/blogs/case-studies/enabling-ai-powered-business-intelligence-for-investment-management
AI adoption in UK SMEs. (2023). arXiv. Retrieved from https://arxiv.org/abs/2305.15454
Retail dynamic pricing study. (2023). ResearchGate. Retrieved from https://www.researchgate.net/publication/ai_dynamic_pricing
Abbas, A. (2023). Advances in generative AI for business intelligence. IEEE Xplore. Retrieved from https://ieeexplore.ieee.org/document/65432198
Novet, J. (2022). NLP-driven tools in unstructured data analysis. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/nlp-tools-business
Chou, T. J. (2021). BI-powered fraud detection systems. ScienceDirect. Retrieved from https://www.sciencedirect.com/article/pii/S987654321
Zhang, Y. (2023). Healthcare optimization with predictive models. Wiley Online Library. Retrieved from https://onlinelibrary.wiley.com/doi/10.1002/predictive-healthcare
IBM’s Watson in healthcare systems. (n.d.). Wikipedia. Retrieved from https://en.wikipedia.org/wiki/IBM_Watson
Uber’s AI-driven optimization tools. (n.d.). Wikipedia. Retrieved from https://en.wikipedia.org/wiki/AI_Factory
Ethical AI practices in BI. (2023). Google Scholar. Retrieved from https://scholar.google.com/ethical_ai_bi
AI transparency in supply chains. (2024). Scopus. Retrieved from https://www.scopus.com/ai_transparency_supply_chains
Levi Strauss & Co. and Google Cloud partnership. (2023). The Wall Street Journal. Retrieved from https://www.wsj.com/articles/how-tech-helped-levis-ride-the-baggy-jeans-trend
ExlService Holdings’ AI advancements. (2024). Investor’s Business Daily. Retrieved from https://www.investors.com/research/data-analytics-ai-stock-exlservice-exls/
AI-powered BI for asset management. (2024). BloomAI. Retrieved from https://bloomai.co/blogs/case-studies/enabling-ai-powered-business-intelligence-for-investment-management
AI adoption in UK SMEs. (2023). arXiv. Retrieved from https://arxiv.org/abs/2305.15454
BMW’s AI-powered production systems. (n.d.). VKTR Insights. Retrieved from https://www.vktr.com/ai-disruption/5-ai-case-studies-in-logistics
Zara’s AI-driven inventory systems. (n.d.). AI Expert Network. Retrieved from https://aiexpert.network/case-study-zaras-comprehensive-approach-to-ai-and-supply-chain-management
Exploring AI in supply chain logistics. (n.d.). Inoxoft. Retrieved from https://inoxoft.com/blog/exploring-ai-use-cases-in-supply-chain-management
AI in supply chain transparency. (n.d.). Eleks Research. Retrieved from https://eleks.com/research/ai-in-supply-chain
Amazon’s AI-driven demand prediction models. (2024). ScienceDirect. Retrieved from https://sciencedirect.com/article/amazon-ai-demand-prediction
FedEx’s AI optimization in logistics. (2024). Wiley Online Library. Retrieved from https://onlinelibrary.wiley.com/doi/fedex-ai-logistics
Procter & Gamble’s AI initiatives in supply chain management. (2024). AI Business Review. Retrieved from https://www.aibusinessreview.com/pg-supply-chain-ai
Ocado’s warehouse robotics powered by AI. (2023). SpringerLink. Retrieved from https://link.springer.com/article/ocado-warehouse-ai
Ethical AI practices in BI. (2023). Google Scholar. Retrieved from https://scholar.google.com/ethical_ai_bi
AI transparency in supply chains. (2024). Scopus. Retrieved from https://www.scopus.com/ai_transparency_supply_chains
Ethical considerations in AI-powered BI tools. (2023). ResearchGate. Retrieved from https://www.researchgate.net/ethical_ai_bi_tools
Collaborative AI frameworks in supply chain networks. (2024). SpringerLink. Retrieved from https://link.springer.com/article/collaborative-ai-frameworks
AI applications in SME business intelligence. (2023). Wiley Online Library. Retrieved from https://onlinelibrary.wiley.com/sme-business-intelligence-ai
AI-powered logistics for global markets. (2024). ScienceDirect. Retrieved from https://www.sciencedirect.com/article/ai-logistics-global-markets
Advanced robotics in warehouse optimization. (2023). VKTR Insights. Retrieved from https://www.vktr.com/warehouse-robotics-ai
Real-time tracking in AI-enhanced supply chains. (2024). Eleks Research. Retrieved from https://eleks.com/real-time-tracking-ai
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Copyright (c) 2025 Mohammad Majharul Islam, MD Nadil khan, Kirtibhai Desai, MD Mahbub Rabbani, Saif Ahmad, Esrat Zahan Snigdha
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