PUBLISHER: KBV Research | PRODUCT CODE: 1335935
PUBLISHER: KBV Research | PRODUCT CODE: 1335935
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