From Data to Insights: Leveraging AI and Reciprocal Symmetry for Business Intelligence

Sai Sirisha Maddula; Mohamed Ali Shajahan; Arun Kumar Sandu

doi:10.18034/ajase.v8i1.86

Authors

Sai Sirisha Maddula Front End Developer, Nartal Systems, 2650 US-130 e, Cranbury, NJ 08512, USA
Mohamed Ali Shajahan Sr. Staff SW Engineer, Continental Automotive Systems Inc., Auburn Hills, MI 48326, USA
Arun Kumar Sandu Lead Engineer – Databases, Grab Technology, 777 108th Ave NE Unit 1900, Bellevue, WA 98004, USA

Keywords:

Data Analytics

Artificial Intelligence

Business Intelligence

Machine Learning

Predictive Modeling

Reciprocal Symmetry

Decision Support Systems

Data Visualization

Abstract

This paper examines how business intelligence (BI) uses AI and reciprocal symmetry principles to gain actionable insights from data. The goals are to study the synergy between AI and reciprocal symmetry, their use in BI, and their effects on strategic decision-making. A complete review of AI, reciprocal symmetry, BI literature, research articles, and case studies is used. Secondary data sources are aggregated and evaluated to explain essential concepts and methods in this integrated approach. Significant findings show how reciprocal symmetry-guided AI-driven analytics improves data interpretation and insight production. This integration enhances decision-making, innovation, and industry operations. Policies should address ethical issues, data privacy concerns, and legal frameworks to promote responsible AI adoption and data-driven decision-making transparency. BI can transform with AI and reciprocal symmetry to open new opportunities and gain a competitive advantage. This integrated approach emphasizes constant innovation and adaptation to maximize data potential for strategic business success.

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