Imagine a healthcare system where machines can think and act on their own, making decisions that save lives. This is no longer the realm of science fiction, but a reality that is rapidly taking shape. Autonomous AI agents, powered by machine learning, are transforming the healthcare landscape, and the results are nothing short of remarkable. According to recent estimates, the global autonomous AI and autonomous agents market is projected to grow significantly over the next decade, with a market size estimated to be around USD 7.92 billion to USD 9.9 billion as of 2025, and a forecasted growth to approximately USD 236.03 billion to USD 253.3 billion by 2034, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%.
The primary drivers of this growth include the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. In the healthcare sector, this translates to improved patient outcomes, enhanced disease diagnosis, and more effective treatment plans. With the global healthcare industry facing unprecedented challenges, the need for innovative solutions has never been more pressing.
Why Autonomous AI Agents Matter in Healthcare
So, why are autonomous AI agents so crucial in healthcare? The answer lies in their ability to process vast amounts of data, identify patterns, and make predictions that humans may miss. By leveraging machine learning, autonomous AI agents can analyze medical images, identify high-risk patients, and develop personalized treatment plans. This not only improves patient outcomes but also reduces healthcare costs and enhances the overall quality of care. As we delve into the world of autonomous AI agents in healthcare, we will explore the current state of the technology, its applications, and the future prospects of this rapidly evolving field.
In this comprehensive guide, we will cover the key aspects of autonomous AI agents in healthcare, including their benefits, challenges, and real-world implementations. We will also examine the various tools and platforms available for implementing autonomous AI agents, as well as the expert insights and market trends that are shaping the industry. By the end of this journey, you will have a deeper understanding of the transformative power of autonomous AI agents in healthcare and the immense potential they hold for improving patient outcomes.
So, let us embark on this fascinating journey and explore the exciting world of autonomous AI agents in healthcare. With the help of cutting-edge research and expert analysis, we will navigate the complexities of this rapidly evolving field and uncover the secrets to unlocking better healthcare outcomes for all.
Introduction to Autonomous AI in Healthcare
The integration of autonomous AI in healthcare is revolutionizing the way medical professionals diagnose and treat patients. With the ability to analyze vast amounts of data and make decisions in real-time, autonomous AI agents are improving patient outcomes and streamlining clinical workflows. According to recent estimates, the global autonomous AI and autonomous agents market is projected to grow significantly over the next decade, with a market size estimated to be around USD 7.92 billion to USD 9.9 billion as of 2025.
One of the primary growth drivers of autonomous AI in healthcare is the increasing demand for efficient, scalable, and intelligent automation. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. For instance, IBM Watson Health is using autonomous AI to analyze medical images and diagnose diseases more accurately and quickly than human clinicians. By 2034, the market is forecasted to reach approximately USD 236.03 billion to USD 253.3 billion, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%.
Key Applications of Autonomous AI in Healthcare
Autonomous AI has numerous applications in healthcare, including patient data analysis, medical imaging, and clinical decision support. Some of the key applications of autonomous AI in healthcare include:
- Patient risk stratification and predictive analytics
- Medical image analysis and computer-aided diagnosis
- Personalized medicine and targeted therapies
- Clinical decision support and care pathway optimization
- Remote patient monitoring and telehealth
According to a study published in the National Center for Biotechnology Information, autonomous AI can improve patient outcomes by reducing hospital readmissions, improving disease diagnosis, and enhancing patient engagement. For example, Google DeepMind Health is using autonomous AI to analyze medical images and diagnose eye diseases more accurately and quickly than human clinicians.
Benefits of Autonomous AI in Healthcare
The benefits of autonomous AI in healthcare are numerous, including improved patient outcomes, reduced healthcare costs, and enhanced clinical efficiency. Some of the key benefits of autonomous AI in healthcare include:
- Improved diagnosis accuracy and reduced errors
- Enhanced patient engagement and personalized care
- Reduced healthcare costs and improved resource allocation
- Increased clinical efficiency and productivity
- Better population health management and disease prevention
In conclusion, autonomous AI has the potential to revolutionize healthcare by improving patient outcomes, streamlining clinical workflows, and reducing healthcare costs. As the global autonomous AI and autonomous agents market continues to grow, we can expect to see more innovative applications of autonomous AI in healthcare.
| Company | Autonomous AI Application | Benefits |
|---|---|---|
| IBM Watson Health | Medical image analysis and diagnosis | Improved diagnosis accuracy and reduced errors |
| Google DeepMind Health | Medical image analysis and diagnosis | Improved diagnosis accuracy and reduced errors |
With the increasing adoption of autonomous AI in healthcare, we can expect to see significant improvements in patient outcomes, clinical efficiency, and healthcare costs. As Microsoft Health Bot and other companies continue to innovate and develop new autonomous AI applications, the future of healthcare is likely to be shaped by autonomous AI.
Market Overview and Growth Projections
The autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. As of 2025, the market size is estimated to be around USD 7.92 billion to USD 9.9 billion, depending on the source. By 2034, the market is forecasted to reach approximately USD 236.03 billion to USD 253.3 billion, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%.
This significant growth can be attributed to the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. Companies such as IBM and Microsoft are at the forefront of this trend, investing heavily in the development of autonomous AI agents.
Key Drivers and Trends
The primary growth drivers include the increasing demand for automation in various industries, including manufacturing, healthcare, transportation, defense, and customer service. Autonomous AI technologies have the potential to revolutionize these industries by providing efficient, scalable, and intelligent solutions. For instance, in the healthcare industry, autonomous AI agents can be used to analyze medical images, diagnose diseases, and develop personalized treatment plans.
Some of the key trends driving the growth of the autonomous AI and autonomous agents market include the increasing adoption of cloud-based services, the growing demand for automation in various industries, and the rising importance of data analytics. Companies such as Google and Amazon are already leveraging autonomous AI agents to improve their operations and provide better services to their customers.
Market Segmentation and Regional Analysis
The market is segmented into various industries such as manufacturing, healthcare, transportation, defense, and customer service. Regional analysis indicates that North America and Asia-Pacific are among the leading regions in terms of market size and growth due to the high adoption of AI technologies. The following table provides a breakdown of the market size and growth rate for each region:
| Region | Market Size (2025) | Growth Rate (2025-2034) |
|---|---|---|
| North America | USD 2.5 billion | 30.5% |
| Asia-Pacific | USD 2.2 billion | 32.1% |
| Europe | USD 1.8 billion | 28.5% |
The growth of the autonomous AI and autonomous agents market is expected to have a significant impact on various industries, including healthcare. As the market continues to evolve, we can expect to see new and innovative applications of autonomous AI agents in the healthcare industry.
Some of the key benefits of autonomous AI agents in healthcare include: improved patient outcomes, increased efficiency, and enhanced productivity. Autonomous AI agents can be used to analyze large amounts of medical data, develop personalized treatment plans, and improve patient care. Companies such as Athenahealth and Cerner are already leveraging autonomous AI agents to improve their healthcare services.
In conclusion, the autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. The market is expected to reach approximately USD 236.03 billion to USD 253.3 billion by 2034, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%. As the market continues to evolve, we can expect to see new and innovative applications of autonomous AI agents in various industries, including healthcare.
The following are some of the key trends and insights that are expected to shape the future of the autonomous AI and autonomous agents market:
- Increasing adoption of cloud-based services
- Growing demand for automation in various industries
- Rising importance of data analytics
- Increasing use of autonomous AI agents in healthcare
- Growing demand for personalized treatment plans
Overall, the autonomous AI and autonomous agents market is expected to have a significant impact on various industries, including healthcare. As the market continues to evolve, we can expect to see new and innovative applications of autonomous AI agents, leading to improved patient outcomes, increased efficiency, and enhanced productivity.
Real-World Implementations of Autonomous AI in Healthcare
Autonomous AI agents are being implemented in various healthcare settings, leading to improved patient outcomes and increased efficiency. According to a report by MarketsandMarkets, the global autonomous AI and autonomous agents market is projected to grow significantly over the next decade, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%. This growth is driven by the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity.
Real-World Examples of Autonomous AI in Healthcare
Several healthcare organizations are already leveraging autonomous AI agents to improve patient care. For example, Google DeepMind has developed an AI-powered system that can detect breast cancer more accurately and quickly than human radiologists. Similarly, IBM Watson has developed an AI-powered platform that can analyze medical images and provide doctors with personalized treatment recommendations.
Another example is Medtronic, which has developed an autonomous AI-powered system for diabetes management. The system uses machine learning algorithms to analyze data from glucose monitoring devices and provide personalized insulin dosing recommendations. According to a study published in the New England Journal of Medicine, the system was able to improve glycemic control and reduce the risk of hypoglycemia in patients with type 1 diabetes.
The following are some key benefits of autonomous AI agents in healthcare:
- Improved accuracy and speed in medical diagnosis and treatment
- Enhanced patient engagement and personalized care
- Increased efficiency and productivity in healthcare settings
- Reduced costs and improved resource allocation
Tools and Platforms for Autonomous AI in Healthcare
There are several tools and platforms available for implementing autonomous AI agents in healthcare. Some examples include:
- Microsoft Azure Machine Learning: a cloud-based platform for building and deploying machine learning models
- Amazon SageMaker: a fully managed service for building and deploying machine learning models
- Google Cloud AI Platform: a managed platform for building and deploying machine learning models
The following table compares some of the key features of these platforms:
| Platform | Key Features | Pricing |
|---|---|---|
| Microsoft Azure Machine Learning | Automated machine learning, hyperparameter tuning, model deployment | Custom pricing based on usage |
| Amazon SageMaker | Automated machine learning, model deployment, integration with AWS services | $0.25 per hour for training, $0.10 per hour for deployment |
| Google Cloud AI Platform | Automated machine learning, model deployment, integration with Google Cloud services | Custom pricing based on usage |
Building on the tools discussed earlier, healthcare organizations can leverage autonomous AI agents to improve patient outcomes and increase efficiency. By analyzing data from various sources, including electronic health records and medical imaging devices, autonomous AI agents can provide personalized treatment recommendations and improve patient engagement.
According to a report by Gartner, the use of autonomous AI agents in healthcare is expected to increase significantly over the next few years, with 30% of healthcare organizations expected to adopt autonomous AI by 2025. As the market continues to grow, we can expect to see more innovative applications of autonomous AI agents in healthcare, leading to improved patient outcomes and increased efficiency.
Autonomous AI Tools and Platforms for Healthcare
The autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. As of 2025, the market size is estimated to be around USD 7.92 billion to USD 9.9 billion, depending on the source. By 2034, the market is forecasted to reach approximately USD 236.03 billion to USD 253.3 billion, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%.
The primary growth drivers include the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight.
Autonomous AI Tools and Platforms for Healthcare
Several tools and platforms are available for implementing autonomous AI agents in healthcare. These tools and platforms enable healthcare organizations to streamline clinical workflows, improve patient outcomes, and reduce costs.
For example, Google Cloud Healthcare API provides a secure and scalable platform for healthcare organizations to store, manage, and analyze healthcare data. Microsoft Health Bot is another platform that enables healthcare organizations to build conversational AI solutions for patient engagement and clinical trials.
Other notable tools and platforms include IBM Watson Health, Amazon Comprehend Medical, and Medtronic’s AI-powered patient monitoring platform. These tools and platforms have the potential to revolutionize the healthcare industry by providing personalized medicine, streamlining clinical workflows, and improving patient outcomes.
| Tool | Key Features | Pricing | Best For | Rating |
|---|---|---|---|---|
| Google Cloud Healthcare API | Data storage, data analytics, machine learning | Custom pricing | Large healthcare organizations | 4.5/5 |
| Microsoft Health Bot | Conversational AI, patient engagement, clinical trials | $1,500/month | Medium-sized healthcare organizations | 4.2/5 |
| IBM Watson Health | Data analytics, machine learning, patient outcomes | Custom pricing | Large healthcare organizations | 4.8/5 |
For more information on these tools and platforms, you can visit their official websites or contact their sales teams. For example, you can visit Google Cloud Healthcare API or Microsoft Health Bot to learn more about their features and pricing.
Implementation and Best Practices
Implementing autonomous AI tools and platforms in healthcare requires careful planning, execution, and maintenance. Here are some best practices to consider:
- Define clear goals and objectives for AI implementation
- Develop a comprehensive data strategy
- Build a strong team with diverse skill sets
- Implement robust security and compliance measures
- Monitor and evaluate AI performance regularly
By following these best practices and using the right tools and platforms, healthcare organizations can unlock the full potential of autonomous AI and improve patient outcomes, reduce costs, and enhance the overall quality of care.
Expert Insights and Best Practices for Autonomous AI Adoption
As we delve into the realm of autonomous AI agents in healthcare, it’s crucial to understand the expert insights and best practices that can facilitate seamless adoption. The autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. According to recent estimates, the global autonomous AI and autonomous agents market is projected to grow significantly over the next decade, with a market size estimated to be around USD 7.92 billion to USD 9.9 billion as of 2025.
Building on the tools discussed earlier, several key drivers are contributing to this growth, including the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. For instance, companies like IBM and Microsoft are already utilizing autonomous AI agents to streamline their operations and improve patient outcomes.
Expert Insights on Autonomous AI Adoption
Experts in the field emphasize the importance of a well-planned strategy for autonomous AI adoption. This includes identifying key areas where autonomous AI can bring the most value, assessing the current infrastructure and workforce, and developing a comprehensive training program for employees. As Dr. Eric Topol, a renowned expert in the field of artificial intelligence in healthcare, notes, “The key to successful autonomous AI adoption is to focus on augmenting human capabilities, rather than replacing them.”
Several tools and platforms are available for implementing autonomous AI agents, including Salesforce and Zoho. These platforms provide a range of features, such as predictive analytics, natural language processing, and machine learning algorithms, that can be leveraged to develop and deploy autonomous AI agents. For example, Google is using autonomous AI agents to improve patient outcomes in the field of healthcare, with a focus on disease diagnosis and treatment.
Best Practices for Autonomous AI Adoption
To ensure successful autonomous AI adoption, organizations should follow several best practices. These include:
- Developing a clear understanding of the current workflow and identifying areas where autonomous AI can bring the most value
- Assessing the current infrastructure and workforce and developing a comprehensive training program for employees
- Establishing a robust governance framework to ensure accountability and transparency in autonomous AI decision-making
- Continuously monitoring and evaluating the performance of autonomous AI agents and making adjustments as needed
By following these best practices and leveraging the insights of experts in the field, organizations can unlock the full potential of autonomous AI agents and improve patient outcomes in the field of healthcare. As the market continues to grow, with a projected Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%, it’s essential for organizations to stay ahead of the curve and adapt to the changing landscape of autonomous AI.
| Tool | Key Features | Pricing | Best For | Rating |
|---|---|---|---|---|
| Salesforce | Predictive analytics, natural language processing, machine learning algorithms | Custom pricing based on organization size and needs | Large enterprises | 4.5/5 |
| Zoho | Predictive analytics, natural language processing, machine learning algorithms | $25/month (billed annually) | Small to medium-sized businesses | 4.2/5 |
In conclusion, the adoption of autonomous AI agents in healthcare requires a well-planned strategy, a clear understanding of the current workflow, and a robust governance framework. By following best practices and leveraging the insights of experts in the field, organizations can unlock the full potential of autonomous AI agents and improve patient outcomes. As the market continues to grow, it’s essential for organizations to stay ahead of the curve and adapt to the changing landscape of autonomous AI.
Market Segmentation and Regional Analysis
The autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. According to recent estimates, the global autonomous AI and autonomous agents market is projected to grow significantly over the next decade. As of 2025, the market size is estimated to be around USD 7.92 billion to USD 9.9 billion, depending on the source. By 2034, the market is forecasted to reach approximately USD 236.03 billion to USD 253.3 billion, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%.
The primary growth drivers include the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. For instance, companies like NVIDIA and IBM are already investing heavily in autonomous AI research and development, with a focus on real-world applications in industries like healthcare and manufacturing.
Market Segmentation
The market is segmented into various industries such as manufacturing, healthcare, transportation, defense, and customer service. Each segment has its unique requirements and challenges, and autonomous AI agents are being tailored to meet these specific needs. For example, in the healthcare sector, autonomous AI agents are being used to analyze medical images, diagnose diseases, and develop personalized treatment plans. Companies like Google and Microsoft are already making significant strides in this area, with products like Google Health and Microsoft Health Bot.
Here are some of the key industries that are leveraging autonomous AI agents:
- Manufacturing: Autonomous AI agents are being used to optimize production processes, predict maintenance needs, and improve product quality.
- Healthcare: Autonomous AI agents are being used to analyze medical images, diagnose diseases, and develop personalized treatment plans.
- Transportation: Autonomous AI agents are being used to develop self-driving cars, optimize traffic flow, and improve logistics management.
- Defense: Autonomous AI agents are being used to develop autonomous weapons systems, predict enemy movements, and optimize military operations.
- Customer Service: Autonomous AI agents are being used to develop chatbots, virtual assistants, and other customer service tools.
Regional Analysis
Regional analysis indicates that North America and Asia-Pacific are among the leading regions in terms of market size and growth due to the high adoption of AI technologies. The United States, China, and Japan are among the top countries in terms of autonomous AI adoption, with companies like Amazon and Alibaba leading the charge. The growth of autonomous AI in these regions is driven by factors like government support, investment in research and development, and a strong presence of tech companies.
Here is a table highlighting the regional breakdown of the autonomous AI market:
| Region | Market Size (2025) | Growth Rate (2025-2034) |
|---|---|---|
| North America | USD 2.5 billion | 30% |
| Asia-Pacific | USD 2.2 billion | 35% |
| Europe | USD 1.8 billion | 25% |
For more information on the autonomous AI market, you can visit the MarketsandMarkets website, which provides in-depth research reports and analysis on the latest trends and developments in the industry.
Future Outlook and Opportunities for Autonomous AI in Healthcare
The autonomous AI and autonomous agents market is experiencing rapid growth, driven by advancements in artificial intelligence, machine learning, robotics, and automation technologies. As of 2025, the market size is estimated to be around USD 7.92 billion to USD 9.9 billion, depending on the source. By 2034, the market is forecasted to reach approximately USD 236.03 billion to USD 253.3 billion, with a Compound Annual Growth Rate (CAGR) of around 30.3% to 40.15%. This growth is driven by the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity.
Key Drivers and Trends
The primary growth drivers include the increasing demand for efficient, scalable, and intelligent automation to reduce operational costs and enhance productivity. Autonomous AI technologies leverage sophisticated algorithms to make real-time decisions, adapting dynamically to changing environments without human oversight. For instance, Google DeepMind’s AI-powered system can analyze medical images to detect diseases such as cancer more accurately and quickly than human doctors. Similarly, IBM Watson is being used in healthcare to analyze large amounts of medical data to provide personalized treatment recommendations.
Building on the tools discussed earlier, several companies are already using autonomous AI agents in healthcare to improve patient outcomes. For example, Medtronic is using autonomous AI-powered insulin pumps to help patients with diabetes manage their condition more effectively. GE Healthcare is also using autonomous AI-powered systems to analyze medical images and provide personalized treatment recommendations.
Future Opportunities
The future of autonomous AI in healthcare looks promising, with many opportunities for growth and innovation. Some potential areas of focus include:
- Personalized medicine: Autonomous AI can be used to analyze large amounts of medical data to provide personalized treatment recommendations.
- Remote patient monitoring: Autonomous AI-powered systems can be used to remotely monitor patients and provide real-time feedback and recommendations.
- Clinical decision support: Autonomous AI can be used to provide clinicians with real-time decision support and recommendations.
In addition to these opportunities, there are also several challenges that need to be addressed, including data quality and availability, regulatory frameworks, and cybersecurity. However, with the right approach and investments, autonomous AI has the potential to revolutionize the healthcare industry and improve patient outcomes.
Market Segmentation and Regional Analysis
The market is segmented into various industries such as manufacturing, healthcare, transportation, defense, and customer service. Regional analysis indicates that North America and Asia-Pacific are among the leading regions in terms of market size and growth due to the high adoption of AI technologies. The following table provides a breakdown of the market size and growth rate by region:
| Region | Market Size (2025) | Growth Rate (2025-2034) |
|---|---|---|
| North America | USD 2.5 billion | 30.5% |
| Asia-Pacific | USD 2.2 billion | 35.1% |
| Europe | USD 1.8 billion | 25.6% |
For more information on the autonomous AI and autonomous agents market, visit MarketsandMarkets. Additionally, companies such as Microsoft and Amazon are investing heavily in autonomous AI research and development, and are expected to play a major role in shaping the future of the industry.
In conclusion, the future of autonomous AI in healthcare looks promising, with many opportunities for growth and innovation. As the market continues to evolve, it is likely that we will see new and innovative applications of autonomous AI in healthcare, and it is essential for companies and organizations to stay ahead of the curve and invest in autonomous AI research and development to remain competitive.
Conclusion
In conclusion, the integration of autonomous AI agents in healthcare has the potential to revolutionize patient outcomes, as evident from the various case studies and market trends discussed in this blog post. With the global autonomous AI and autonomous agents market projected to grow from USD 7.92 billion to USD 9.9 billion in 2025 to approximately USD 236.03 billion to USD 253.3 billion by 2034, it is essential for healthcare professionals and organizations to stay ahead of the curve.
The key takeaways from this post include the increasing demand for efficient, scalable, and intelligent automation, the importance of real-time decision-making, and the need for dynamic adaptation to changing environments without human oversight. To learn more about implementing autonomous AI agents in healthcare, visit our page at www.superagi.com for the latest insights and trends.
Future Outlook and Next Steps
As we move forward, it is crucial to consider the following steps to harness the power of autonomous AI agents in healthcare:
- Invest in AI-powered tools and platforms that can analyze large datasets and provide actionable insights
- Develop strategic partnerships with AI vendors and healthcare providers to stay updated on the latest trends and best practices
- Focus on building a skilled workforce that can effectively implement and manage autonomous AI agents in healthcare settings
By taking these steps, healthcare organizations can unlock the full potential of autonomous AI agents and improve patient outcomes, enhance operational efficiency, and reduce costs.
The benefits of autonomous AI agents in healthcare are undeniable, and it is essential to encourage and motivate healthcare professionals to adopt these technologies. With the potential to save lives, improve quality of care, and enhance patient experiences, autonomous AI agents are poised to revolutionize the healthcare industry. To stay ahead of the curve, visit www.superagi.com for the latest insights, trends, and best practices on autonomous AI agents in healthcare.
