Strategic Integration of AI in Modern Data Management

Title

Strategic Integration of AI in Modern Data Management

Creator

Divakaran, Prakash; Parnami, Tanmay; Gaur, Sonali; Baryah, Neha; Gupta, Komal; Upreti, Kamal

Description

The exponential growth of data from sources such as social media, IoT, and enterprise systems has catalyzed a transformative shift in data management practices. This paper explores the integration of artificial intelligence (AI), edge computing, cloud-native frameworks, and graph-based techniques to support intelligent, low-latency, and scalable data processing across complex ecosystems. It presents a comparative analysis of classical versus modern data architectures, highlighting how technologies like Graph Neural Networks (GNN4TS), reinforcement learning, and large language models (LLMs) enable more adaptive, interpretable, and automated pipelines. The study also addresses challenges in legacy system modernization, time-series modeling, and cyber threat detection while underscoring the role of AI in autonomous database management and metadata enrichment. Further, it examines critical risks - including explainability, adversarial vulnerabilities, concept drift, and privacy preservation - associated with AI-integrated data workflows. A structured overview of emerging paradigms such as neuro-symbolic AI, adaptive governance in multi-agent systems, and the potential of quantum computing provides a future-focused lens on intelligent data ecosystems. The insights presented aim to assist researchers, data engineers, and decision-makers in navigating the evolving landscape of AI-driven data management. 2025 IEEE.

Source

2025 World Skills Conference on Universal Data Analytics and Sciences, WorldSUAS 2025;

Date

01-01-2025

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Artificial Intelligence; Automation; Challenges; Data Management; Traditional Techniques

Coverage

Divakaran P., Himalayan University, Department of Management, Arunchal Pradesh, India; Parnami T., GGSIPU, Dept. of Computer Science & Engineering, New Delhi, India; Gaur S., EMPI Business School, Dept. of Management, New Delhi, India; Baryah N., Chandigarh Group of Colleges, Chandigarh School of Business, Department of Forensic Sciences, Punjab, Mohali, India; Gupta K., Finance Manager Accenture, Bangalore, India; Upreti K., Christ University, Department of Computer Science, Ghaziabad, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833153925-2;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/WorldSUAS66815.2025.11199110

https://www.scopus.com/pages/publications/105022276679?origin=resultslist