Global 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
根據 KBV Cardinal Matrix 發表的分析，微軟公司和Google有限責任公司在 AI 程式碼工具市場處於領先。 2023 年 5 月，Google LLC 宣布推出名為 PaLM2 的下一代語言模型，該模型具有改進的多語言、推理和編碼功能。透過此公告，Google旨在幫助開發人員和資料科學家建立生成式人工智慧應用程式。
軟體開發在電子商務、醫療保健和金融等各個行業都有很高的需求。隨著公司越來越依賴軟體解決方案來改善業務並提高競爭力，對更有效率、更可靠的開發工具的需求也在增加。隨著智慧型手機、物聯網設備、網路應用程式等的普及，對軟體應用程式的需求正在迅速增加。 AI 程式碼工具透過自動化程式碼產生和測試等開發任務來加速這些應用程式的開發。將人工智慧和機器學習融入各種應用程式和服務的運動日益盛行。人工智慧程式碼工具對於人工智慧開發至關重要，因為它們有助於高效產生複雜的演算法、預測模型和其他人工智慧元件。由於軟體開發需求的增加，AI程式碼工具市場正在顯著擴大。
就工具部署類型而言，市場分為雲端和本地。 2022年，雲端細分市場收益佔有率最大。雲端基礎的人工智慧程式碼工具為組織提供了按需擴展資源的能力。開發人員擁有處理各種編碼計劃所需的運算能力和儲存空間，而不受本地硬體的限制。雲端基礎的AI 程式碼工具與流行的 IDE 和程式碼編輯器整合。這種整合透過在開發人員的首選環境中提供編碼幫助來簡化開發人員的工作流程。雲端基礎的人工智慧程式碼工具的採用引入了靈活的定價模式，包括計量收費和基於訂閱的計劃。用戶只需為他們消耗的資源付費，從而提供成本效率和預算可預測性。
從技術角度來看，市場分為機器學習、自然語言處理和生成人工智慧。 2022年，機器學習領域以最大的收益佔有率主導市場。機器學習演算法不斷提高程式碼提案的準確性和相關性。這些工具現在可以根據說明的程式碼、編碼模式和開發人員意圖提供上下文感知建議。機器學習模型用於根據開發人員類型預測程式碼完成情況。這些模型考慮程式碼的上下文，並幫助您完成程式碼片段、函數名稱和變數名稱。使用機器學習產生測試案例，使測試過程更加有效和全面。 AI程式碼工具可以識別潛在的測試場景並產生測試程式碼。
根據應用程式，市場分為資料科學/機器學習、雲端服務/DevOps、Web 開發、行動應用程式開發、遊戲開發、嵌入式系統等。 2022年市場中，雲端服務/DevOps領域將佔據相當大的收益佔有率。開發人員可以即時配合措施編碼計劃、共用程式碼並進行協作，無論地理位置如何。這些工具非常適合 DevOps 工作流程，因為 DevOps 實踐強調協作。雲端服務允許組織自訂和配置人工智慧程式碼工具，以滿足自家公司的編碼標準和要求。 DevOps 實踐鼓勵自動化和標準化，從而可以輕鬆應用自訂配置。
按行業分類，可分為 BFSI、IT/通訊、醫療保健/生命科學、製造、零售/電子商務、政府/公共部門、媒體/娛樂等。 2022年，BFSI細分市場以最大的收益佔有率主導市場。 BFSI 領域經常需要開發自訂金融應用程式，例如銀行軟體、行動銀行應用程式和保險申請處理系統。這種客製化使金融機構能夠應對不斷變化的市場條件和客戶需求。安全性是 BFSI 領域的重中之重。人工智慧程式碼工具有助於產生漏洞較少的安全程式碼，幫助金融機構保護敏感資料和金融交易。
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.
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.
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.
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.
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.
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.
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.
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.
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.
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:
Unique Offerings from KBV Research