Role Of Core Computer Science Branch in AI Tools Development
Prof. Thange Sanket Dhondibhau · Zenodo (CERN European Organization for Nuclear Research) · 2026
The development of modern Artificial Intelligence (AI) tools is deeply rooted in the fundamental principles of core Computer Science (CS) branches, including algorithms, data structures, operating systems, databases, computer networks, software engineering and theory of computation. This paper examines the critical role these core CS disciplines play in enabling the design, efficiency, scalability and reliability of AI tools such as machine learning frameworks, large language models, intelligent code assistants, and automated decision-making systems. It highlights how algorithmic efficiency underpins model training, and inference, data structures support large-scale data management, operating systems, and computer architecture enable high-performance computation, and database, and networking concepts facilitate distributed, and cloud-based AI systems. Additionally, the study emphasizes the importance of software engineering practices in ensuring maintainability, reproducibility, and ethical deployment of AI tools. Through an analytical review of existing literature, and real-world AI systems, this research demonstrates that advances in AI tools are not isolated innovations but are the result of strong integration with core CS foundations. The paper concludes that sustained progress in AI tool development depends on reinforcing core Computer Science knowledge, making it essential for both researchers, and practitioners in the AI domain.