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Generative AI in Software and Coding Market By Function (Code Generation, Code Enhancement, Code Review, and Language Translation), By End User - Global Industry Outlook, Key Companies (Open AI, IBM Corp, Google LLC, and others), Trends and Forecast 2024-2033

Published on : October-2024  Report Code : RC-1163  Pages Count : 314  Report Format : PDF
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Market Overview

The Global Generative AI in Software and Coding Market is projected to reach USD 31.6 million in 2024 and grow at a compound annual growth rate of 25.5% from there until 2033 to reach a value of USD 243.7 million.
 
The Generative AI in Software and Coding market includes the utilization of AI technologies that can automatically generate code, software components, and even entire applications, which transforms how software is developed by automating repetitive tasks, optimizing code, and creating new solutions with minimal human intervention.

Global Generative AI in Software and Coding Market Growth Analysis
 
Generative AI in Software and Coding Market is rapidly revolutionizing software development. New AI advances have allowed for automation of coding tasks, code generation and bug detection - vastly increasing developer productivity with tools powered by AI aiding from writing code through testing to debugging; ultimately streamlining development.

An increasing trend in the market is the integration of Generative AI tools such as OpenAI's Codex and GitHub Copilot into development environments, providing assistance by suggesting code snippets, completing functions, or even developing entire applications without manual coding being necessary - thus improving workflow efficiencies for developers and streamlining workflow processes. Such innovations are redefining developer roles while streamlining workflow processes more efficiently.

AI-driven software solutions continue to experience steady market growth as organizations seek faster development cycles and superior code quality. Businesses are rapidly adopting generative AI for both enterprise-grade software projects as well as smaller ones; businesses recognize its ability to both increase development efficiency and foster innovation in coding processes. This has driven uptake, driving market expansion by an astounding 30% year over year increase since 2015.

Opportunities in the Generative AI in Software and Coding Market are vast. Start-ups as well as established players are exploring AI's potential to automate tasks that were traditionally performed by developers. Thanks to advances in natural language processing (NLP) and machine learning technologies, new AI-powered coding platforms are emerging to meet specific industry requirements.

As per salesforce Salesforce research shows that workers are divided on generative AI. Although 61% use or plan to use it, many have expressed worries over navigating its risks and developing necessary skills. Sixty-eight percent believe it will enhance customer service while another 67% say it will strengthen other tech investments - yet many workers worry about inaccuracies, bias, and security risks when using it.

Generative AI offers immense potential, and 86% of IT leaders anticipate its deployment as an essential element within their organizations. However, challenges still exist: 65% of IT decision-makers feel they cannot justify implementing it due to security concerns, skilled employee shortages or integration issues with existing tech stacks; furthermore many lack an organized data strategy.

Employees believe key components for effective implementation of generative AI include human oversight (60%), enhanced security (59%), trusted customer data (58%), and ethical use guidelines (58%). While enthusiasm for this technology may be high, IT leaders face barriers such as potential security threats (71%), and needing additional skills (66%). Before full deployment can happen.

The US Generative AI in Software and Coding Market

The US Generative AI in Software and Coding Market is projected to reach USD 9.3 million in 2024 at a compound annual growth rate of 23.9% over its forecast period.

The US  Generative AI in Software and Coding Market Growth Analysis

The U.S. has many growth opportunities in generative AI for software and coding, driven by its strong and advanced tech ecosystem, higher R&D capabilities, and large investment in AI technologies. The need for AI-driven automation in software development, along with a skilled workforce and a culture of innovation, positions the U.S. as a leader in advancing and scaling AI-driven coding solutions.

Further, the growth in generative AI for software and coding in the US is driven by its strong tech ecosystem, significant R&D investments, and a highly skilled workforce that fosters innovation. However, challenges like high implementation costs and concerns over data privacy and security, which can hinder the widespread adoption & integration of AI technologies in development processes.

Key Takeaways

  • Market Growth: The Generative AI in Software and Coding Market size is expected to grow by 204.9 million, at a CAGR of 25.5% during the forecasted period of 2025 to 2033.
  • By Function: The Code Generation is expected to lead in 2024 with a major & is anticipated to dominate throughout the forecasted period.
  • By End User: IT & Telecom sector is expected to get the largest revenue share in 2024 in the Generative AI in Software and Coding Market.
  • Regional Insight: North America is expected to hold a 33.5% share of revenue in the Global Generative AI in Software and Coding Market in 2024.
  • Use Cases: Some of the use cases of Generative AI in Software and Coding include electric vehicles, marine propulsion, and more.

Use Cases

  • Automated Code Generation: Simplifies writing code by automatically generating syntactically correct and logically accurate code, minimizing development time.
  • Language Translation: Converts code between programming languages, simplifying updates & maintenance, mainly for legacy systems.
  • Code Reviews: Provides AI-driven analysis & feedback on code quality, ensuring adherence to coding standards and best practices.
  • Bug Detection and Fixing: Identifies & automatically corrects errors in code, improving software reliability & reducing debugging time.

Market Dynamic

Driving Factors

Efficiency and Innovation
The demand for faster software development & innovation drives the adoption of generative AI, as it automates routine coding tasks, and enables developers to look into complex problem-solving and creative aspects.

AI Integration in Development Tools
The growing integration of AI in Integrated Development Environments (IDEs) improves the accessibility and usability of generative AI tools, making them essential for enhancing productivity and code quality in software development.

Restraints

Data Privacy and Security Concerns
The usage of generative AI in software development creates concerns about data privacy & security, mainly when AI models require access to sensitive codebases and development environments.

High Implementation Costs
The initial costs of implementing generative AI tools, like the need for specialized hardware, software, and skilled personnel, can be a barrier for smaller companies and startups.

Opportunities

Customization and Personalization
Generative AI provides the opportunity to develop highly customized software solutions customized to specific business needs, allowing companies to differentiate their products and services in competitive markets.

Scalability in Development
As generative AI tools improve, they deliver the potential to scale software development processes, enabling organizations to handle larger and more complex projects with increased efficiency and reduced time-to-market.

Trends

AI-Powered Code Assistants
The growth of AI-powered code assistants within development environments is becoming a trend, providing real-time suggestions, error detection, and code optimization, making the development process faster and more efficient.

Collaborative AI Tools
There’s an increase in the trend of collaborative AI tools that supports teamwork among developers by automating code reviews, merging requests, and ensuring consistent coding standards across large teams and projects.

Research Scope and Analysis

By Function

In the generative AI market for software and coding, Code Generation is expected to come out as a leading function due to its critical role of automating code writing, which significantly minimizes the time developers spend on routine tasks. By using AI to handle the more repetitive aspects of coding, developers can dedicate their efforts to complex and innovative parts of software development, which not only leads to more efficient project completions but also drives greater innovation. 

Code Generation tools use advanced AI algorithms to get the project requirements and produce syntactically correct, logically sound code. These tools are highly integrated into development environments (IDEs), making them more accessible and user-friendly for developers. 

As these tools learn from large codebases, they constantly improve, providing better output and reliability over time.

Further, language translation tools also play a major role by converting code from one programming language to another, simplifying updates and maintenance, mainly in legacy systems. 

In addition, AI-powered Code Reviews provide automated analysis & feedback on code quality, making developers adhere to coding standards and best practices.

By End User

The IT & Telecom sector is set to dominate in adopting generative AI for software and coding in 2024 as the industry needs constant innovation and efficiency in the face of rapid technological changes & intense competition. Generative AI allows companies in this sector to quickly develop new applications & services, helping them stay competitive & meet the ever-changing demands of their customers. 

Global Generative AI in Software and Coding Market End User Analysis

By automating routine coding tasks & managing more complex functions like system maintenance and technology integration, generative AI effectively enhances operational efficiency. AI-driven code generation tools reduce human error, accelerate development timelines, and enable faster product launches. Further, in the Retail & E-commerce industries, AI is highly used to improve user experience through better personalization and more effective recommendation engines within software systems. 

In addition, the ‘Others’ category, which contains various emerging and niche sectors, shows a higher interest in AI applications. These industries are exploring AI as a way to differentiate themselves and optimize their operations, recognizing the potential for AI to provide a competitive edge and improve performance in their specific fields.

The Generative AI in Software and Coding Market Report is segmented on the basis of the following

By Function

  • Code Generation
  • Code Enhancement
  • Code Review
  • Language Translation

By End User

  • IT & Telecom
  • BFSI
  • Healthcare & Life Science
  • Media & Entertainment
  • Retail & E-commerce
  • Others

Regional Analysis

North America is expected to have a dominant 33.5% share in the generative AI market for software and coding in 2024, due to its strong tech ecosystem and significant AI funding. The region’s dominance is driven by the presence of major tech companies & innovative startups, which constantly push the boundaries of AI development. High adoption rates of advanced technologies, along with a strong aim for R&D, play a major role in shaping the regions' market dynamics. 

Global Generative AI in Software and Coding Market Regional Analysis

In addition, the region’s skilled workforce & culture of innovation make it an ideal environment for the growth of AI technologies in software development. Moreover, it is expected to maintain its leadership position, with ongoing investments and collaborations among tech firms further improving capabilities and driving sustained growth.

Further, in Europe, the focus is on AI ethics and data privacy, areas where the region has established rigorous standards. Major investments in AI are set to support Europe’s technological infrastructure, expanding its influence in generative AI applications. 

Meanwhile, Asia Pacific is experiencing rapid growth, driven by a tech-savvy population and a booming tech sector. The region is emerging as a key player in the innovation and application of generative AI technologies, contributing significantly to global advancements in this field.

By Region

North America
  • The U.S.
  • Canada
Europe
  • Germany
  • The U.K.
  • France
  • Italy
  • Russia
  • Spain
  • Benelux
  • Nordic
  • Rest of Europe
Asia-Pacific
  • China
  • Japan
  • South Korea
  • India
  • ANZ
  • ASEAN
  • Rest of Asia-Pacific
Latin America
  • Brazil
  • Mexico
  • Argentina
  • Colombia
  • Rest of Latin America
Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Israel
  • Egypt
  • Rest of MEA

Competitive Landscape

The competitive landscape of the generative AI market for software and coding experiencing a dynamic mix of established tech giants & innovative startups. Key players focus on developing advanced AI models and tools that automate coding tasks and improve software development efficiency. Companies are actively investing in R&D, leading to constant advancements and new features. 

Further, collaborations between tech firms and research institutions also drive innovation. The competition is strong, with a high emphasis on improving AI capabilities, usability, and integration into development environments.

Some of the prominent players in the Global Generative AI in Software and Coding are
  • Open AI
  • IBM Corp
  • Google LLC
  • Microsoft Corp
  • NVIDIA Corp
  • Codeacademy
  • Codota
  • Tabnine
  • CodiumAI
  • DeepCode
  • Other Key Players

Recent Developments

  • In July 2024, CodiumAI, the generative code integrity platform, launched its enterprise platform which allows development teams to use generative AI to enhance code quality. Through organization-specific code suggestions, tests, and reviews, Codium's enterprise platform allows enterprises to confidently adopt AI-generated code.
  • In July 2024, AWS launched Amazon Q Apps, a feature of its generative AI coding tool that enables workers to develop applications using natural language prompts, as the users use the tool to create applications that generate onboarding plans, draft memos, and summarize feedback.
  • In May 2024, Hitachi, Ltd. plans the implementation of the Hitachi Group's Generative AI Common Platform with a focus on reforming the work styles and enhancing the productivity of software engineers and front-line workers, who are facing human resource shortages in various industries. As part of the Generative AI Common Platform, a new development framework has been developed to apply generative AI to the development domain of mission-critical systems.
  • In February 2024, Cognizant introduced a generative AI (gen AI)-enabled platform, Cognizant Flowsource that looks to fuel the next generation of software engineering for enterprises. Cognizant Flowsource integrates all stages of the software development lifecycle & incorporates digital assets and tools to assist cross-functional engineering teams deliver high-quality code faster, with better control and transparency.
  • In November 2023, SAP launched a set of new generative artificial intelligence (AI) tools & extensions for its enterprise resource planning (ERP) software package, SAP Business Technology Platform, which operates in integration with the Joule generative AI copilot to make it possible to write code for application logic, data models, and test scripts using natural language.

Report Details

Report Characteristics
Market Size (2024) USD 31.6 Mn
Forecast Value (2033) USD 243.7 Mn
CAGR (2024-2033) 25.5%
Historical Data 2018 – 2023
The US Market Size (2024) USD 9.3 Mn
Forecast Data 2025 – 2033
Base Year 2023
Estimate Year 2024
Report Coverage Market Revenue Estimation, Market Dynamics, Competitive Landscape, Growth Factors and etc.
Segments Covered By Function (Code Generation, Code Enhancement, Code Review, and Language Translation), By End User (IT & Telecom, BFSI, Healthcare & Life Science, Media & Entertainment, Retail & E-commerce, and Others)
Regional Coverage North America – The US and Canada; Europe – Germany, The UK, France, Russia, Spain, Italy, Benelux, Nordic, & Rest of Europe; Asia- Pacific– China, Japan, South Korea, India, ANZ, ASEAN, Rest of APAC; Latin America – Brazil, Mexico, Argentina, Colombia, Rest of Latin America; Middle East & Africa – Saudi Arabia, UAE, South Africa, Turkey, Egypt, Israel, & Rest of MEA
Prominent Players Open AI, IBM Corp, Google LLC, Microsoft Corp, NVIDIA Corp, Codeacademy, Codota, Tabnine, CodiumAI, DeepCode, and Other Key Players
Purchase Options We have three licenses to opt for: Single User License (Limited to 1 user), Multi-User License (Up to 5 Users) and Corporate Use License (Unlimited User) along with free report customization equivalent to 0 analyst working days, 3 analysts working days and 5 analysts working days respectively.

 

Frequently Asked Questions

  • How big is the Global Generative AI in Software and Coding Market?

    The Global Generative AI in Software and Coding Market size is expected to reach a value of USD 31.6 million in 2024 and is expected to reach USD 243.7 million by the end of 2033.

  • Which region accounted for the largest Global Generative AI in Software and Coding Market?

    North America is expected to have the largest market share in the Global Generative AI in Software and Coding Market with a share of about 33.5% in 2024.

  • How big is the Generative AI in Software and Coding Market in the US?

    The Generative AI in Software and Coding Market in the US is expected to reach USD 9.3 million in 2024.

  • Who are the key players in the Global Generative AI in Software and Coding Market?

    Some of the major key players in the Global Generative AI in Software and Coding Market are Open AI, IBM Corp, Google LLC, and others.

  • What is the growth rate in the Global Generative AI in Software and Coding Market?

    The market is growing at a CAGR of 25.5 percent over the forecasted period.

  • Contents

      1.Introduction
        1.1.Objectives of the Study
        1.2.Market Scope
        1.3.Market Definition and Scope
      2.Generative AI in Software and Coding Market Overview
        2.1.Global Generative AI in Software and Coding Market Overview by Type
        2.2.Global Generative AI in Software and Coding Market Overview by Application
      3.Generative AI in Software and Coding Market Dynamics, Opportunity, Regulations, and Trends Analysis
        3.1.Market Dynamics
          3.1.1.Generative AI in Software and Coding Market Drivers
          3.1.2.Generative AI in Software and Coding Market Opportunities
          3.1.3.Generative AI in Software and Coding Market Restraints
          3.1.4.Generative AI in Software and Coding Market Challenges
        3.2.Emerging Trend/Technology
        3.3.PESTLE Analysis
        3.4.PORTER'S Five Forces Analysis
        3.5.Technology Roadmap
        3.6.Opportunity Map Analysis
        3.7.Case Studies
        3.8.Opportunity Orbits
        3.9.Pricing Analysis
        3.10.Ecosystem Analysis
        3.11.Supply/Value Chain Analysis
        3.12.Covid-19 & Recession Impact Analysis
        3.13.Product/Brand Comparison
      4.Global Generative AI in Software and Coding Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Function, 2017-2032
        4.1.Global Generative AI in Software and Coding Market Analysis by By Function: Introduction
        4.2.Market Size and Forecast by Region
        4.3.Code Generation
        4.4.Code Enhancement
        4.5.Code Review
        4.6.Language Translation
      5.Global Generative AI in Software and Coding Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By End User, 2017-2032
        5.1.Global Generative AI in Software and Coding Market Analysis by By End User: Introduction
        5.2.Market Size and Forecast by Region
        5.3.IT & Telecom
        5.4.BFSI
        5.5.Healthcare & Life Science
        5.6.Media & Entertainment
        5.7.Retail & E-commerce
        5.8.Others
      10.Global Generative AI in Software and Coding Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by Region, 2017-2032
        10.1.North America
          10.1.1.North America Generative AI in Software and Coding Market: Regional Analysis, 2017-2032
            10.1.1.1.The US
            10.1.1.2.Canada
        10.2.1.Europe
          10.2.1.Europe Generative AI in Software and Coding Market: Regional Trend Analysis
            10.2.1.1.Germany
            10.2.1.2.France
            10.2.1.3.UK
            10.2.1.4.Russia
            10.2.1.5.Italy
            10.2.1.6.Spain
            10.2.1.7.Nordic
            10.2.1.8.Benelux
            10.2.1.9.Rest of Europe
        10.3.Asia-Pacific
          10.3.1.Asia-Pacific Generative AI in Software and Coding Market: Regional Analysis, 2017-2032
            10.3.1.1.China
            10.3.1.2.Japan
            10.3.1.3.South Korea
            10.3.1.4.India
            10.3.1.5.ANZ
            10.3.1.6.ASEAN
            10.3.1.7.Rest of Asia-Pacifc
        10.4.Latin America
          10.4.1.Latin America Generative AI in Software and Coding Market: Regional Analysis, 2017-2032
            10.4.1.1.Brazil
            10.4.1.2.Mexico
            10.4.1.3.Argentina
            10.4.1.4.Colombia
            10.4.1.5.Rest of Latin America
        10.5.Middle East and Africa
          10.5.1.Middle East and Africa Generative AI in Software and Coding Market: Regional Analysis, 2017-2032
            10.5.1.1.Saudi Arabia
            10.5.1.2.UAE
            10.5.1.3.South Africa
            10.5.1.4.Israel
            10.5.1.5.Egypt
            10.5.1.6.Turkey
            10.5.1.7.Rest of MEA
      11.Global Generative AI in Software and Coding Market Company Evaluation Matrix, Competitive Landscape, Market Share Analysis, and Company Profiles
        11.1.Market Share Analysis
        11.2.Company Profiles
          11.3.1.Company Overview
          11.3.2.Financial Highlights
          11.3.3.Product Portfolio
          11.3.4.SWOT Analysis
          11.3.5.Key Strategies and Developments
        11.4.Open AI
          11.4.1.Company Overview
          11.4.2.Financial Highlights
          11.4.3.Product Portfolio
          11.4.4.SWOT Analysis
          11.4.5.Key Strategies and Developments
        11.5.IBM Corp
          11.5.1.Company Overview
          11.5.2.Financial Highlights
          11.5.3.Product Portfolio
          11.5.4.SWOT Analysis
          11.5.5.Key Strategies and Developments
        11.6.Google LLC
          11.6.1.Company Overview
          11.6.2.Financial Highlights
          11.6.3.Product Portfolio
          11.6.4.SWOT Analysis
          11.6.5.Key Strategies and Developments
        11.7.Microsoft Corp
          11.7.1.Company Overview
          11.7.2.Financial Highlights
          11.7.3.Product Portfolio
          11.7.4.SWOT Analysis
          11.7.5.Key Strategies and Developments
        11.8.NVIDIA Corp
          11.8.1.Company Overview
          11.8.2.Financial Highlights
          11.8.3.Product Portfolio
          11.8.4.SWOT Analysis
          11.8.5.Key Strategies and Developments
        11.9.Codeacademy
          11.9.1.Company Overview
          11.9.2.Financial Highlights
          11.9.3.Product Portfolio
          11.9.4.SWOT Analysis
          11.9.5.Key Strategies and Developments
        11.10.Codota
          11.10.1.Company Overview
          11.10.2.Financial Highlights
          11.10.3.Product Portfolio
          11.10.4.SWOT Analysis
          11.10.5.Key Strategies and Developments
        11.11.Tabnine
          11.11.1.Company Overview
          11.11.2.Financial Highlights
          11.11.3.Product Portfolio
          11.11.4.SWOT Analysis
          11.11.5.Key Strategies and Developments
        11.12.CodiumAI
          11.12.1.Company Overview
          11.12.2.Financial Highlights
          11.12.3.Product Portfolio
          11.12.4.SWOT Analysis
          11.12.5.Key Strategies and Developments
        11.13.DeepCode
          11.13.1.Company Overview
          11.13.2.Financial Highlights
          11.13.3.Product Portfolio
          11.13.4.SWOT Analysis
          11.13.5.Key Strategies and Developments
        11.14.Other Key Players
          11.14.1.Company Overview
          11.14.2.Financial Highlights
          11.14.3.Product Portfolio
          11.14.4.SWOT Analysis
          11.14.5.Key Strategies and Developments
      12.Assumptions and Acronyms
      13.Research Methodology
      14.Contact
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