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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
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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.

Scope of the Study

Market Segments covered in the Report:

By Offering

By Technology

By Application

By Vertical

By Geography

Companies Profiled

Unique Offerings from KBV Research

Table of Contents

Chapter 1. Market Scope & Methodology

Chapter 2. Market at a Glance

Chapter 3. Market Overview

Chapter 4. Competition Analysis - Global

Chapter 5. Global AI Code Tools Market by Offering

Chapter 6. Global AI Code Tools Market by Technology

Chapter 7. Global AI Code Tools Market by Application

Chapter 8. Global AI Code Tools Market by Vertical

Chapter 9. Global AI Code Tools Market by Region

Chapter 10. Company Profiles

Chapter 11. Winning Imperatives of AI Code Tools Market

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