市场调查报告书
商品编码
1395548
人工智慧编码工俱全球市场规模、占有率、行业趋势分析报告:按报价、按技术、按应用、按行业、按地区、展望和预测,2023-2030Global AI Code Tools Market Size, Share & Industry Trends Analysis Report By Offering, By Technology (Machine Learning, Natural Language Processing, and Generative AI), By Application, By Vertical, By Regional Outlook and Forecast, 2023 - 2030 |
2030年,AI代码工具市场规模预计将达到172亿美元,预测期内市场成长率为22.3%。
根据 KBV Cardinal Matrix 发表的分析,微软公司和Google有限责任公司在 AI 程式码工具市场处于领先。 2023 年 5 月,Google LLC 宣布推出名为 PaLM2 的下一代语言模型,该模型具有改进的多语言、推理和编码功能。透过此公告,Google旨在帮助开发人员和资料科学家建立生成式人工智慧应用程式。
市场成长要素
软体开发需求增加
软体开发在电子商务、医疗保健和金融等各个行业都有很高的需求。随着公司越来越依赖软体解决方案来改善业务并提高竞争力,对更有效率、更可靠的开发工具的需求也在增加。随着智慧型手机、物联网设备、网路应用程式等的普及,对软体应用程式的需求正在迅速增加。 AI 程式码工具透过自动化程式码产生和测试等开发任务来加速这些应用程式的开发。将人工智慧和机器学习融入各种应用程式和服务的运动日益盛行。人工智慧程式码工具对于人工智慧开发至关重要,因为它们有助于高效产生复杂的演算法、预测模型和其他人工智慧元件。由于软体开发需求的增加,AI程式码工具市场正在显着扩大。
低程式码/无程式码平台的采用增加
具有人工智慧程式码产生功能的低程式码/无程式码开发平台正在兴起。这些平台允许非技术用户参与软体开发,减轻专业开发人员的负担并加速应用开发。低程式码/无程式码平台透过让更广泛的用户(包括公民开发人员和业务分析师)可以使用软体开发来实现软体开发的民主化。这些平台中的人工智慧程式码工具使用户可以更轻鬆地产生程式码,从而扩大了潜在开发人员的范围。由于越来越多地采用敏捷开发,预计市场将因所有这些因素而成长。
市场抑制因素
复杂且专业的应用
人工智慧程式码工具通常缺乏复杂应用程式所需的特定领域知识。人工智慧程式码工具有时很难理解航太、医疗保健和金融等专业行业的具体要求、细微差别和最佳实践。人工智慧程式码工具在很大程度上依赖训练资料来学习并做出资讯的决策。为专业应用产生高品质、相关且全面的培训资料既困难又耗时。专业应用通常包括复杂的演算法、复杂的逻辑和独特的资料处理要求。产生的程式码的品质可能会阻碍市场的成长。
供给展望
透过提供,市场分为工具和服务。在2022年的AI代码工具市场中,服务业占据了相当大的收益占有率。咨询服务可协助组织评估其软体开发需求并确定整合人工智慧程式码工具的机会。顾问提供有关工具选择、实施策略和最佳实践的指导。该服务还包括帮助开发人员和团队有效使用人工智慧程式码工具的培训计划。这透过增加用户对这些工具的了解和信心来改善市场区隔。该提供者提供程式码审查和品质保证服务,以帮助组织确保人工智慧产生的程式码符合品质标准并遵守最佳实践。
工具展望
就工具部署类型而言,市场分为云端和本地。 2022年,云端细分市场收益占有率最大。云端基础的人工智慧程式码工具为组织提供了按需扩展资源的能力。开发人员拥有处理各种编码计划所需的运算能力和储存空间,而不受本地硬体的限制。云端基础的AI 程式码工具与流行的 IDE 和程式码编辑器整合。这种整合透过在开发人员的首选环境中提供编码帮助来简化开发人员的工作流程。云端基础的人工智慧程式码工具的采用引入了灵活的定价模式,包括计量收费和基于订阅的计划。用户只需为他们消耗的资源付费,从而提供成本效率和预算可预测性。
技术展望
从技术角度来看,市场分为机器学习、自然语言处理和生成人工智慧。 2022年,机器学习领域以最大的收益占有率主导市场。机器学习演算法不断提高程式码提案的准确性和相关性。这些工具现在可以根据说明的程式码、编码模式和开发人员意图提供上下文感知建议。机器学习模型用于根据开发人员类型预测程式码完成情况。这些模型考虑程式码的上下文,并帮助您完成程式码片段、函数名称和变数名称。使用机器学习产生测试案例,使测试过程更加有效和全面。 AI程式码工具可以识别潜在的测试场景并产生测试程式码。
应用前景
根据应用程序,市场分为资料科学/机器学习、云端服务/DevOps、Web 开发、行动应用程式开发、游戏开发、嵌入式系统等。 2022年市场中,云端服务/DevOps领域将占据相当大的收益占有率。开发人员可以即时配合措施编码计划、共用程式码并进行协作,无论地理位置如何。这些工具非常适合 DevOps 工作流程,因为 DevOps 实践强调协作。云端服务允许组织自订和配置人工智慧程式码工具,以满足自家公司的编码标准和要求。 DevOps 实践鼓励自动化和标准化,从而可以轻鬆应用自订配置。
各行业展望
按行业划分,可分为 BFSI、IT/通讯、医疗保健/生命科学、製造、零售/电子商务、政府/公共部门、媒体/娱乐等。 2022年,BFSI细分市场以最大的收益占有率主导市场。 BFSI 领域经常需要开发自订金融应用程序,例如银行软体、行动银行应用程式和保险申请处理系统。这种客製化使金融机构能够应对不断变化的市场条件和客户需求。安全性是 BFSI 领域的重中之重。人工智慧程式码工具有助于产生漏洞较少的安全程式码,帮助金融机构保护敏感资料和金融交易。
区域展望
从区域来看,我们对北美、欧洲、亚太地区和拉丁美洲地区的市场进行了分析。 2022年,亚太地区在市场中获得了显着的收益占有率。亚太地区拥有许多技术人才,包括软体开发人员、资料科学家和人工智慧工程师。这些专业人员越来越多地使用人工智慧程式码工具来提高生产力和效率。亚太地区的电子商务和零售业正在迅速扩张。人工智慧程式码工具用于开发推荐系统、库存管理解决方案和客户服务聊天机器人。
The Global AI Code Tools Market size is expected to reach $17.2 billion by 2030, rising at a market growth of 22.3% CAGR during the forecast period.
On-premises deployment gives organizations complete control over the customization and configuration of AI code tools. Consequently, the On-premises segment would generate approximately 11.35% share of the market by 2030. This is particularly valuable for organizations with unique coding standards, specific coding practices, or the need to integrate AI code tools with existing on-premises systems. Organizations that develop proprietary code or sensitive intellectual property prefer to keep code on-premises to protect their assets. On-premises deployment provides an added layer of privacy and security, which is important for many businesses.
The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In August, 2023, IBM Corporation unveiled a new generative AI-assisted product called Watsonx Code Assistant for Z, to accelerate code development and incresing developer productivity, throughout the application modernization lifecycle. Additionally, In August, 2023, Meta, Inc. has unveiled Code Llama, a powerful code generation model. This specialized Llama variant helps with code completion and debugging in popular programming languages like C++, Java, PHP, Typescript (JavaScript), and more.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the AI Code Tools Market. In May, 2023, Google LLC introduced a next generation language model called PaLM2 with improved multilingual, reasoning, and coding capabilities. Through this launch Google aims to give developers and data scientists more capabilities to build generative AI applications. and Companies such as Meta Platforms, Inc., IBM Corporation, Salesforce, Inc. are some of the key innovators in the Market.
Market Growth Factors
Increasing Demand for Software Development
Software development is in high demand across several industries, including e-commerce, healthcare, and finance. As enterprises increasingly rely on software solutions to improve their operations and competitiveness, the need for more efficient and dependable development tools becomes critical. With the proliferation of smartphones, IoT devices, web applications, and more, the demand for software applications has surged. AI code tools expedite the development of these applications by automating code generation, testing, and other development tasks. Integrating AI and machine learning into various applications and services is rising. AI code tools are essential for AI development, as they can help generate complex algorithms, predictive models, and other AI components efficiently. The AI code tools market is expanding significantly due to the increasing demand for software development.
Growing Adoption of Low-Code/No-Code Platform
Low-code and no-code development platforms are on the rise, with AI code generation features. These platforms empower non-technical users to participate in software development, reducing the burden on professional developers and accelerating application development. Low-code/no-code platforms democratize software development by making it accessible to a broader range of users, including citizen developers and business analysts. AI code tools within these platforms enable users to generate code more easily, expanding the pool of potential developers. As a result of the increased adoption of agile development, the market is estimated to grow due to all these factors.
Market Restraining Factors
Complex and Specialized Applications
AI code tools often lack the domain-specific knowledge required for complex applications. They can struggle to understand the specific requirements, nuances, and best practices of specialized industries, such as aerospace, healthcare, or finance. AI code tools heavily rely on training data to learn and make informed decisions. Generating high-quality, relevant, comprehensive training data for specialized applications can be challenging and time-consuming. Specialized applications often involve complex algorithms, intricate logic, and unique data processing requirements. The quality of generated code can hamper the market growth.
Offering Outlook
By offering, the market is bifurcated into tools and services. The services segment covered a considerable revenue share in the AI code tools market in 2022. Consulting services help organizations assess their software development needs and identify opportunities for integrating AI code tools. Advisors provide guidance on tool selection, implementation strategies, and best practices. Services include training programs to help developers and teams become proficient in using AI code tools effectively. This uplifts the market segment by enhancing user knowledge and confidence in these tools. Providers offer code review and quality assurance services to assist organizations in ensuring that AI-generated code meets quality standards and adheres to best practices.
Tools Outlook
Under tools deployment type, the market segmented into cloud and on premise. In 2022, the cloud segment registered the maximum revenue share in the market. Cloud-based AI code tools provide organizations with the ability to scale resources on demand. Developers harness the computing power and storage needed to work on a wide range of coding projects without the constraints of local hardware. Cloud-based AI code tools were integrated with popular IDEs and code editors. This integration streamlined the developer's workflow by providing coding assistance within their preferred environment. Adopting cloud-based AI code tools introduced flexible pricing models, such as pay-as-you-go and subscription-based plans. Users only paid for their consumed resources, offering cost-efficiency and budget predictability.
Technology Outlook
On the basis of technology, the market fragmented into machine learning, natural language processing, and generative AI. in 2022, the machine learning segment dominated the market with maximum revenue share. Machine learning algorithms are continuously improving the accuracy and relevance of code suggestions. These tools can now provide context-aware recommendations based on the code written, coding patterns, and the developer's intent. Machine learning models are used to predict code completions as developers' type. These models consider the context of the code, helping to complete code snippets, function names, and variable names. Machine learning is used to generate test cases, making the testing process more effective and comprehensive. AI code tools can identify potential test scenarios and generate test code.
Application Outlook
Based on application, the market is classified into data science & machine learning, cloud services & DevOps, web development, mobile app development, gaming development, embedded systems, and others. The cloud services & DevOps segment covered a considerable revenue share in the market in 2022. Developers can work on coding projects in real-time, share code, and collaborate regardless of geographical location. DevOps practices emphasize collaboration, making these tools well-suited to DevOps workflows. Cloud services allow organizations to customize and configure AI code tools to align with their coding standards and requirements. DevOps practices encourage automation and standardization, making it easier to apply custom configurations.
Vertical Outlook
On the basis of vertical, the market is divided into BFSI, IT & telecom, healthcare & life sciences, manufacturing, retail & eCommerce, government & public sector, media & entertainment, and others. In 2022, the BFSI segment dominated the market with maximum revenue share. The BFSI segment frequently requires the development of custom financial applications, such as banking software, mobile banking apps, and insurance claim processing systems. This customization allows financial institutions to adapt to changing market conditions and customer demands. Security is a top priority in the BFSI segment. AI code tools can assist in generating secure code that is less prone to vulnerabilities, helping financial organizations protect sensitive data and financial transactions.
Regional Outlook
Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the Asia Pacific region acquired a significant revenue share in the market. Asia Pacific is home to a large pool of tech talent, including software developers, data scientists, and AI engineers. These professionals increasingly use AI code tools to enhance their productivity and efficiency. The e-commerce and retail sectors in APAC are expanding rapidly. AI code tools are used to develop recommendation systems, inventory management solutions, and chatbots for customer service.
The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Google LLC (Alphabet, Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce, Inc., Meta Platforms, Inc., OpenAI, L.L.C., Datadog, Inc., Tabnine Inc., and CodiumAI
Recent Strategies Deployed in AI Code Tools Market
Partnership, Collaborations & Agreements
June-2023: Microsoft Corporation entered into partnership with Microstrategy Incorporated, an American company specializing in business intelligence (BI), mobile software, and cloud-based services. In this alliance, Microsoft's objective is to integrate its cutting-edge AI capabilities into Microstrategy's business intelligence suite, enabling users to create fresh visualizations and dashboards while minimizing the manual efforts presently needed for building workflows and other content.
Apr-2023: IBM Corporation joined hands with Siemens Digital Industries Software, a subsidiary of Siemens AG specializing in industry, infrastructure, and digital transformation. Through this collaboration they have joined forces to enhance their long-term partnership working together to create integrated software solutions that bridge IBM Engineering System Design Rhapsody for systems engineering with Siemens' Xcelerator software and services, including Teamcenter® for Product Lifecycle Management (PLM) and Capital™ for electrical/electronic (E/E) systems development and implementation.
Mar-2023: Google LLC's cloud business today announced a partnership with Replit Inc., the creator of a popular coding platform used by more than 20 million developers. The 2023-Mar: Google Cloud, a division of Google LLC, has partnered with Replit Inc, an American software company offering online integrated development solutions. This collaboration aims to enhance software development by integrating Google's large language models with Replit IDEs. This integration will enable users to generate code based on text prompts, explain existing code, and troubleshoot software errors within Replit's cloud-based IDE.
Mar-2023: TabNine inc. joined forces with Google Cloud, a division of Google LLC, an American multinational technology company focusing on artificial intelligence. This collaboration's goal is to enhance generative AI on Google Cloud Platform (GCP), enabling the use of generative AI to simplify coding and provide developer support through a Google Cloud-powered platform, ultimately empowering developers to harness AI on Google Cloud more effectively.
June-2021: Amazon Web Services, an Amazon division, has joined forces with Salesforce, a cloud-based CRM software company. This collaboration aims to combine Salesforce and AWS capabilities for faster development of impactful business applications, facilitating digital transformation and enhancing the Salesforce Customer360 experience while simplifying developers' lives.
Product Launches & Product Expansions
Aug-2023: IBM Corporation unveiled a new generative AI-assisted product called Watsonx Code Assistant for Z, which help in enable faster translation of COBOL to Java on IBM Z. through this product launch IBM aims to accelerate code development and incresing developer productivity, throughout the application modernization lifecycle.
Aug-2023: Meta, Inc. has unveiled Code Llama, a powerful code generation model. This specialized Llama variant helps with code completion and debugging in popular programming languages like C++, Java, PHP, Typescript (JavaScript), and more. Meta's goal with this release is to empower software engineers across all sectors by enhancing their capabilities and addressing vulnerabilities.
June-2023: TabNine Inc. has unveiled Tabnine Chat, an AI-powered assistant designed for developers. Tabnine Chat not only generates code but also responds to questions related to an organization's codebase. With this release, Tabnine's objective is to seamlessly integrate the Chat feature into its platform, aiming to revolutionize the entire software development process within organizations, enabling developers to accelerate the creation of business outcomes.
May-2023: Google LLC has introduced a next generation language model called PaLM2 with improved multilingual, reasoning, and coding capabilities. Through this launch Google aims to give developers and data scientists more capabilities to build generative AI applications.
Mar-2023: Codium Ltd. has introduced TestGPT, a cutting-edge AI-powered solution designed for code error testing. TestGPT leverages the immense capabilities of OpenAI's GPT large language model. With this release, Codium's primary objective is to provide developers with an interactive code testing tool that dynamically generates tests to enhance their coding experience.
June-2022: Amazon, Inc. has introduced a novel AI-generated coding tool named Codewhisper, akin to GitHub Copilot. Codewhisper functions as an AI pair programming companion, capable of automatically completing entire functions with minimal input, such as a comment or a few keystrokes. Currently, it offers support for Java, JavaScript, and Python.
Merger & Acquisitions
Aug-2023: Datadog, Inc. has acquired Codiga, a company developed by Xcoding Labs, Inc. Codiga specializes in creating a platform that assists software developers in generating code. This acquisition is part of Datadog's broader strategy to offer an all-encompassing observability platform that addresses various stages of the software development process. By integrating Codiga's technology, Datadog aims to enhance its capability to identify and rectify errors at an earlier stage in the development cycle, ultimately leading to time and cost savings and improved product delivery.
Nov-2021: Datadog Inc. Took over Ozcode, a company specializing in innovative debugging solutions for .NET applications. This strategic acquisition by Datadog is aimed at enhancing its portfolio by introducing live debugging solutions. These solutions will address the challenges of troubleshooting production issues, eliminating the uncertainty that developers often face when trying to diagnose what caused errors to occur.
May-2020: Microsoft Corporation has successfully completed the acquisition of Softomotive Ltd., a company specializing in robotic process automation technology for digital workplaces. Through this strategic acquisition, Microsoft aims to enhance its low-code robotic process capabilities within Microsoft Power Automate. This move is part of Microsoft's commitment to making robotic process automation more accessible and user-friendly, allowing individuals from all backgrounds to create bots and streamline business processes.
Market Segments covered in the Report:
By Offering
By Technology
By Application
By Vertical
By Geography
Companies Profiled
Unique Offerings from KBV Research