Generative Artificial Intelligence (AI) In Coding Market Size, Share, Opportunities, And Trends By Operation (Code Generation, Code Enhancement, Language Translation, Code Reviews), By Application (Data Science And Analytics, Game Development And Design, Web And Application Development, IoT And Smart Devices), By End–User (BFSI, Media And Entertainment, IT & Telecom, Healthcare And Life Sciences, Transport & Logistics, Retail & E-commerce, Others), And By Geography - Forecasts From 2023 To 2028

  • Published : Nov 2023
  • Report Code : KSI061616202
  • Pages : 144

The generative AI in coding market is anticipated to show steady growth during the forecast period.

Generative AI, also known as artificial intelligence, is an innovative technology that exhibits the capability to produce a diverse array of content, encompassing textual material, imagery, audio files, and even synthetic data points. This cutting-edge AI technology operates by initiating with a prompt, which can take the form of various inputs such as text, images, videos, musical notes, or intricate designs, effectively processed by the AI system. A multitude of sophisticated AI algorithms then generate fresh content in response to the given prompt. This content can span a broad spectrum, ranging from comprehensive essays and intricate problem-solving solutions to hyper-realistic fabrications derived from images or audio recordings of individuals. Moreover, the applications of generative AI extend to a wide range of practical tasks, including but not limited to the creation of culinary recipes, the systematic debugging of intricate code, and the automated generation of textual content. Nonetheless, it is imperative to note that this advancement in AI technology can give rise to ethical issues, especially about the production of plagiarized content, which poses a serious challenge in the digital landscape. Although generative AI generates text based on the underlying patterns and information derived from its training data, it does not possess the conscious ability to replicate or duplicate specific texts with the explicit intention of plagiarizing. However, a critical concern lies in the attribution predicament associated with generative AI. This technology can generate coherent segments of text that might be only partially original, thus posing a significant conundrum regarding the ownership and originality of the generated content. Organizations relying on the utilization of generative AI models must confront the inherent risks, both in terms of reputation and legal implications. The content produced by these AI models can inadvertently perpetuate biases and can be manipulated to facilitate unethical or even criminal activities, thereby underscoring the importance of implementing comprehensive safeguards and ethical guidelines within the development and deployment of generative AI models.


The generative AI market is expanding rapidly, fueled by the increasing adoption of artificial intelligence-integrated systems across various industrial verticals. Additionally, the growing demand for creating and enhancing virtual worlds within the metaverse is also contributing significantly to the market's expansion. The need to update the workforce with advanced AI capabilities further underpins this growth trajectory. This surge in the market is expected to continue in the forthcoming years, promising substantial growth and development opportunities. Notably, the utilization of generative AI technologies in marketing departments signifies a transformative shift in the sector, rather than a passing trend, indicating a fundamental shift in how marketing strategies are formulated and implemented. With an emphasis on digital marketing, automated content creation, data analysis, customer interaction, and personalized marketing, the marketing and advertising sector is experiencing the highest Compound Annual Growth Rate (CAGR) during the projected period. This underscores the pivotal role played by generative AI in revolutionizing marketing practices and fostering unparalleled customer engagement and brand resonance. Moreover, the segmentation of the generative AI market based on components, technology, end-users, and regions highlights the diverse applications and potential for widespread integration across various sectors. Notably, key industry players such as Synthesia, MOSTLY AI Inc., Genie AI Ltd., Amazon Web Services, Inc., IBM, Google LLC, Microsoft, Adobe,, and D-ID are actively contributing to the expansion and evolution of the generative AI market, leveraging cutting-edge technologies and innovative solutions. The upward trajectory of the generative AI market is primarily driven by the increasing deployment of novel technologies across industries and the growing emphasis on streamlining and modernizing workflow processes. This demand for innovative solutions is reshaping the business landscape, fostering efficiency, and driving operational excellence across diverse sectors. As a result, the generative AI market is poised for substantial growth, serving as a cornerstone for the continued evolution and transformation of various industries.


  • Demand for AI-generated content: The increasing demand for AI-created content has boosted the growth of the generative AI market. This efficiency is particularly valuable in industries such as marketing and advertising, where tailoring and diversifying content is essential for effectively connecting with consumers.
  • Software development: Generative AI in software development leverages large datasets of existing code to learn patterns and structures using machine learning algorithms. This knowledge enables AI models to generate new code or provide recommendations and suggestions to developers. It has implications for a wide range of industries, from IT and software organizations that can benefit from the rapid generation of mostly accurate code to organizations in need of marketing copy.
  • Transformative influence on several industries: AI remains a transformative force in many industries, with fraud detection and process automation among its most widely adopted applications. However, Generative AI is now taking the spotlight, thanks to advances in natural language processing and the development of large language models.
  • User-friendly tools: Generative AI is evolving beyond text generation to encompass the creation of image, audio, and video content. User-friendly tools powered by generative AI allow users to produce high-quality content quickly and easily for various communication channels. As text generation models continue to advance, they will generate even higher-quality content.
  • IT & Telecom segment: Generative AI has a significant impact on the IT and Telecom industries, enabling transformative applications that enhance efficiency, automation, and problem-solving. In IT, generative AI is used for code generation and optimization, automatically generating code snippets, templates, and even entire modules, which speeds up software development and reduces manual coding.

Products offered by key companies:

  • The NVIDIA Triton Inference Server is an open-source software platform that makes it easy to deploy and manage AI models at scale. It supports a variety of generative AI models, including text generation, image generation, and code generation models.
  • Google offers Vertex AI a managed machine learning platform that makes it easy to build, deploy, and manage machine learning models. It supports a variety of generative AI models, including text generation, image generation, and code generation models

Prominent growth in the code generation segment within the generative AI in the coding market:

The code generation segment is a prominent growth area within the generative AI in the coding market. As technology continues to evolve, the demand for automated code-generation tools has seen a significant upsurge. Notably, the code generation segment holds the largest revenue share of the generative AI in the software development market, showcasing its pivotal role in driving efficiency and productivity in the coding landscape. In code generation, generative AI exhibits its prowess by automatically generating pieces of code or even completing entire programs based on specific user-defined specifications. This capability serves as a time-saving boon for developers, efficiently streamlining their workflow by automating repetitive tasks and providing initial code structures that serve as a solid foundation for further development. By reducing the manual labor involved in the initial stages of coding, generative AI allows developers to allocate more time and resources toward higher-level problem-solving and innovation. Furthermore, the integration of generative AI in coding offers intelligent recommendations, insightful suggestions, and comprehensive code analysis, enabling developers to write high-quality code with enhanced software performance. Through its sophisticated algorithms and machine learning capabilities, generative AI assists developers in identifying potential errors, optimizing code syntax, and adhering to best practices, ultimately contributing to the development of robust, reliable software solutions. The dynamic landscape of generative AI in the coding market continues to introduce innovative solutions that revolutionize and augment various aspects of the coding process. From facilitating code completion and refactoring to enabling efficient bug detection and resolution, generative AI technology catalyzes increased efficiency, accelerated development cycles, and heightened accuracy in software development. As the market for generative AI in coding continues to expand, its transformative impact on the software development ecosystem is poised to shape the future of coding practices and redefine the boundaries of technological innovation.

The Asia Pacific region is expected to hold a significant share of the generative AI in the coding market:

The Asia Pacific region is expected to hold a significant share of the generative AI in the coding market due to several key factors. Firstly, the region's strong emphasis on innovation and digital transformation has fostered an environment conducive to the widespread adoption of cutting-edge technologies such as generative AI. This emphasis on technological advancement has led to the integration of generative AI in coding across a wide array of industries, including but not limited to e-commerce, fintech, healthcare, and gaming. In these sectors, companies recognize the strategic importance of leveraging generative AI to stay competitive amidst the dynamic and ever-evolving market landscape. Moreover, major tech giants like Google are actively exploring and investing in new markets within the Asia-Pacific region, with a particular focus on advancing the use of generative artificial intelligence technology. Such initiatives not only highlight the growing significance of the region but also contribute to the acceleration of technological advancements in the field of generative AI in coding. On a global scale, the generative AI in the coding market represents the convergence of artificial intelligence (AI) and software development, where sophisticated AI models are harnessed to assist developers in various coding tasks, thereby streamlining and enhancing the efficiency of the software development process. Ultimately, the Asia Pacific region's anticipated substantial presence in the generative AI in the coding market can be attributed to its forward-thinking approach to innovation, its technological prowess, and the widespread incorporation of generative AI in diverse industries.

Market developments:

  • In July 2023, Persistent Systems, a global leader in digital engineering, partnered with Google Cloud, a subsidiary of Alphabet Inc., to launch a suite of generative AI solutions. These solutions help enterprises of all sizes to implement advanced AI technologies at scale, reduce time to market, and cut costs.
  • In March 2023, NVIDIA and Microsoft partnered to bring industrial metaverse and AI supercomputing to millions of enterprise users via the Azure cloud.


  • By Operation
    • Code Generation
    • Code Enhancement
    • Language Translation
    • Code Reviews
  • By Application
    • Data Science and Analytics
    • Game Development and Design
    • Web and Application Development
    • IoT and Smart Devices
  • By End–User
    • BFSI
    • Media and Entertainment
    • IT & Telecom
    • Healthcare and Life Sciences
    • Transport & logistics
    • Retail & E-commerce
    • Others
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • United Kingdom
      • Germany
      • France
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Israel
      • Others
    • Asia Pacific
      • Japan
      • China
      • India
      • South Korea
      • Indonesia
      • Thailand
      • Others


1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base, and Forecast Years Timeline


2.1. Research Data

2.2. Research Processes


3.1. Research Highlights


4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Force Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis


5.1. Introduction

5.2. Code Generation

5.3. Code Enhancement

5.4. Language Translation

5.5. Code Reviews


6.1. Introduction

6.2. Data Science and Analytics

6.3. Game Development and Design

6.4. Web and Application Development

6.5. IoT and Smart Devices


7.1. Introduction

7.2. BFSI

7.3. Media and Entertainment

7.4. IT & Telecom

7.5. Healthcare and Life Sciences

7.6. Transport & logistics

7.7. Retail & E-commerce

7.8. Others


8.1. Introduction

8.2. North America

8.2.1. United States

8.2.2. Canada

8.2.3. Mexico

8.3. South America

8.3.1. Brazil

8.3.2. Argentina

8.3.3. Others

8.4. Europe

8.4.1. United Kingdom

8.4.2. Germany

8.4.3. France

8.4.4. Spain

8.4.5. Others

8.5. The Middle East and Africa

8.5.1. Saudi Arabia

8.5.2. UAE

8.5.3. Israel

8.5.4. Others

8.6. Asia Pacific

8.6.1. Japan

8.6.2. China

8.6.3. India

8.6.4. South Korea

8.6.5. Indonesia

8.6.6. Thailand

8.6.7. Others


9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisitions, Agreements, and Collaborations


10.1. Codecademy

10.2. CodiumAI

10.3. Google LLC

10.4. IBM Corporation

10.5. Microsoft Corporation

10.6. NVIDIA Corporation

10.7. OpenAI

10.8. Tabnine



Google LLC

IBM Corporation

Microsoft Corporation

NVIDIA Corporation



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