Enhancing software development practices with AI insights in high-tech companies

Artificial Intelligence (AI) is revolutionizing software development practices in high-tech companies, providing transformative insights and tools that enhance productivity, quality, and efficiency. This review explores the integration of AI into software development processes, highlighting its impact on key areas such as code generation, bug detection, project management, and testing. AI-driven tools are enabling developers to automate repetitive tasks, optimize code, and identify potential issues before they become critical, thus reducing development time and improving software reliability. Machine learning algorithms analyze vast amounts of data from past projects to provide predictive analytics, guiding teams in decision-making and resource allocation. Natural language processing (NLP) facilitates more intuitive interactions with development tools, streamlining communication and collaboration among team members. Furthermore, AI enhances continuous integration and continuous deployment (CI/CD) pipelines by automating the testing and deployment stages, ensuring that code changes are seamlessly integrated and deployed with minimal human intervention. By leveraging AI, high-tech companies can adopt more agile methodologies, respond swiftly to market changes, and deliver high-quality software products. The review also discusses the challenges of integrating AI into software development, including the need for substantial initial investment, the complexity of AI models, and the importance of ensuring data privacy and security. Solutions such as fostering a culture of continuous learning, investing in AI-specific training for developers, and establishing robust data governance frameworks are essential for overcoming these barriers. In conclusion, AI-driven insights and tools offer significant advantages for high-tech companies, enabling them to enhance their software development practices, achieve greater efficiency, and maintain a competitive edge in a rapidly evolving technological landscape. Embracing these advancements requires a strategic approach, including investment in AI technologies and training, to fully harness the potential of AI and drive innovation in software development. Keywords: AI, Software Development, High-Tech, Practices, Companies.

Authors

Institutions

Publication Details

Journal
Computer Science & IT Research Journal
Published
2024-08-23
DOI
https://doi.org/10.51594/csitrj.v5i8.1450
Citations
25
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
19.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing software development practices with AI insights in high-tech companies

Patrick Azuka Okeleke, Chinedu Ezeigweneme, Samuel Olaoluwa Folorunsho, Daniel Ajiga
25 citations
Computer Science & IT Research Journal
Software Engineering Techniques and Practices
19.48
article

Enhancing software development practices with AI insights in high-tech companies

Patrick Azuka Okeleke, Chinedu Ezeigweneme, Samuel Olaoluwa Folorunsho, Daniel Ajiga
article en
25 citations

Abstract

Artificial Intelligence (AI) is revolutionizing software development practices in high-tech companies, providing transformative insights and tools that enhance productivity, quality, and efficiency. This review explores the integration of AI into software development processes, highlighting its impact on key areas such as code generation, bug detection, project management, and testing. AI-driven tools are enabling developers to automate repetitive tasks, optimize code, and identify potential issues before they become critical, thus reducing development time and improving software reliability. Machine learning algorithms analyze vast amounts of data from past projects to provide predictive analytics, guiding teams in decision-making and resource allocation. Natural language processing (NLP) facilitates more intuitive interactions with development tools, streamlining communication and collaboration among team members. Furthermore, AI enhances continuous integration and continuous deployment (CI/CD) pipelines by automating the testing and deployment stages, ensuring that code changes are seamlessly integrated and deployed with minimal human intervention. By leveraging AI, high-tech companies can adopt more agile methodologies, respond swiftly to market changes, and deliver high-quality software products. The review also discusses the challenges of integrating AI into software development, including the need for substantial initial investment, the complexity of AI models, and the importance of ensuring data privacy and security. Solutions such as fostering a culture of continuous learning, investing in AI-specific training for developers, and establishing robust data governance frameworks are essential for overcoming these barriers. In conclusion, AI-driven insights and tools offer significant advantages for high-tech companies, enabling them to enhance their software development practices, achieve greater efficiency, and maintain a competitive edge in a rapidly evolving technological landscape. Embracing these advancements requires a strategic approach, including investment in AI technologies and training, to fully harness the potential of AI and drive innovation in software development. Keywords: AI, Software Development, High-Tech, Practices, Companies.

Computer Science & IT Research JournalVol. 5(8)
Seattle University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Software Engineering Techniques and Practices
19.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.