人工智慧 (AI)套件全球市場規模、佔有率、行業趨勢分析報告：2023-2030 年按組件、技術、行業和地區分類的展望和預測
Global Artificial Intelligence Toolkit Market Size, Share & Industry Trends Analysis Report By Component (Software, Hardware, and Services), By Technology, By Vertical, By Regional Outlook and Forecast, 2023 - 2030
預計到 2030 年，全球人工智慧 (AI)套件市場規模將達到 1,644 億美元，預測期內市場年複合成長率為 34.3%。
根據KBV Cardinal Matrix發表的分析，微軟和Google是這個市場的先驅。 2023 年 9 月，微軟公司擴大了與阿布達比 G42 的合作夥伴關係，以開發跨領域的人工智慧技術並在阿拉伯聯合大公國提供雲端基礎設施。此舉使阿拉伯聯合大公國的公共部門和其他行業能夠使用 Microsoft Azure 的雲端和人工智慧功能，確保遵守當地的隱私和監管要求。 IBM公司、NVIDIA公司和英特爾公司等公司是這個市場的主要創新者。
例如，人工智慧套件用於教育計畫、線上課程以及個人學習人工智慧概念和開發技術的培訓。教育資源的可用性有利於技能發展。人工智慧教育和培訓計畫幫助個人（包括開發人員、資料科學家和工程師）獲得使用人工智慧套件所需的知識和技能。這些項目對於培養人工智慧產業的人才至關重要。隨著人工智慧認證和專業資格的普及，您可以展示您在人工智慧開發方面的專業知識。這些程式通常需要人工智慧套件的實務經驗。訓練營提供人工智慧開發的密集培訓，並通常將人工智慧套件涵蓋其課程中。該訓練營旨在幫助參與者做好準備，快速進入產業中與人工智慧相關的角色。對於想要透過學習 AI 開發來增強技能的軟體開發人員來說，AI 套件是不可或缺的資源。這些套件將幫助您快速啟動您的人工智慧計劃。由於人工智慧教育和技能開拓的進步，預計該市場將會成長。
按組成部分，市場分為軟體、硬體和服務。 2022年，軟體領域佔據市場最高收益佔有率。人工智慧套件包含廣泛的軟體元件、函式庫和框架，使開發人員、資料科學家和企業能夠利用人工智慧的力量。例如，Google 開發的 TensorFlow 是最受歡迎的開放原始碼機器學習框架之一。 TensorFlow 2.0引進Keras作為官方進階API，更容易使用。 Hugging Face 提供尖端的 NLP 模型和庫，包括以其預訓練語言模型（例如 BERT 和 GPT-2）而聞名的 Transformers。
根據技術，市場分為自然語言處理、機器學習、電腦視覺和機器人流程自動化。 2022 年，機器學習領域在市場中取得了顯著的收益佔有率。 AI套件附帶各種 ML 演算法，從傳統的統計模型到尖端的深度學習架構。這種多樣性使開發人員能夠為特定任務選擇最合適的演算法，從而獲得更準確、更有效的人工智慧解決方案。機器學習框架和套件讓更多人可以使用人工智慧，從而實現了人工智慧的民主化。這些套件使企業、研究人員和個人能夠創建人工智慧應用程式，而無需廣泛的機器學習專業知識。
按產業分類，可分為 BFSI、零售/電子商務、醫療保健/生命科學、製造、IT/通訊、媒體/娛樂、能源/公用事業、政府/國防、汽車/運輸/物流等。到 2022 年，零售和電子商務領域將在市場中佔據重要的收益佔有率。零售商和電子商務平台正在部署人工智慧驅動的聊天機器人和虛擬助理，以提供客戶支援、聯絡方式處理和訂單追蹤。具有 NLP 功能的 AI套件支援開發這些聊天機器人並改善客戶服務。零售和電子商務公司正在使用人工智慧套件來檢測和防止詐欺。機器學習模型可以分析交易資料以識別可疑活動並防止非法貿易。
The Global Artificial Intelligence (AI) Toolkit Market size is expected to reach $164.4 billion by 2030, rising at a market growth of 34.3% CAGR during the forecast period.
AI toolkits are used to create predictive models that help identify individuals at risk of certain diseases. Consequently, the healthcare & life sciences segment captured $1,721.8 million revenue in the market in 2022. AI toolkits are used to develop AI models for medical imaging interpretation. These models can detect and diagnose conditions in radiology images such as X-rays, CT scans, and MRIs, improving the accuracy and efficiency of diagnoses. These models analyze patient data and genetic information for early intervention and preventive measures. AI toolkits support the analysis of electronic health records. Machine learning models can extract valuable insights from EHR data, aiding clinical decision-making and patient management.
The major strategies followed by the market participants are Partnerships, Collaborations & Agreements as the key developmental strategy to keep pace with the changing demands of end users. For instance, IBM Corporation expanded its collaboration with Amazon Web Services (AWS), to help mutual clients operationalize and derive value from generative AI. However, In September, 2023, NVIDIA Corporation partnered with Reliance Industries Limited, to advance artificial intelligence in India. The partnership will help to develop an indigenous foundation large language model trained on the nation's diverse languages and tailored for generative Al applications.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Market. In, September, 2023, Microsoft Corp. expanded its partnership with Abu Dhabi's G42, developing AI technology across sectors and providing cloud infrastructure in the United Arab Emirates. This move granted the UAE public sector and other industries access to Microsoft Azure's cloud and AI features, ensuring compliance with local privacy and regulatory requirements. Companies such as IBM Corporation, NVIDIA Corporation, Intel Corporation are some of the key innovators in the Market.
Market Growth Factors
AI education and skill development
For Instance, AI toolkits are used in educational programs, online courses, and training to help individuals learn AI concepts and development practices. The availability of educational resources promotes skill development. AI education and training programs help individuals, including developers, data scientists, and engineers, acquire the knowledge and skills needed to work with AI toolkits. These programs are essential for building a competent workforce in the AI industry. AI certifications and specializations are becoming more prevalent, allowing individuals to demonstrate their expertise in AI development. These programs often require hands-on experience with AI toolkits. Bootcamps provide intensive, focused training in AI development, often incorporating AI toolkits into the curriculum. They aim to prepare participants for AI-related roles in the industry quickly. AI toolkits are vital resources for software developers who want to enhance their skill set by learning AI development. They can quickly get started with AI projects using these toolkits. As a result of the increasing AI education and skill development, the market is estimated to grow.
Accessibility and democratization of AI
However, AI toolkits have made AI development more accessible, enabling a broader range of users, from developers to data scientists, to create AI applications without extensive AI expertise. This democratization has fueled the growth of AI solutions. Accessibility and democratization of AI have expanded the user base beyond specialized data scientists and AI experts. Accessibility has encouraged the use of AI for social good. Individuals and organizations with diverse backgrounds use AI toolkits to address societal issues, from healthcare diagnostics to environmental conservation. Democratization extends AI into non-technical fields such as marketing, healthcare, and education. Professionals in these domains use AI toolkits to integrate AI capabilities into their work. The market is expanding significantly due to the accessibility and democratization of AI.
Market Restraining Factors
Integration complexity for AI toolkit
Integrating AI solutions created with AI toolkits into existing systems and workflows can be difficult and time-consuming. Compatibility issues with legacy systems may arise. Different AI toolkits have varying compatibility with programming languages, hardware, and operating systems. This can make it challenging to seamlessly integrate AI solutions into an organization's existing technology stack. Ensuring that AI solutions built using toolkits can scale to meet increasing data volumes and user demands can be challenging. Scalability issues can result in performance bottlenecks. Introducing AI solutions into existing workflows can disrupt established processes and require retraining of employees. Integrating AI solutions require additional hardware, software, and computational resources. Allocating resources effectively can be a complex task. Integration complexity is a significant challenge that hampers the growth of the market.
By component, the market is categorized into software, hardware, and services. In 2022, the software segment held the highest revenue share in the market. AI toolkits encompass a wide range of software components, libraries, and frameworks that enable developers, data scientists, and businesses to harness the power of artificial intelligence. For instance, developed by Google, TensorFlow is one of the most popular open-source machine learning frameworks. TensorFlow 2.0 introduced Keras as its official high-level API, making it more user-friendly. Hugging Face provides state-of-the-art NLP models and libraries, including Transformers, known for its pre-trained language models like BERT, GPT-2, and more.
Based on technology, the market is classified into natural language processing, machine learning, computer vision, and robotic process automation. The machine learning segment recorded a remarkable revenue share in the market in 2022. AI toolkits come with various ML algorithms, from traditional statistical models to cutting-edge deep learning architectures. This diversity allows developers to choose the most suitable algorithms for specific tasks, leading to more accurate and effective AI solutions. ML frameworks and toolkits have democratized AI by making it accessible to a broader audience. They empower businesses, researchers, and individuals to create AI applications without the need for extensive ML expertise.
On the basis of vertical, the market is divided into BFSI, retail & eCommerce, healthcare & life sciences, manufacturing, IT & telecom, media & entertainment, energy & utilities, government & defense, automotive, transportation, & logistics, and others. The retail & eCommerce segment covered a considerable revenue share in the market in 2022. Retailers and eCommerce platforms deploy AI-powered chatbots and virtual assistants for customer support, query handling, and order tracking. AI toolkits with NLP capabilities enable the development of these chatbots, improving customer service. Retail and eCommerce companies use AI toolkits for fraud detection and prevention. Machine learning models can analyze transaction data to identify suspicious activities and protect against fraudulent transactions.
In 2022, the North America region led the market by generating the highest revenue share. North America has a robust technology ecosystem, with numerous tech giants, startups, research institutions, and academic centers dedicated to AI research and development. This ecosystem fosters innovation and drives the demand for AI toolkits. AI toolkits find applications in diverse industries across North America, including healthcare, finance, automotive, manufacturing, e-commerce, and more. The region's broad range of use cases contributes to adopting AI toolkits.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, IBM Corporation, Google LLC, Oracle Corporation, NVIDIA Corporation, Thales Group S.A., Intel Corporation, Adobe, Inc., Salesforce, Inc. and DataRobot, Inc.
Recent Strategies Deployed in Artificial Intelligence (AI) Toolkit Market
Partnerships, Collaborations, and Agreements:
Oct-2023: Microsoft Corporation expanded its partnership with Siemens, a German multinational technology conglomerate, and introduced Siemens Industrial Copilot as a first step, an AI-powered assistant improving human-machine collaboration in manufacturing. The integration between Siemens Teamcenter software and Microsoft Teams was launched, simplifying virtual collaboration across business functions.
Oct-2023: IBM Corporation expanded its collaboration with Amazon Web Services (AWS), a subsidiary of Amazon that provides on-demand cloud computing platforms, to advance the development of generative artificial intelligence (AI) tools. The partnership aimed to help mutual clients operationalize and derive value from generative AI. As part of the initiative, IBM Consulting aimed to train 10,000 consultants in generative AI expertise on AWS by the end of 2024.
Sep-2023: Microsoft Corp. expanded its partnership with Abu Dhabi's G42, developing AI technology across sectors and providing cloud infrastructure in the United Arab Emirates. This move granted the UAE public sector and other industries access to Microsoft Azure's cloud and AI features, ensuring compliance with local privacy and regulatory requirements.
Sep-2023: IBM Corporation renewed its research partnership with the Indian Institute of Technology (IIT), Bombay, and the Indian Institute of Science (IISc), Bangalore. The collaboration aimed to lead developments in hybrid cloud and artificial intelligence, focusing on areas such as natural language processing, generative AI for time series, combating fake news, hybrid cloud optimization, and sustainable computing.
Sep-2023: NVIDIA Corporation partnered with Reliance Industries Limited, an Indian multinational conglomerate, to advance artificial intelligence in India. The partnership is being done to boost India's artificial intelligence and semiconductor chip ambitions. Additionally, the partnership will help develop an indigenous foundation large language model trained on the nation's diverse languages and tailored for generative Al applications.
Sep-2023: NVIDIA Corporation expanded its partnership with Infosys Ltd., an Indian multinational information technology company that provides business consulting, information technology, and outsourcing services, to develop generative AI tools for enterprises, marking another India-focused initiative for the U.S.-based company known for powering ChatGPT. The enhanced alliance merged Nvidia AI Enterprise and Infosys Topaz, forming an expert workforce to assist businesses in utilizing the platform for building custom apps and solutions.
Sep-2023: Salesforce, Inc. expanded its strategic partnership with Google, an American multinational technology company focusing on artificial intelligence, to integrate Salesforce, the leading AI CRM, and Google Workspace, the widely used productivity tool. The collaboration introduced bidirectional integrations, enabling customers to merge context from Salesforce and Google Workspace, including Google Calendar, Docs, Meet, Gmail, and more, to enhance generative AI experiences across platforms.
Aug-2023: IBM Corporation collaborated with Salesforce, Inc., an American cloud-based software company, to accelerate global businesses across industries in adopting AI for CRM. The partnership aimed to revolutionize customer, partner, and employee experiences while safeguarding data. IBM Consulting and Salesforce worked with shared clients to expedite business transformations using generative AI.
Jul-2023: Thales Group S.A. partnered with Genethon, a pioneer and leader in gene therapy research and development for rare genetic diseases, to develop groundbreaking digital models for enhancing bioproduction yields in gene therapy. The collaboration combined expertise in artificial intelligence and healthcare innovation, bringing together research, industry, and digital services for joint innovative solutions.
Jun-2023: Thales Group S.A. announced a partnership with Google Cloud to enhance data security capabilities through generative AI, aiming to improve the discovery, classification, and protection of sensitive data for companies. This collaboration was part of Thales' generative AI strategy, introducing AI-powered features and experiences to users of the CipherTrust data security platform.
Jun-2023: Adobe, Inc. expanded its partnership with Omnicom Group Inc., A global leader in marketing communications, initiating a joint effort to provide enterprise generative AI capabilities to shared clients. This collaboration aimed to produce on-brand content, assisting marketers in orchestrating better outcomes.
May-2023: NVIDIA Corporation collaborated with Microsoft Corp. and integrated its AI Enterprise software into Microsoft's Azure Machine Learning to accelerate enterprise AI initiatives. This integration formed a secure, enterprise-ready platform, allowing global Azure customers to swiftly build, deploy, and manage customized applications using over 100 NVIDIA AI frameworks and tools supported in NVIDIA AI Enterprise, the software layer of NVIDIA's AI platform.
May-2023: NVIDIA Corporation partnered with ServiceNow, an American software company based in Santa Clara, California, to enhance enterprise workflow automation using powerful generative AI capabilities. This collaboration expanded ServiceNow's AI functionality, benefiting IT, customer service, employees, and developers, increasing productivity across the board.
May-2023: DataRobot, Inc. partnered with Microsoft to expedite AI adoption in the enterprise. Integrations with Microsoft Azure OpenAI Service, Azure Machine Learning, and Azure Kubernetes Service (AKS) allowed data scientists to leverage large language models (LLMs) for code writing assistance. This facilitated the building, deploying, and managing of end-to-end enterprise-ready AI solutions on Microsoft Azure for DataRobot and Microsoft customers.
Jan-2023: Microsoft Corporation expanded its strategic partnership with HCLTech, collaborating to leverage generative artificial intelligence (AI) for joint solutions that enhance business outcomes and transformation. Clients benefited from innovative solutions, improving productivity, streamlining IT operations, accelerating application development, and optimizing business processes using HCLTech's industry expertise and Microsoft's Azure OpenAI Service.
Oct-2022: Google Cloud expanded its partnership with Accenture, an Irish-American professional services company, by renewing their commitment to growing talent, increasing joint capabilities, developing new solutions with data and AI, and offering enhanced support. This collaboration aimed to assist clients in building a robust digital core and reinventing their enterprises on the cloud.
Aug-2022: Oracle Cloud Infrastructure, a subsidiary of Oracle Corporation, collaborated with Anaconda Inc., a software development and consulting company, to provide secure open-source Python and R tools and packages by embedding Anaconda's repository in OCI's artificial intelligence and machine learning services. This partnership allowed customers direct access to Anaconda services within OCI, eliminating the need for a separate enterprise license.
Product Launches and Product Expansions:
Oct-2023: Adobe, Inc. integrated generative AI enhancements into its core products, including Firefly, Illustrator, Adobe Express, and Photoshop, aiming to enhance creativity and precision in creative workflows.
Sep-2023Oracle Corporation enhanced Oracle Fusion Cloud Customer Experience (CX) with additional AI capabilities. This automation allowed marketers, sellers, and service agents to increase revenue and deliver exceptional customer experiences through conversational interfaces, providing relevant content, recommendations, and insights while eliminating manual tasks.
Sep-2023: Oracle Corporation introduced generative AI services for healthcare, incorporating the Oracle Clinical Digital Assistant into EHR solutions. This integration provided voice-commanded automation for providers, reducing manual tasks, improving patient care, and allowing patients to perform self-service actions through straightforward voice commands.
Sep-2023: Adobe, Inc. released the web version of Photoshop for all paid plan users. After nearly two years in beta, the web version now includes Firefly-powered AI tools like generative fill and generative expand. The toolbar features tools based on workflows, such as image reproduction or object selection, with full tool names displayed for beginners instead of tooltip descriptions.
Sep-2023: Salesforce, Inc. launched the next-gen Einstein AI, featuring Einstein Copilot, a built-in conversational assistant for every Salesforce application, and Einstein Copilot Studio for creating custom AI-powered apps. These advancements aimed to reshape how millions of CRM users interact with business applications, enhancing performance and job satisfaction.
Aug-2023: Google LLC introduced its artificial intelligence-powered tools to enterprise customers for a monthly fee of $30 per user. The new tools, including "Duet AI in Workspace," aided customers across Google apps with tasks such as writing in Docs, drafting emails in Gmail, and generating custom visuals in Slides, among others.
Aug-2023: Google Cloud collaborated with NVIDIA Corp., an American multinational technology company incorporated in Delaware, and announced AI infrastructure and software, enabling customers to construct and deploy large models for generative AI and accelerate data science workloads. Additionally, over the past two years, Google DeepMind and Google research teams have actively employed these integrations, leveraging NVIDIA technologies.
May-2023: IBM Corporation introduced IBM Watsonx, a released AI and data platform, empowering enterprises to scale advanced AI impact with trusted data and a comprehensive technology stack for training, tuning, and deploying models across their organization, ensuring speed, governance, and compatibility across any cloud environment.
Mar-2023: DataRobot, Inc. released AI Platform 9.0, rebranding its AI Cloud with added features for faster AI product deployment. The platform includes Workbench for experimentation, integrated with Notebook for code or code-free data science work, and features guardrails like bias mitigation and model monitoring.
Nov-2022: Intel Corporation launched streamlined artificial intelligence (AI) benefits within the Intel Partner Alliance, enhancing support for ecosystem partners, including independent software vendors (ISVs), original equipment and device manufacturers, and system integration (SI) partners. The move aimed to foster connections, drive innovation, and accelerate business growth.
Sep-2022: Salesforce, Inc. collaborated with AWS, a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs, to reveal integrations between the Salesforce Platform and Amazon SageMaker. This allowed customers to utilize Amazon SageMaker, AWS's machine learning service, in conjunction with Einstein, Salesforce's AI technology, to develop customized AI models for real-time use across the Customer 360.
Mar-2022: Adobe, Inc. unveiled new Adobe Sensei-powered capabilities in Adobe Experience Cloud, enhancing customer journeys with AI features. Over 80% of Adobe Experience Cloud customers leveraged these capabilities, including product recommendations, live search results, intelligent budget forecasting, cross-channel budget optimization, and smart content creation and delivery.
Acquisition and Mergers:
Sep-2023: Salesforce, Inc. acquired Airkit.ai, a provider of AI-powered customer service applications, to enhance AI capabilities. This addition supported Service, Sales, Marketing, and Commerce teams in swiftly adapting to the future of customer engagement in the AI era.
Mar-2022: Microsoft Corporation completed its acquisition of Nuance Communications Inc., a leader in conversational AI across various industries. This powerful combination aimed to enhance healthcare affordability and accessibility, as well as create more personalized customer experiences across all sectors. The Nuance team was welcomed into the Microsoft family with great satisfaction.
Mar-2022: Intel Corporation acquired Granulate, AI-powered optimization software that improves performance by creating a streamlined environment for any app, to expand operations in Israel and enhance tools for customers to manage traffic on Intel-powered systems. The acquisition enabled the application of Granulate's autonomous optimization software to production workloads without code changes, delivering optimized hardware and software value for every cloud and data center customer.
Sep-2021: DataRobot, Inc. acquired Decision.ai, a potent decision-making tool with transformative potential for businesses. This allowed DataRobot to integrate crucial complementary technology and onboard talented individuals like Dan Becker and his team. Additionally, the combination of the AI Cloud platform and an AI-native strategic success team empowered enterprises to harness AI's transformative power.
Oct-2020: Intel Corporation acquired SigOpt, a San Francisco startup with an optimization platform for running AI modeling and simulations more effectively. Intel integrated SigOpt's technology into its AI business, specifically within its AI Analytics Toolkit.
Jun-2020: DataRobot, Inc. acquired BCG's SOURCE AI technology, and both organizations entered a strategic partnership. This unique collaboration between a global consulting firm and an AI solution provider combined proprietary IP with consulting services, delivering both human expertise and technical know-how for optimal, continuous AI value.
May-2023: IBM Consulting established a Center of Excellence for generative AI, complementing its global AI and Automation practice. The existing practice, with 21,000 consultants, had conducted over 40,000 client engagements. The CoE had over 1,000 consultants with specialized generative AI expertise, engaging globally to enhance productivity in IT operations, core business processes, elevate customer experiences, and create new business models.
Market Segments covered in the Report:
Unique Offerings from KBV Research