The Global Generative AI In Coding Market size is expected to reach $95.5 million by 2030, rising at a market growth of 23.5% CAGR during the forecast period.
Generative AI models have been used to automate the creation of various forms of media content, including articles, scripts, music, and even visual art. For example, AI-driven tools can generate news articles, create plot outlines for movies or TV shows, and even compose music. Consequently, the media and entertainment segment would generate approximately 23.1% share of the market by 2030. AI-powered tools are used for video and audio editing, making the process faster and more efficient. Generative AI can assist in tasks such as video captioning, audio transcription, and automatic subtitle generation, improving accessibility and user experience. Therefore, the media and entertainment segment demand are expected to grow rapidly in the coming years.
The major strategies followed by the market participants are Partnerships, Collaborations & Agreements as the key developmental strategy to keep pace with the changing demands of end users. For instance, In August, 2023, IBM Corporation expanded its collaboration with Microsoft Corporation, an American multinational technology corporation. Through this collaboration, the IBM Consulting Azure OpenAI Service was unveiled. In July, 2023, NVIDIA Corporation collaborated with ServiceNow, a software company that provides a cloud-based platform, and Accenture, an Irish-American professional services company. Through this collaboration, the AI Lighthouse was launched.
Based on the Analysis presented in the KBV Cardinal matrix; Google, Inc. and Microsoft Corporation are the forerunners in the market. In March 2023, Google LLC formed a partnership with Replit, Inc., an online integrated development environment. Through this partnership, the developers of Replit got to access Google Cloud infrastructure, services, and foundation models through. and Companies such as IBM Corporation, NVIDIA Corporation, Adobe, Inc. are some of the key innovators in the Market.
Automation of repetitive coding tasks significantly improves efficiency in software development. Automation diminishes the risk of human errors in coding. Generative AI tools can generate code that adheres to best practices and coding standards, reducing the likelihood of bugs and vulnerabilities. Fewer errors lead to more reliable and secure software. The AI can identify code issues, suggest improvements, and perform code analysis more rapidly and consistently than manual reviews. Furthermore, automation reduces the need for extensive manual coding and testing, resulting in organization cost savings. Fewer resources are required to achieve the same or even higher productivity and code quality levels. These factors are expected to boost the demand for market in the upcoming years.
Generative AI coding tools can assist less experienced developers by providing code suggestions, auto-completion, and real-time feedback, reducing the learning curve and allowing developers to become more productive. These tools can automatically generate code snippets or complete code sections based on high-level descriptions or requirements. This feature benefits less experienced developers who may need help writing complex or error-prone code from scratch. This helps less experienced developers learn from their mistakes and improve their coding practices. These tools often support multiple programming languages and frameworks, allowing less experienced developers to work in the languages they are most comfortable with or that are most in demand. As a result, these factors pose a lucrative prospect for the market.
In specialized industries or niche domains, a limited amount of relevant training data may be available. For example, in medical coding or aerospace engineering, the volume of publicly accessible code samples or datasets can be significantly smaller than in general programming domains like web development. This scarcity of data poses a fundamental challenge, as generative AI models require substantial data to learn effectively. Furthermore, creating high-quality training data often involves manual annotation and labeling, which can be labor-intensive and costly, especially for specialized coding tasks. This increases the overall cost and time required to develop generative AI models. These factors are expected to limit the growth of the market in the future.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships, Collaborations & Agreements.
Based on operation, the market is divided into code generation, code enhancement, language translation, and code reviews. The code generation segment procured the largest revenue share in the market in 2022. As software development continues to be a critical aspect of various industries, there is a growing demand for automation in coding. Generative AI, with its ability to automatically generate code snippets and even entire programs, addresses this demand by speeding up development processes and reducing the need for manual coding. In addition, the technology industry needs more skilled developers, and this gap is expected to widen.
By application, the market is segmented into data science & analytics, game development & design, web & application development, and IoT & smart devices. In 2022, the web and application development segment acquired a considerable revenue share in the market. Web and application development projects often have tight deadlines. Generative AI coding tools help accelerate development by automating repetitive tasks like generating code templates, layouts, and UI components. This speed is crucial in meeting market demands for timely product releases.
On the basis of vertical, the market is divided into BFSI, media & entertainment, IT & telecom, healthcare & life sciences, transport & logistics, and retail & e-commerce. The IT and telecom segment witnessed the maximum revenue share in the market in 2022. In the IT and telecom industry, there is a growing demand for automating network operations, including the configuration of network devices, troubleshooting, and optimization. Generative AI coding tools can help automate repetitive tasks by generating code scripts for network management, which saves time and reduces human errors.
| Report Attribute | Details |
|---|---|
| Market size value in 2022 | USD 18.4 Million |
| Market size forecast in 2030 | USD 95.5 Million |
| Base Year | 2022 |
| Historical Period | 2019 to 2021 |
| Forecast Period | 2023 to 2030 |
| Revenue Growth Rate | CAGR of 23.5% from 2023 to 2030 |
| Number of Pages | 295 |
| Number of Table | 403 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Market Share Analysis, Companies Strategic Developments, Company Profiling |
| Segments covered | Operation, Application, Vertical, Region |
| Country scope | US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria |
| Growth Drivers |
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| Restraints |
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Based on region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. In 2022, the Asia Pacific segment garnered a considerable revenue share in the market. Cities like Beijing, Shanghai, Bangalore, Singapore, and Tokyo have emerged as tech hubs and innovation centers in the APAC region. These hubs are home to numerous startups, research institutions, and tech companies actively involved in developing and applying generative AI in coding. APAC countries, particularly India and China, have many highly skilled software developers and engineers. This skilled workforce is a source of demand for generative AI coding solutions and a talent pool for developing these technologies. All these factors will boost the demand in the Asia Pacific segment in the upcoming years.
Free Valuable Insights: Global Generative AI In Coding Market size to reach USD 95.5 Million by 2030
The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include Skillsoft Corporation, CodiumAI, Snyk Limited, Google LLC, IBM Corporation, Microsoft Corporation, NVIDIA Corporation, OpenAI, L.L.C., Tabnine, Adobe, Inc.
By Operation
By Application
By Vertical
By Geography
This Market size is expected to reach $95.5 million by 2030.
Increasing demand for automation in various sectors are driving the Market in coming years, however, Concerns associated with data quality and quantity restraints the growth of the Market.
Skillsoft Corporation, CodiumAI, Snyk Limited, Google LLC, IBM Corporation, Microsoft Corporation, NVIDIA Corporation, OpenAI, L.L.C., Tabnine, Adobe, Inc.
The expected CAGR of this Market is 23.5% from 2023 to 2030.
The Data Science & Analytics segment is leading the Market by Application in 2022; thereby, achieving a market value of $32.4 million by 2030.
The North America region dominated the Market by Region in 2022, and would continue to be a dominant market till 2030; thereby, achieving a market value of $32.3 million by 2030.
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