Autonomous AI and Autonomous Agents Market Analysis and Forecast Size, Share, Forecast & Trends by Component (Services, Software, and Hardware), Technology (NLP, Machine Learning, Computer Vision, and Context Awareness), Deployment, and End-Use Industry - Global Forecast to 2035

Autonomous AI and Autonomous Agents Market Analysis and Forecast Booms as Intelligent Automation and Multi-Domain Applications Drive Growth

The global autonomous AI and autonomous agents market was valued at USD 7.91 billion in 2024. This market is expected to grow at 45.2% CAGR, reaching approximately USD 477.8 billion by 2035 from USD 11.5 billion in 2025.

The autonomous AI and autonomous agents market is expected to grow due to the rapid development of machine learning and deep learning technologies, as well as the increasing adoption of artificial intelligence in various industries. The utilization of autonomous agents in the financial sector enhances efficiency and contributes to greater accuracy in decision-making, helping financial institutions navigate the complexities of today's dynamic markets.

Machine learning & deep learning are key technologies in the auto industry. ML and deep learning allow the car to learn from its data and enhance its driving performance over time. Neural networks, for instance, are trained to identify objects and recognize traffic signals and signs. These advancements in autonomous AI, bolstered by machine learning and deep learning technologies, are not only revolutionizing vehicle safety but also paving the way for the development of self-driving cars that can navigate complex environments with precision and reliability.

Competitive Scenario and Insights

Click here to: Get Free Sample Pages of this Report

The autonomous AI and autonomous agents market is quite competitive and major high holders are interested in being innovative, scalable, and be able to integrate it with their activities or offerings. The old technology giants such as Google DeepMind, IBM, Microsoft, and Amazon are continuing to build on their formidable AI research and cloud capabilities to offer advanced autonomous solutions, with new startups, including Adept AI and Fetch.ai offering highly focused, and niche use-cases. The factor further contributes to competition as companies invest heavily in R&D to increase flexibility of adaptation and accurate decision making and real-time processing. Strategic alliances, acquisitions and cross-industry cooperation are also prevalent, and allow the players to integrate AI skills with their own knowledge in specific area e.g. having AI experts combine with automotive developers on autonomous vehicles.

Recent Developments

Wipro & Google Cloud Launching Agentic AI Solutions

In August 2025, Wipro, an Indian IT giant has collaborated with Google Cloud to roll-out 200 AI agents across healthcare, banking, retail, manufacturing and IT. The initiative involves the application of domain knowledge and expertise of Wipro and the reliable cloud capabilities of Google to offer scalable industry specific agentic AI capabilities.

Manus Launches Broad Research Platform for Multi-Agent Collaboration

In July 2025, Singaporean (China-based) startup Manus AI launched a new platform, called Broad Research, will enable the deployment and operation of more than 100 general-purpose artificial intelligence agents in parallel. Each agent is independent, although together they work on projects that require many people, including product analysis and web scraping, report writing and creative content.

Key Market Drivers

1. Increase in Demand of Automation in Industries: The application of autonomous agent in industry is currently in increased demand, due to the fact that industry seeks to alleviate manual errors along the line of industry as well as enhance efficiency. For instance, in March 20205, Amazon warehouse robots manage their own inventory, which simplifies the process of work, and minimizes operating costs. This is likely to be enhanced further as other industries embrace AI agents in predictive maintenance and real time process optimization.
2. Increasing Automation of AI and Machine Learning Ability: The identified areas of the outlined capabilities of NLP, computer vision, and reinforcement learning are still developing, which confers greater flexibility and intelligence to the discussed agents. Therefore, GPT-based assistants created by OpenAI are able to independently handle a customer support-related task with a sufficient context. Moreover, the steady advancement of AI models is making it possible to leave more and more complex decision-making processes to the handling of agents humans only have to exercise the lightest of supervision.
3. Increasing Applications in Autonomous Vehicles & Robotics: The incorporation of the AI agents into mobility along with robotics is accelerating the market. The self-driving Waymo cars and warehouse robots by Boston Dynamics would be the two prominent ones. Moreover, the drones and AI-controlled robotized delivery systems extend the market by providing new approaches to logistics and transport.

Key Market Restraints

1. Minimal Implementation & Maintenance Costs: The high expenses of implementing complex autonomous systems and maintaining it paralyze the small and medium size businesses because the process of implementing the high end autonomous system from the autonomous systems will be a cost demanding venture. This can only work with bigger corporations that have enough to spend, which restricts the rate of penetration in the market especially in the SME sector.
2. Privacy and Security Problems of Data: Autonomous agents make use of sensitive data sets and all these sets can fall victim to leakage or manipulation. AI-driven financial advisor must ensure that it is in adherence to stringent laws pertaining to the security of data, in order to retain the confidence of the individuals.  In addition, misuse or compromise of data can seriously hurt brand reputation leading to regulatory fines which will once again deter adoption.

Table: Key Factors Impacting Global Autonomous AI and Autonomous Agents Market Analysis and Forecast (2025–2035)

Base CAGR: 45.2%

Regional Analysis

North America Dominates the Autonomous Agents and Autonomous AI Market

North America is estimated to hold the largest revenue share of around 40% in the autonomous AI and autonomous agents market in 2025, because of a powerful technological infrastructure, the high adoption rate in the sectors, and considerable investments in the major AI companies. The grazing of the market by the giants such as Google, Microsoft, IBM and Amazon, has fast-tracked the growth and introduction of the sophisticated autonomous agents across the domains of money, shipping, medicine, and even cars. For instance, Waymo, an autonomous driving company owned by Alphabet, has led the way in the autonomous vehicle industry.

By 2024, the Waymo ride-hailing service, Waymo One was available in several American cities, such as Phoenix, San Francisco, and Los Angeles. The service has recorded more than 250,000 self-driving taxi rides weekly proving the feasibility and practicality of autonomous agents in the city-driven transport.

Asia Pacific Rises as the Fastest Growing Region

The Asia Pacific region is expected to witness a rapid CAGR of around 50% during the forecast period, primarily due to a high level of digitalization, massive AI research, and government-funded automation programs. Countries such as China, Japan and South Korea are progressively investing in AI-led robotics, self-governing vehicles, and clever foundation assignments. For instance, Apollo autonomous driving program developed by Baidu in China presents the achievements of the Chinese region in terms of the scale of autonomous mobility solutions deployment in the region and indicates its fast-growing growth curve.

Country-level Analysis

Strong Innovation and Enterprise Adoption in the U.S.

The autonomous AI and autonomous agents market is dominated by the United States with its extensive technological infrastructure, extensive research and development potential, and the presence of worldwide artificial intelligence frontrunners, Google, IBM, Microsoft, and Amazon. Various industries such autonomous driving, defense, healthcare, and the finance industry in the country have witnessed wide usage of AI agents. An example of large-scale, real-world adoption of AI with regard to transport is the Waymo self-driving city-based ride-hailing service in places such as Phoenix.

China’s Government Support and Large-Scale Deployment

China is actively developing the autonomous AI which is also supported by well-developed government policies, large investments in AI research, and the rapid development of industrial automation. The largest technology companies such as Baidu, Alibaba, and Tencent are working on autonomous vehicle AI agents, smart city/manufacturing AI agents. As an example, the Baidu Apollo Go robotaxi service is available in several cities, emphasising the potential of China to scale the autonomous mobility option across the country. 

Emerging Hub for Autonomous AI Development in India

India is also taking its place as a major actor in the self-driving AI and autonomous agents industry, where more than 80% of the companies are currently working on developing the autonomous agents. This rather significant increase toward Agentic AI implies that more people become interested in the possibility to use autonomous agents to improve the business activities. Although India has adopted major progress in the development of AI, a few challenges still face the development of the basis of AI technologies, which will eventually constrain universal competitiveness in the global AI competition.

Segmental Analysis

By Component, Software Segment Dominated the Market with Highest Revenue Share of 50-60%.

The software component segment accounted for the highest revenue share of 50-60% in the autonomous AI and autonomous agents market. This supremacy is supported by the mainstreaming of AI algorithms, machine learner models, natural language processors, and application programming interfaces (APIs) that help autonomous agents carry out complex processes with little human interference. For instance, AI agents in Salesforce using Agentforce technology have processed 66% of inquiries made on the website and 84% of queries made by customers, which immensely improved operational efficiency and customer satisfaction.

Similarly, in April 2025, Nvidia targets has launched the the NeMo microservices platform by enabling the construction of autonomous AI agents through offering businesses marine flexible, open-weight AI systems that contain less reliance on proprietary systems. These developments indicate the paramount importance of software in developing the growth and operation of autonomous AI systems across the industries.

By Technology, Machine Learning Segment held the Majority Share of 35-40%

The majority of the market share of 35-40% of the autonomous AI and autonomous agents market was expected to acquire by machine learning segment. The possibility to use machine learning algorithms to analyze large data, identify patterns, and make predictive decisions about autonomous agents in various activities contributes to the growth of this segment. Banks, healthcare and retail institutions are seeing an increased trend in deploying machine learning agents to automate risk analysis, diagnosis and prognosis, inventory planning and personalized suggestions.

For instance, in BFSI sector, the modern credit scoring models supported by AI and machine learning have reached USD 2 million loan applications monthly replacing manual effort and increasing accuracy of approvals. Moreover, advances in reinforcement learning and neural network structures are advancing in making agents in autonomous systems more versatile and versatile, which makes machine learning the most critical technology in market growth.

Report Specifications:

Market Segmentation

• By Component
  • Services
  • Software
  • Hardware
• By Technology
  • NLP
  • Machine Learning
  • Computer Vision
  • Context Awareness
• By Deployment
  • Cloud
  • On-premises
• By End-Use Industry
  • Defense
  • BFSI
  •  IT/Telecom
  • Healthcare
  • Automotive & Transportation
  • Manufacturing
  • Retail & E-commerce
  • Energy & Utilities
  • Other End-use Industries

Key Questions Answered in the Report: