AI Code Tools Market by Offering (Tools (Deployment Mode) and Services), Technology (ML, NLP, Generative AI), Application (Data Science & Machine Learning, Cloud Services & DevOps, Web Development), Vertical and Region - Global Forecast to 2028
The global market for AI Code Tools Market is projected to grow from USD 4.3 billion in 2023 to USD 12.6 billion by 2028, at a CAGR of 24.0% during the forecast period. The AI code tools market is fueled by several key factors, including rapid advancements in generative Al is revolutionizing software development. These tools are instrumental in enhancing efficiency and productivity for developers, as they address the challenges of handling intricate coding tasks. The need to assist developers in tackling complex coding tasks and enhance scalability and transformative shift in the roles of software developers propels the AI code tools market.
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Market Dynamics
Driver: Need to assist developers in tackling complex coding tasks
AI code tools provide invaluable assistance to software developers when facing complex coding tasks, and this has emerged as a compelling driver for their adoption in the software development landscape. One significant aspect of this assistance lies in the ability of AI coding tools to simplify code translation, particularly when dealing with legacy source code or multiple programming languages. A study at the 2021 International Conference on Intelligent User Interfaces highlighted how generative AI offered developers a skeletal framework to translate source code into Python. In a 2022 study published in the Proceedings of the Association for Computing Machinery on Programming Languages (PACMPL), it was observed that these tools, like GitHub Copilot, facilitated faster coding by offering end-of-line suggestions for function calls and argument completions.
Restraint: Overreliance on AI code tools to hinder the problem solving abilities
Overreliance on AI code tools represents a critical restraint in the software development landscape. While these AI-driven tools offer efficiency and productivity, they can inadvertently hinder developers' creative problem-solving capabilities and critical thinking. Developers are often drawn to AI code tools because of their convenience and the ability to expedite coding tasks. However, this convenience can lead to a situation where developers become overly dependent on AI-generated code suggestions. This overreliance may manifest in several ways, including developers bypassing manual coding, overlooking innovative problem-solving, and adopting a more passive role in the development process. Rather than proactively engaging with code challenges and devising unique solutions, developers may turn to AI tools as a one-stop solution. The consequence of such overreliance is a potential stifling of creative thinking and the development of skills that are crucial in software engineering.
Opportunity: Emergence of Prompt Engineering in software industry
The emergence of Prompt Engineering is a significant opportunity for the software development industry. This approach recognizes the importance of effective communication with AI systems, treating it as a form of meta-programming. Developers will need to convey their intentions to AI systems using well-structured prompts, ensuring that the AI co-developers generate code that aligns with their objectives. In the face of increasing App Development workloads and the need for improved productivity, Prompt Engineering and AI and Human Collaboration offer a solution to navigate the future of software development effectively, providing a more efficient, rewarding, and collaborative environment for developers while enhancing software quality and speed.
Challenge: Legal and ethical complexities in AI code tools
Legal and ethical complexities are inherent challenges in the use of AI code tools, primarily due to the rapidly evolving landscape of artificial intelligence and its interaction with established legal frameworks and ethical standards. These complexities encompass a range of issues, including intellectual property rights, liability, data privacy, and ethical considerations. One significant concern relates to intellectual property, particularly in the case of AI-generated code. Determining the ownership of code created by AI tools can be convoluted, as it involves questions about whether AI-generated code can be copyrighted, patented, or owned at all.
AI code tools Market Ecosystem
The AI code tools market ecosystem is a dynamic landscape consisting of various key components, each playing a distinct role in advancing the field of artificial intelligence and software development. These components include AI code tool providers, service providers, integrators, end users, and regulatory bodies.
By Vertical, BFSI segment accounts for the largest market size during the forecast period
Artificial Intelligence (AI) has transformed the BFSI sector by introducing a wide array of code tools designed to streamline operations, enhance customer experiences, and improve risk management. These AI code tools are helping banks, financial institutions, and insurance companies become more efficient, agile, and competitive in a rapidly evolving industry. One prominent application is the use of Natural Language Processing (NLP) and Machine Learning (ML) algorithms to automate document processing and analysis. By parsing large volumes of unstructured data from sources such as loan applications, financial statements, and customer queries, AI code tools can quickly extract key information, assess risk profiles, and make data-driven decisions.
Managed Services segment is projected to grow at the highest CAGR during the forecast period
Managed services offer a comprehensive approach to AI implementation, transforming the way organizations harness the power of artificial intelligence. These services, often provided by third-party experts, encompass end-to-end management of AI systems, from planning and development to ongoing operations and support. Managed services relieve organizations of the complexities associated with AI, allowing them to focus on their core competencies while benefiting from expert guidance. Managed service providers oversee tasks such as data preparation, model training, deployment, and continuous monitoring, ensuring the seamless and optimal functioning of AI solutions.
North America to account for the largest market size during the forecast period
The AI code tools market in North America stands as a global powerhouse, shaped by the innovation and technological prowess of both the United States and Canada. The United States has long maintained its position as a global leader in AI, driven by an innovation ecosystem that fosters collaboration between industry, academia, and government. With substantial investments, a concentration of top-tier AI researchers, and tech giants like IBM and Microsoft, the U.S. dominates AI startup funding deals and patents, reinforcing its readiness to implement AI in the public sector. Similarly, Canada boasts a thriving tech industry, marked by an emphasis on research and development, access to highly skilled talent, and strong tech ecosystems in major cities. The nation's commitment to STEM education and collaborative research has established it as a significant player in the global software market, with thriving AI hubs that attract global companies.
Key Market Players
The major AI code tools and service providers include IBM (US), Microsoft (US), Google (US), AWS (US), Salesforce (US), Meta (US), OpenAI (US), Tabnine (Israel), Replit (US), Sourcegraph (US), Moolya (India), Synk (US), CircleCI (US), JetBrains (Czech Republic), Adacore (France), WingWare (US), Datadog (US), Lightning AI (US), Kodezi (US), Sourcery (England), CodeWP (US), SQLAI.ai (Germany) , SinCode AB (Sweden), Seek AI (US), Enzyme (US), Assistive.ai (Germany), CodiumAI (Israel), Mutable AI (US), Judini (US) and Safurai (Italy). These companies have used both organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the AI code tools market.
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Report Metrics |
Details |
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Market size available for years |
2017–2028 |
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Base year considered |
2022 |
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Forecast period |
2023–2028 |
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Forecast units |
USD Billion |
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Segments covered |
Offering (Tools (Deployment Mode) and Services), Technology (ML, NLP, Generative AI), Application (Data Science & Machine Learning, Cloud Services & DevOps, Web Development), Vertical, and Region |
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Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
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Companies covered |
IBM (US), Microsoft (US), Google (US), AWS (US), Salesforce (US), Meta (US), OpenAI (US), Tabnine (Israel), Replit (US), Sourcegraph (US), Moolya (India), Synk (US), CircleCI (US), JetBrains (Czech Republic), Adacore (France), WingWare (US), Datadog (US), Lightning AI (US), Kodezi (US), Sourcery (England), CodeWP (US), SQLAI.ai (Germany) , SinCode AB (Sweden), Seek AI (US), Enzyme (US), Assistive.ai (Germany), CodiumAI (Israel), Mutable AI (US), Judini (US), Safurai (Italy) |
This research report categorizes the AI code tools market based on Offering, Application, Vertical, and Region.
By Offering:
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Tools
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Deployment Mode
- Cloud
- On Premises
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Deployment Mode
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Services
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Professional Services
- Consulting
- Training
- System Integration & Implementation
- Support & Maintenance
- Managed Services
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Professional Services
By Technology:
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Machine Learning
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Deep Learning
- Recurrent neural networks
- Long short-term memory (LSTM)
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Deep Learning
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Natural Language Processing
- Natural language understanding (NLU)
- Natural language interface for code
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Generative AI
- Large language models (LLMs)
- Code generation models
By Application:
- Data Science & Machine Learning
- Cloud Services & DevOps
- Web Development
- Mobile App Development
- Gaming Development
- Embedded Systems
- Other Applications
By Vertical:
- BFSI
- IT&ITeS
- Healthcare & Life Sciences
- Manufacturing
- Retail & eCommerce
- Telecommunications
- Government & Public Sector
- Media & Entertainment
- Others (Education, Automotive, and Energy & Utilities)
By Region:
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Recent Developments:
- In July 2023, Meta announced the release of Llama 2, the next iteration of its open-source large language model. This development is part of an expanded partnership between Microsoft and Meta, with Microsoft being designated as the preferred partner for Llama 2.
- In May 2023, IBM introduced WatsonX, a new AI and data platform enabling enterprises to scale and accelerate the impact of the most advanced AI with trusted data. WatsonX was designed to be a comprehensive platform with an AI development studio, a data store, and an AI governance toolkit.
- In March 2023, Replit, a prominent cloud software development platform, announced a partnership with Google Cloud. This partnership introduces the latest Large Language Model (LLM) chat applications capable of generating complete code for entire programs based on straightforward natural language prompts.
- In March 2023, Baidu unveiled ERNIE Bot, its latest innovation in generative AI, featuring a knowledge-enhanced LLM. This cutting-edge technology can understand human intentions and provide precise, coherent, and fluent responses that approach human-level comprehension and communication.
- In December 2022, DeepMind launched AlphaCode, a code generation system that can write computer programs at a competitive level. It was trained on a massive dataset of code and text and can generate code in a variety of programming languages, including Python, Java, C++, and C#.
- In March 2022, CircleCI announced the acquisition of Ponicode, a Paris-based AI engine specializing in source code analysis, aiming to assist developers in enhancing their code quality within their local development environments. Ponicode's unique emphasis on alleviating developers from their less favored tasks, particularly the repetitive aspects of code creation such as test writing, code commenting, and code quality analysis, captured CircleCI's interest and aligns with its mission to support developers in producing superior code.
Frequently Asked Questions (FAQ):
What are AI Code Tools?
AI code tools are software applications and platforms that leverage various AI technologies to assist software developers and programmers in various aspects of the software development lifecycle. These tools provide a wide range of functionalities, including code autocompletion, code generation, code optimization, automated testing, code review, and bug detection and prevention.
Which region is expected to hold the highest share in the AI code tools market?
North America is expected to dominate the AI code tools market in 2028. North America is at the forefront of AI code tool development and adoption, with a thriving ecosystem of startups, established tech giants, and innovative enterprises actively leveraging these tools.
Which are key end users adopting AI code tools solutions and services?
Key end users adopting AI code tools solutions and services include BFSI, Healthcare & Life Sciences, IT & ITeS, Retail & eCommerce, Manufacturing, Telecommunications, Media & Entertainment, Government & Public Sector And Other Vertical (Education, Automotive and Energy & Utilities)
Which are the key drivers supporting the market growth for AI code tools?
The key drivers supporting the market growth for AI code tools include rapid advancements in generative Al is revolutionizing software development, increased efficiency and productivity with Al code tools, need to assist developers in tackling complex coding tasks and enhance scalability and transformative shift in the roles of software developers.
Who are the key vendors in the market for AI code tools?
The key vendors in the global AI code tools market include are IBM (US), Microsoft (US), Google (US), AWS (US), Salesforce (US), Meta (US), OpenAI (US), Tabnine (Israel), Replit (US), Sourcegraph (US), Moolya (India), Synk (US), CircleCI (US), JetBrains (Czech Republic), Adacore (France), WingWare (US), Datadog (US), Lightning AI (US), Kodezi (US), Sourcery (England), CodeWP (US), SQLAI.ai (Germany) , SinCode AB (Sweden), Seek AI (US), Enzyme (US), Assistive.ai (Germany), CodiumAI (Israel), Mutable AI (US), Judini (US), Safurai (Italy).
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The research study for the AI code tools market involved extensive secondary sources, directories, and several journals. Primary sources were mainly industry experts from the core and related industries, preferred AI code tools provider, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews were conducted with various primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information, and assess the market’s prospects.
Secondary Research
The market size of companies offering AI code tools and services was arrived at based on secondary data available through paid and unpaid sources. It was also arrived at by analyzing the product portfolios of major companies and rating the companies based on their performance and quality.
In the secondary research process, various sources were referred to for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendor websites. Additionally, AI code tools spending of various countries was extracted from the respective sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on solutions, services, market classification, and segmentation according to offerings of major players, industry trends related to solutions, services, deployment modes, functionality, applications, verticals, and regions, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and AI code tools expertise; related key executives from AI code tools vendors, SIs, professional service providers, and industry associations; and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using AI code tools, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of AI code tools and services, which would impact the overall AI code tools market
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Market Size Estimation
Multiple approaches were adopted for estimating and forecasting the AI code tools market. The first approach involves estimating the market size by summation of companies’ revenue generated through the sale of tools and services.
Market Size Estimation Methodology-Top-down approach
In the top-down approach, an exhaustive list of all the vendors offering solutions and services in the AI code tools market was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor’s offerings were evaluated based on the breadth of solutions and services, deployment modes, applications, and verticals. The aggregate of all the companies’ revenue was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets repository for validation.
Market Size Estimation Methodology-Bottom-up approach
In the bottom-up approach, the adoption rate of AI code tools and services among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of AI code tools and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the AI code tools market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major AI code tool providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall AI code tools market size and segments’ size were determined and confirmed using the study
Top-down and Bottom-up approaches
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Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
According to IBM, AI code tools refer to a suite of advanced software solutions empowering developers and data scientists in the creation, training, and deployment of AI & ML models. These tools collectively enable the seamless integration of AI capabilities into applications and business processes, fostering innovation and efficiency in the development lifecycle.
According to Microsoft, AI code tools are a comprehensive set of software solutions designed to empower developers in building, training, and deploying AI models.
Stakeholders
- AI code tool vendors
- AI code solution vendors
- Managed service providers
- Support and maintenance service providers
- System Integrators (SIs)/migration service providers
- Value-added resellers (VARs) and distributors
- Distributors and value-added resellers (VARs)
- System integrators (SIs)
- Independent software vendors (ISV)
- Third-party providers
- Technology providers
Report Objectives
- To define, describe, and predict the AI code tools market by offering (tools and services), technology, application, vertical, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the AI code tools market.
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- Product matrix provides a detailed comparison of the product portfolio of each company
Geographic Analysis as per Feasibility
- Further breakup of the North American AI code tools Market
- Further breakup of the European Market
- Further breakup of the Asia Pacific Market
- Further breakup of the Middle East & Africa Market
- Further breakup of the Latin American AI code tools Market
Company Information
- Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in AI Code Tools Market