The Generative Artificial Intelligence (AI) in Coding Market is expected to grow at a CAGR of 26.31%, reaching a market size of US$144.280 million in 2030 from US$44.880 million in 2025.
The rise of generative AI in coding is a result of software development processes incorporating machine learning (ML) and artificial intelligence (AI) techniques. With the aid of this technology, developers can streamline the coding process by automating and improving various aspects of it. Because of this advancement, traditional coding tasks require less manual labour, which results in quicker development cycles and increased productivity. Generative AI is necessary to handle complex coding in software applications for machine learning, deep learning, and data analysis.

Generative AI is increasingly being incorporated into Integrated Development Environments (IDEs) to improve the coding environment and increase developer productivity by offering AI-generated code suggestions and solutions within the coding workspace. This progression represents the coming together of AI powers and traditional coding techniques, leading to a more productive and cooperative development process. Microsoft's Visual Studio IntelliCode is an example of an AI-powered extension that can improve developers' coding experience with the Visual Studio IDE. By using AI technology, such innovations can enhance and expedite software development.
Further, more researchers are exploring the potential of AI to assist in the automation of various programming tasks, including code generation, providing solutions for coding problems, and enhancing programming efficiency. By incorporating machine learning and artificial intelligence, coding research is expected to build advanced instruments that may aid developers' productivity and streamline effective software creation processes. As this field transforms, it holds promise for the complete revolutionization of how programming codes are developed, tested, and optimized.
The swelling need for content generated by artificial intelligence has propelled the generative AI market growth. This is of great significance, especially in sectors such as marketing and advertising, where diversity and customization are fundamental to making it work with consumers. In software development, generative AI employs large datasets of pre-existing code that the ML algorithms then analyze for patterns and structure. With this knowledge, an AI model can either create brand-new code or make suggestions to the developers. It covers numerous fields, from IT and software companies that need quick production of almost precise codes to agencies requiring marketing copies.
The significant increase in developer productivity due to the incorporation of generative AI in coding is one of the main reasons this market is growing rapidly. By automating repetitive programming tasks, suggesting code snippets, and providing intelligent code completions, these AI tools let developers focus on more complex and creative aspects of software development. For example, GitHub’s Copilot supports programmers by automatically completing their code and suggesting relevant operations in real-time. In addition, such automation leads to significant cost savings in the development process. Furthermore, this efficiency accelerates the entire software development process and allows companies to scale up their solutions much quicker, owing to the demand for quick digital transformation in several industries.
Generative AI greatly improves code quality and consistency beyond just increasing efficiency. In the early stages of development, developers can identify and rectify potential bugs, vulnerabilities, and performance issues by using AI-driven code analysis tools. DeepCode is an example of a program that utilizes machine learning to sift through code patterns to provide advice on improving the readability and reliability of the code. This software will have fewer defects by anticipating coding standards, making it easier to maintain and more scalable.
Security and privacy concerns are the main reasons for the limited growth of generative artificial intelligence in programming markets. This raises questions about data confidentiality and intellectual property rights since there is a chance that some private or sensitive information may be accidentally acquired or reproduced while training AI algorithms on large codebases. Furthermore, hackers may sometimes exploit security holes created by them.
For instance, around 30% of AI-driven tools designed to make suggestions about the code might contain security holes. These vulnerabilities compromise trust in these software applications, reducing their efficacy as an effective means of making use of automated coding techniques. Nevertheless, businesses and developers remain cautious whenever they have to use these tools since digital asset safety becomes their main concern.
The surge is a result of many important things, such as a lively environment of start-ups and technological growth, huge financial resources allocated to AI research and development, and a strong innovation climate. With these exclusive market dynamics in this region, generative AI instruments are being embraced to raise output levels and make programming more efficient.
Further, the market presence of North America has significant future implications. The region is expected to set global standards for AI in coding and influence software development practices globally as it continues to advance AI. North America's sustained innovation and growth will probably draw in more capital, enhancing its dominant position in the market.
| Report Metric | Details |
|---|---|
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 β 2031 |
| Report Metric | Details |
| Generative AI in Coding Market Size in 2025 | US$44.880 million |
| Generative AI in Coding Market Size in 2030 | US$144.280 million |
| Growth Rate | CAGR of 26.31% |
| Study Period | 2020 to 2030 |
| Historical Data | 2020 to 2023 |
| Base Year | 2025 |
| Forecast Period | 2025 – 2030 |
| Forecast Unit (Value) | USD Million |
| Segmentation |
|
| Geographical Segmentation | North America, South America, Europe, Middle East and Africa, Asia Pacific |
| List of Major Companies in Generative AI in Coding Market |
|
| Customization Scope | Free report customization with purchase |
The Generative Artificial Intelligence (AI) in coding market is analyzed into the following segments:
Page last updated on: September 19, 2025