市場調查報告書
商品編碼
1335935
自主人工智慧和自主代理全球市場規模、佔有率、行業趨勢分析報告:按領域、按技術、按交付型態(軟體、硬體、服務)、按軟體部署類型、按地區、前景和預測,2023年~2030年Global Autonomous AI and Autonomous Agents Market Size, Share & Industry Trends Analysis Report By Vertical, By Technology, By Offering (Software, Hardware, and Services), By Software Deployment Type, By Regional Outlook and Forecast, 2023 - 2030 |
到 2030 年,自主人工智慧和自主代理市場規模預計將達到 512 億美元,預測期內市場年複合成長率率為 40.7%。
根據KBV Cardinal矩陣中發布的分析,微軟公司和Google有限責任公司(Alphabet Inc.)是該市場的先驅。 2023年2月,微軟公司擴大了與OpenAI的合作關係,獨立行銷人工智慧超級運算和研究領域的先進人工智慧技術。 Oracle Corporation、NVIDIA Corporation 和 Salesforce, Inc. 等公司是該市場的主要創新者。
市場成長要素
人工智慧應用的成長
人工智慧在各個領域的應用不斷成長的趨勢是自主人工智慧和智慧體發展的主要要素。包括醫療保健、交通運輸、金融和製造在內的各種行業正在使用人工智慧來解決複雜問題並改善營運。隨著對有效和智慧解決方案的需求不斷增加,對能夠在無需持續人類互動的情況下獨立適應和運行的自主人工智慧系統和代理的需求也不斷增加。由此可見,人工智慧的不斷成長的應用預計將支持市場的擴大。
利用自主人工智慧和代理來改善醫療保健
自主人工智慧領域適合用途管理工作流程、影像分析、機器人手術、虛擬助理和臨床決策支援。自主人工智慧可以檢查大量醫療資料,包括患者記錄、測試結果和醫學影像,以幫助醫療保健專業人員做出準確的診斷。因此,可以完成先前由經過大量專業訓練的眼科醫生和驗光師執行的認知困難任務。因此,其市場需求正在迅速成長。
市場抑制因素
由於道德和法律方面的考察,市場面臨重大障礙
隨著自主人工智慧系統和代理變得更加複雜和普及,一些道德問題將會出現。自動駕駛汽車和機器人造成事故和傷害的可能性令人嚴重擔憂。由於機器決策、製造商設計和人類互動的相互作用,確定涉及自主代理的事故責任可能很困難。此外,許多自主代理由人工智慧演算法提供支持,這些演算法可以從訓練它們的資料中繼承偏差。偏見可能導致不公平歧視某些群體的決定。這些有關自主代理的道德和法律問題可能會阻礙市場的成長。
產業展望
按產業分類,BFSI、醫療保健與生命科學、IT 與電信、零售與電子商務、媒體與娛樂、能源與電力、汽車、運輸與物流、政府與國防、製造業等。 2022年,零售和電子商務部門在市場中佔據重要的收入佔有率。自主購物的興起是自主人工智慧的結果。顧客用智慧型手機付款的智慧「拿了就走」業務正在迅速流行。奈米店、智慧櫃和完全無人店是新策略的一部分。
技術展望
根據技術,市場分為機器學習(ML)、自然語言處理(NLP)、情境辨識和電腦視覺。 2022 年,電腦視覺領域在市場中佔據了重要的收入佔有率。自主人工智慧和代理使用電腦視覺作為核心技術來感知和理解周圍環境的視覺資料。電腦視覺演算法可以分析影像和視訊串流、識別物件、識別模式並得出有意義的特徵。
產品展望
市場分為硬體、服務和軟體。 2023年至2030年,硬體市場預計將以40.9%的年複合成長率成長。服務對於有效部署和運行自主人工智慧和代理系統至關重要。這些服務包括諮詢、實施和整合、培訓、支援和維護。市場上服務提供者的目標是提供增值服務,使組織能夠充分利用人工智慧系統。服務根據組織的特定要求量身定做,以促進協作、知識轉移和持續支持,從而最大限度地發揮自主人工智慧和代理技術的優勢。
軟體類型展望
就軟體類型而言,市場分為計算代理和機器人代理。到 2022 年,計算代理領域將佔據市場上最大的收入佔有率。計算代理僅存在於數位環境中,並由先進演算法和運算能力驅動。這些代理商使用機器學習和人工智慧來評估大量資料、預測結果、最佳化流程並做出自主選擇。
軟體部署展望
對於軟體部署,市場分為本地和雲端。 2022年,雲端細分市場以最大的收入佔有率主導市場。將人工智慧和代理系統託管在雲端服務供應商提供的遠端伺服器上,結構自主的人工智慧和代理雲端部署。這種部署策略為希望利用人工智慧和代理優勢的組織提供了許多好處。
區域展望
從區域來看,我們對北美、歐洲、亞太地區和拉丁美洲地區的市場進行了分析。 2022年,北美地區以最高的收入佔有率引領市場。美國和加拿大是兩個在自主人工智慧和自主代理開發和應用方面走在前沿的北美國家。該地區是人工智慧領域重要科技公司、研究機構和尖端新興企業的所在地。自主人工智慧正在北美的各個行業中得到應用,包括交通、醫療保健、銀行、製造和娛樂。
The Global Autonomous AI and Autonomous Agents Market size is expected to reach $51.2 billion by 2030, rising at a market growth of 40.7% CAGR during the forecast period.
Autonomous AI and autonomous agents revolutionized the financial institutions' function and provided services, profoundly impacting the BFSI (Banking, Financial Services, and Insurance) sector. Hence, the BFSI segment accounted for $821.2 million revenue in the market in 2022. These cutting-edge technologies present unparalleled opportunities for automation, superior decision-making, and increased customer service. In the BFSI industry, autonomous AI systems use machine learning algorithms to evaluate enormous volumes of financial data, detect trends, and make autonomous conclusions about fraud detection, risk management, and investment strategies.
The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. In May, 2023, SAP SE entered into a partnership with IBM Corporation to combine the latter's Watson AI engine over their complete solutions portfolio, consisting of SAP Business One, S/4 HANA Cloud, SAP S/4 HANA, and SAP Business ByDesign. Additionally, In May, 2023, NVIDIA Corporation signed a partnership with ServiceNow, Inc. to create powerful, top-notch generative AI capabilities which can change business processes with quicker and highly intelligent workflow automation.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC (Alphabet Inc.) are the forerunners in the Market. In February, 2023, Microsoft Corporation extended its partnership with OpenAI to independently market the advanced AI technology in AI supercomputing and research. Companies such as Oracle Corporation, NVIDIA Corporation and Salesforce, Inc. are some of the key innovators in the Market.
Market Growth Factors
Growing AI Applications
The rising tide of AI applications in a variety of disciplines is a major factor in the development of autonomous AI and agents. AI is being used to solve complicated problems and improve operations in a variety of industries, including healthcare, transportation, finance, and manufacturing. Autonomous AI systems and agents that can adapt and function independently without continual human interaction are becoming more and more necessary as the demand for effective and intelligent solutions increases. In light of this, it is correct to mention that the growing application of AI is estimated to support the market's expansion.
Using Autonomous AI and Agents to Improve Healthcare
The applications of autonomous AI that are most suitable are in the fields of administrative workflows, image analysis, robotic surgery, virtual assistants, and clinical decision support. To help medical personnel make an accurate diagnosis, autonomous AI may examine a tremendous amount of medical data, including patient records, test results, and medical imaging. As a result, it accomplishes a cognitive, challenging task previously carried out by ophthalmologists and optometrists with substantial, specialized training. Hence, their demand is growing rapidly in the market.
Market Restraining Factors
Significant Obstacles for Market from Ethical and Legal Considerations
Several ethical issues emerge as autonomous AI systems and agents become more sophisticated and widespread. The potential for autonomous vehicles or robots to cause accidents or harm is a significant concern. Determining liability in an accident involving an autonomous agent can be difficult due to the interplay between the machine's decisions, the manufacturer's design, and human interaction. Additionally, a large number of autonomous agents are driven by AI algorithms, and these algorithms may inherit biases from the data they were trained on. Due to biases, decisions that unfairly discriminate against certain groups may be made. These ethical and legal issues with autonomous agents may prevent the market from growing.
Vertical Outlook
On the basis of vertical, the market is categorized into BFSI, healthcare & life sciences, IT & telecom, retail & e-commerce, media & entertainment, energy & power, automotive, transportation & logistics, government & defense, manufacturing, and others. In 2022, the retail & e-commerce segment covered a considerable revenue share in the market. The rise of autonomous shopping is a result of autonomous AI. Smart "grab-and-go" businesses, where customers pay with their smartphones, are quickly gaining popularity. Nanostores, smart cabinets, and completely autonomous stores are a few of the new strategies.
Technology Outlook
Based on technology, the market is fragmented into machine learning (ML), natural language processing (NLP), context awareness and computer vision. The computer vision segment recorded a remarkable revenue share in the market in 2022. Autonomous AI and autonomous agents use computer vision as a core technology to perceive & comprehend visual data from their surroundings. Algorithms for computer vision can analyze images and video streams, identify objects, recognize patterns, and derive meaningful features.
Offering Outlook
By offering, the market is classified into hardware, services and software. The Hardware market is expected to witness a CAGR of 40.9% during (2023 - 2030). Services are essential to effectively deploying and operating autonomous AI and agent systems. These services include consulting, implementation & integration, training and support & maintenance. The goal of service providers in the market is to provide value-added services that allow organizations to utilize their AI systems fully. The services are tailored to the specific requirements of organizations, fostering collaboration, knowledge transfer, and ongoing support to maximize the benefits derived from autonomous AI and agent technologies.
Software Type Outlook
Under software type, the market is bifurcated into computational agents and robotic agents. In 2022, the computational agents segment witnessed the largest revenue share in the market. Computational agents exist exclusively in digital environments and are propelled by advanced algorithms and computing power. These agents use machine learning and artificial intelligence to evaluate enormous volumes of data, forecast outcomes, optimize processes, and make autonomous choices.
Software Deployment Outlook
Under software deployment, the market is segmented into on-premise, and cloud. In 2022, the cloud segment dominated the market with maximum revenue share. Hosting AI and agent systems on distant servers offered by cloud service providers constitutes cloud deployment for autonomous AI and agents. This deployment strategy provides numerous benefits to organizations seeking to leverage the strength of AI and agents.
Regional Outlook
Region wise, the market is analyzed across North America, Europe, Asia-Pacific and LAMEA. In 2022, the North America region led the market by generating the highest revenue share. The United States and Canada are two nations in North America that are at the forefront of the development and application of autonomous AI and autonomous agents. The region is home to significant technology companies, research institutions, and cutting-edge startups in artificial intelligence. Autonomous AI is being used in various industries in North America, including transportation, healthcare, banking, manufacturing, and entertainment.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Oracle Corporation, Google LLC (Alphabet Inc.), Salesforce, Inc., SAP SE, NVIDIA Corporation, Baidu, Inc., Uber Technologies, Inc., Cogito Tech LLC
Recent Strategies Deployed in Autonomous AI and Autonomous Agents Market
Partnerships, Collaborations & Agreements:
Jun-2023: Salesforce, Inc. released AI Cloud, a new product portfolio designed to provide "enterprise-ready" AI. This launch aims to boost the company's position in the ultra-competitive AI space and consists of tools developed to provide enterprise-ready AI.
May-2023: IBM announced the launch of the Watsonx Platform, a new platform to be released for foundation models and generative AI. The launched product provides a data store, governance toolkit, and studio. Furthermore, Watson products combined with generative AI and foundation models are to be released for digital labor, sustainability, AIOps, and security.
May-2023: Oracle Corporation introduces a new Oracle Autonomous Data Warehouse, the industry's foremost and unique autonomous database fueled by machine learning and optimized for analytics workloads. The launched product advances the proprietary and closed nature of conventional data lakes and warehouses.
Apr-2023: Oracle Corporation enhanced Oracle Fusion Cloud Applications portfolio which would further support clients to hasten distribution planning, maximizing operational efficiency and enhancing financial accuracy. The enhanced portfolio would consist of rebate management capabilities, new planning, and usage-based pricing across Oracle Fusion SCM and increase quote-to-cash processes within Oracle Fusion Applications.
Mar-2023: Salesforce, Inc. introduced Einstein GPT, a generative AI push with a pilot of technology having ChatGPT-like characteristics. This launch aims to develop a huge amount of opportunities for innovation in their suite of products as well as our broader ecosystem and wider suite.
Mar-2023: Baidu, Inc. announced the launch of Ernie Bot, the AI chatbot. The launched product can be applied for different applications, consisting of AI cloud, searches, autonomous driving, and smart devices.
Jul-2022: Microsoft Corporation rolled out Project AirSim, an end-to-end platform. The launched product would further facilitate autonomous flight. Moreover, Project AirSim uses high-fidelity simulation to safely create, educate, and test autonomous aircraft on Microsoft Azure.
Jul-2022: Baidu, Inc. introduced Apollo RT6, a modern electric autonomous driving vehicle. The launch would achieve the industry's Level 4 among five feasible levels of technology.
Sep-2021: Oracle unveiled Oracle Exadata X9M platforms, the next generation of the fastest and most cost-effective systems for running the Oracle Database. The new platform involves Exadata Cloud@Customer X9M and Oracle Exadata Database Machine X9M, the only platform that runs Oracle Autonomous Database in customer data centers.
Jun-2021: Salesforce, Inc. announced Einstein Relationship Insights, a brand-new AI-powered research agent. The launched product would autonomously analyze the internet data source and internet to determine relationships between companies, prospects, and customers to support sales reps close deals quickly. Moreover, Einstein Relationship Insights would behave as a virtual agent for salespersons within social media, all industries, email, scanning the web, and other online sources to reveal and suggest related companies and people.
Product Launches and Product Expansions:
May-2023: SAP SE entered into a partnership with IBM Corporation, an American multinational technology corporation. Under this partnership, both companies would combine the latter's Watson AI engine over their complete solutions portfolio, consisting of SAP Business One, S/4 HANA Cloud, SAP S/4 HANA, and SAP Business ByDesign.
May-2023: NVIDIA Corporation signed a partnership with ServiceNow, Inc., an American software company. Following this partnership, both companies would create powerful, top-notch generative AI capabilities which can change business processes with quicker and highly intelligent workflow automation.
May-2023: NVIDIA Corporation collaborated with WPP, plc, a British multinational advertising, communications, public relations, and technology-based company. Under this collaboration, both companies would create a content engine that would utilize NVIDIA Omniverse and AI to allow innovative teams to make superior commercial content quicker, more effectively, and at scale during staying completely aligned with a customer brand.
Mar-2023: Google Cloud, a subsidiary of Google LLC, teamed up with Oxbotica, an autonomous vehicle software developer. This collaboration would help to facilitate the deployment of autonomous software platforms for clients across the world. Additionally, this collaboration would integrate Oxbotica's market-leading autonomous vehicle software with Google Cloud's specialization in cloud infrastructure to develop safe, reliable, and scalable autonomous driving solutions for all businesses with transportation over their value chain.
Mar-2023: NVIDIA Corporation came into partnership with Adobe Inc., an American multinational computer software company. Under this partnership, both companies would co-create modern generative AI models. Furthermore, both companies would combine NVIDIA Omniverse, a platform for developing and operating 3D industrial metaverse applications with Microsoft 365 applications such as Teams, OneDrive, and SharePoint to connect 3D collaboration platforms and productivity.
Mar-2023: NVIDIA Corporation teamed up with Amazon Web Services, Inc., a subsidiary of Amazon.com, Inc. This collaboration aims to create the world's most expandable and on-demand AI infrastructure optimized for training growingly complex large language models (LLMs) and creating generative AI applications.
Feb-2023: Microsoft Corporation extended its partnership with OpenAI, an American artificial intelligence research laboratory. This partnership would further widen their previous partnership which would allow them to independently market the advanced AI technology in AI supercomputing and research.
Oct-2022: Microsoft Corporation collaborated with TCS, an Indian multinational information technology consulting and services company. Under this collaboration, both companies would use Project Bonsai, a low-code, secure, and compliant AI platform, to create innovative AI-powered autonomous solutions on the Microsoft Azure Cloud using Microsoft's in-depth domain expertise in industrial control systems.
Oct-2022: Google Cloud expanded its partnership with Accenture, specializing in information technology (IT) services and consulting. Through this partnership, both companies aimed at jointly developing new solutions using data and AI. Furthermore, it would enable the clients to build a strong core and reinvent their enterprises on the cloud.
Sep-2022: Uber Technologies, Inc. teamed up with Nuro, a pioneer autonomous vehicle company. This partnership aimed to utilize Nuro's autonomous, electric vehicles for food deliveries across the United States. Additionally, the partnership would underline the fastly growing potential for last-mile autonomous delivery of groceries, meals, and other goods and unlock autonomous delivery technology to Uber Eats all sizes of restaurants /merchants.
Sep-2021: Oracle came into a partnership with Adenza, a leading global provider of end-to-end, trading, treasury, risk management, and regulatory compliance. Following the partnership, Adenza would use the Autonomous Transaction Processing and Autonomous Data Warehouse of Oracle to improve RegCloud, its regulatory reporting product line. The partnership would integrate the Oracle Autonomous Database on OCI to Adenza's AxiomSL RegCloud SaaS portfolio which enables further flexibility to customers who have installed Oracle Database on-premises or have opted for Oracle Database for cloud services.
Jul-2021: Baidu, Inc. collaborated with the University of Maryland, College Park, a public land-grant research university. This collaboration aimed to launch a new benchmark in robotics. Moreover, under this collaboration, an autonomous excavator system would be produced which is claimed to give very good results.
Jun-2021: Oracle came into a multi-year partnership with Deutsche Bank, one of the world's largest financial services organizations. Following the partnership, Oracle would help to advance the database technology and expedite the digital transformation of the Bank. Moreover, the two companies would together explore the potential uses of data security technologies, analytics, AI, and blockchain to redesign new financial products and services.
Acquisitions and Mergers:
Jun-2021: IBM today announced the closing of its acquisition of Turbonomic, Inc., an Application Resource Management (ARM) and Network Performance Management (NPM) software provider based in Boston, MA. Now that Turbonomic is a part of our portfolio, IBM is the only company providing a one-stop shop of AI-powered automation capabilities, all built on Red Hat OpenShift to run anywhere.
Market Segments covered in the Report:
By Vertical
By Technology
By Offering
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures