The Convergence of Computer Engineering and Artificial Intelligence: Exploring Modern Software Developments

Abstract

AI and Computer Engineering are combining to revolutionize software development. They encourage creativity, enhance functionality, and increase efficiency. As AI-driven tools and frameworks become indispensable to the development of today, their merging with CE is changing the game and making it possible to create intelligent, adaptable systems that can solve the most challenging problems in multiple industries.

This study aims to investigate where artificial intelligence and computer engineering intertwine in modern software development, specifically by looking into methods that enhance innovation, functionality, and efficiency in software through integrated AI-driven tools, frameworks, and performance measures.A three-phase mixed-methods approach was adopted. The secondary data analysis included pertinent literature and open-source code repositories, structured surveys, and interviews of fifty industry professionals. While qualitative analysis was done by applying thematic coding to find trends, obstacles, and possibilities in AI integration, quantitative analysis focused on performance indicators such as execution speed, accuracy, and memory utilization.

The most widely used AI frameworks are TensorFlow and PyTorch due to their performance and flexibility. The industry-specific trends have been identified with different priorities: healthcare focuses on accuracy (77.5%), retail on the execution speed (55 ms) and minimal resource usage, and finance on balanced optimization. Major challenges were seen in the form of barriers such as a high learning curve (20%), scalability issues (25%), and compatibility issues (30%).The report emphasizes that better tools, increased cross-platform support, and thorough training are needed to overcome the hurdles related to the adoption of AI. It identifies industry-specific needs for AI software optimization and provides useful advice on how to successfully use AI technology in sectors like healthcare, retail, and finance.

Specific Contribution: This study provides practical insights into how AI is revolutionizing software development. It provides a strong analytical framework to assess performance metrics and solve integration issues by analyzing industry-specific trends and trade-offs in AI integration. This advances our understanding of CE-AI convergence and guides future research and development in AI-augmented systems.