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@article{204244,
        author = {Pankaj Diwakar Katre},
        title = {DATA STRUCTURES IN ARTIFICIAL INTELLIGENCE: FOUNDATIONS, APPLICATIONS, AND FUTURE DIRECTIONS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {2613-2617},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204244},
        abstract = {Artificial Intelligence (AI) has become one of the most transformative technologies of the modern era. Now a days it is the most wide field to explore. The effectiveness of AI systems depends not only on algorithms and computational power but also on the underlying data structures that organize, store, and process information efficiently. Data structures provide the foundation for machine learning, deep learning, natural language processing, robotics, and intelligent decision-making systems. This paper explores the significance of data structures in AI, examining commonly used structures such as arrays, linked lists, stacks, queues, trees, graphs, hash tables, and heaps. The study discusses their applications in AI models, search algorithms, knowledge representation, and optimization techniques. Furthermore, recent developments in large language models and graph-based AI systems are analyzed to demonstrate the evolving role of advanced data structures in intelligent computing. The paper concludes by highlighting future research opportunities in scalable and adaptive data structures for next-generation AI systems.},
        keywords = {Artificial Intelligence, Data Structures, Machine Learning, Graphs, Trees, Neural Networks, Knowledge Representation, Algorithms, Language Models},
        month = {June},
        }