Navigating AI-Driven Data Management in the Cloud: Exploring Limitations and Opportunities

Manaswini Davuluri

Abstract


The integration of artificial intelligence (AI) with cloud-based data management is transforming how organizations handle vast amounts of data. Cloud platforms offer scalable solutions for storing, processing, and accessing data, while AI technologies enhance the ability to derive insights, automate workflows, and improve decision-making. This study explores the opportunities and limitations of combining AI with cloud data management, focusing on how AI-driven solutions can optimize data accessibility, processing efficiency, and predictive analytics in various sectors, including healthcare, finance, and manufacturing. While AI can help manage large datasets more efficiently, it also presents challenges related to data security, privacy concerns, and compliance with industry regulations. The research discusses how AI-powered algorithms can automate data cleaning, enable real-time analytics, and improve the accuracy of predictions, but also highlights the risks associated with data bias, data integration complexities, and the need for robust cybersecurity measures. By understanding these opportunities and limitations, organizations can strategically implement AI and cloud technologies to unlock new levels of innovation, streamline operations, and ensure secure, efficient data management.


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