The future of technology is rapidly evolving, and one of the most significant developments is the emergence of autonomous systems, particularly self-healing AI agents. As of 2025, the global AI agents market is valued at approximately $7.92 billion and is forecasted to reach $236.03 billion by 2034, growing at a compound annual growth rate of 45.82%. This rapid growth is driven by the increasing need for highly personalized experiences and the integration of AI agents into business processes. In fact, according to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives.
With the ability to continuously learn and improve, self-healing AI agents are revolutionizing industries such as customer service, healthcare, and finance. These agents can analyze past data and experiences, adjusting to changing conditions by independently learning new tasks or improving current procedures. This enables enhanced decision-making skills and reduces the need for human oversight, particularly in complex and uncertain environments. As a result, companies across various sectors are adopting AI agents to optimize operations, lower costs, and improve customer engagement through personalized interactions.
Why Self-Healing AI Agents Matter
Self-healing AI agents are becoming vital tools in today’s digital landscape, driven by significant improvements in natural language processing applications. The increasing demand for personalized experiences, combined with the need for efficient and automated processes, is driving the growth of the AI agents market. North America remains the largest market for AI agents, holding around 40% of the global share, while the Asia-Pacific region is the fastest-growing, with a CAGR of 49.5%.
In this comprehensive guide, we will explore the trends and predictions for self-healing AI agents in 2025 and beyond. We will examine the tools and platforms that support the development and deployment of these agents, as well as real-world case studies and expert insights. By understanding the current market landscape and future trends, businesses and individuals can harness the potential of self-healing AI agents to drive innovation and stay ahead of the curve. The main sections of this guide will cover the current state of the AI agents market, the benefits and applications of self-healing AI agents, and the future prospects and challenges in this field.
Some of the key topics we will cover include:
- The current market size and growth projections for the AI agents market
- The benefits and applications of self-healing AI agents in various industries
- The tools and platforms that support the development and deployment of self-healing AI agents
- Real-world case studies and expert insights on the adoption and implementation of self-healing AI agents
By the end of this guide, readers will have a deep understanding of the trends and predictions for self-healing AI agents and be equipped with the knowledge to make informed decisions about the adoption and implementation of these agents in their own businesses or organizations. With the AI agents market poised for rapid growth, now is the time to explore the potential of self-healing AI agents and stay ahead of the curve in this exciting and rapidly evolving field.
Introduction to Self-Healing AI Agents
Introduction to self-healing AI agents is a topic of significant interest in the current technological landscape. Self-healing AI agents are equipped with self-learning algorithms, enabling them to continuously improve and optimize their performance by analyzing past data and experiences. According to a report by ResearchAndMarkets.com, artificial intelligence agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance, owing to significant improvements in natural language processing (NLP) applications.
These agents can adjust to changing conditions by independently learning new tasks or improving current procedures, enhancing decision-making skills and reducing the need for human oversight. This is particularly beneficial in complex and uncertain environments such as risk management, financial forecasting, and real-time customer service. For instance, companies like IBM and Google are developing AI-powered tools that can learn and adapt autonomously, providing features such as automated model training, real-time data analysis, and integration with various business systems.
Benefits of Self-Healing AI Agents
The benefits of self-healing AI agents are numerous. They can help companies optimize operations, lower costs, and improve customer engagement through personalized interactions. According to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives. This statistic highlights the importance of implementing self-healing AI agents in customer service and other industries.
Some of the key features of self-healing AI agents include their ability to learn from past data and experiences, adjust to changing conditions, and enhance decision-making skills. They can also reduce the need for human oversight, making them a valuable tool for companies looking to streamline their operations and improve efficiency. The following are some of the benefits of self-healing AI agents:
- Improved customer engagement through personalized interactions
- Enhanced decision-making skills and reduced need for human oversight
- Ability to learn from past data and experiences and adjust to changing conditions
- Reduced costs and improved operational efficiency
Companies like Amazon and Microsoft are already using self-healing AI agents to improve their customer service and operational efficiency. For example, Amazon’s virtual assistant, Alexa, is a self-healing AI agent that can learn and adapt to user behavior and preferences. Microsoft’s AI-powered chatbot, Zo, is another example of a self-healing AI agent that can provide personalized customer service and support.
Real-World Implementations of Self-Healing AI Agents
There are many real-world implementations of self-healing AI agents. For instance, the IBM Watson platform is a cloud-based AI platform that enables companies to build and deploy self-healing AI agents. The Google Cloud AI Platform is another example of a cloud-based platform that provides advanced machine learning and natural language processing capabilities for building self-healing AI agents.
The following table highlights some of the key features and benefits of self-healing AI agents:
| Feature | Benefit |
|---|---|
| Ability to learn from past data and experiences | Improved decision-making skills and reduced need for human oversight |
| Ability to adjust to changing conditions | Enhanced operational efficiency and reduced costs |
| Personalized customer interactions | Improved customer engagement and loyalty |
In conclusion, self-healing AI agents are a powerful tool for companies looking to improve their operational efficiency, reduce costs, and enhance customer engagement. With their ability to learn and adapt autonomously, self-healing AI agents are becoming an essential component of many industries, including customer service, healthcare, and finance. As the technology continues to evolve, we can expect to see even more innovative applications of self-healing AI agents in the future.
According to a report, the global AI agents market, which includes self-healing AI agents, is valued at approximately USD 7.92 billion and is forecasted to reach USD 236.03 billion by 2034, growing at a compound annual growth rate (CAGR) of 45.82%. This statistic highlights the significant growth potential of the self-healing AI agent market and the importance of investing in this technology.
Market Size and Growth Projections
The market for autonomous systems, particularly self-healing AI agents, is experiencing rapid growth. As of 2025, the global AI agents market is valued at approximately USD 7.92 billion and is forecasted to reach USD 236.03 billion by 2034, growing at a compound annual growth rate (CAGR) of 45.82%. Another source indicates that the market was valued at $3.7 billion in 2023 and is projected to reach $103.6 billion by 2032, with a CAGR of 44.9% from 2024 to 2032.
These growth projections are not surprising, given the increasing adoption of AI agents across various sectors, including customer service, healthcare, and finance. Companies like IBM, Google, and Amazon are investing heavily in AI research and development, driving innovation and growth in the market. According to a report by ResearchAndMarkets.com, artificial intelligence agents are becoming vital tools across multiple sectors, owing to significant improvements in natural language processing (NLP) applications.
Market Size and Growth Projections by Region
North America remains the largest market for AI agents, holding around 40% of the global share, driven by significant investments in AI research and development. The Asia-Pacific region is the fastest-growing, with a CAGR of 49.5%, fueled by rapid digital transformation in countries like China, India, and Japan. Companies across various sectors are adopting AI agents to optimize operations, lower costs, and improve customer engagement through personalized interactions.
The following table provides a summary of the market size and growth projections by region:
| Region | Market Size (2025) | CAGR (2025-2034) |
|---|---|---|
| North America | $3.2 billion | 43.1% |
| Asia-Pacific | $1.8 billion | 49.5% |
| Europe | $1.2 billion | 41.2% |
The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth. According to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives. This trend is expected to continue, with more companies adopting AI agents to improve customer engagement and reduce costs.
Key factors driving market growth include:
- Improvements in natural language processing (NLP) applications
- Increasing adoption of AI agents across various sectors
- Rapid digital transformation in emerging economies
- Growing demand for personalized customer experiences
For more information on the AI agents market, visit ResearchAndMarkets.com or MarketsandMarkets.com. These websites provide comprehensive reports and research studies on the AI agents market, including market size and growth projections, trends, and insights.
Technological Advancements
Technological advancements are a crucial aspect of the development and deployment of self-healing AI agents. As the global AI agents market continues to grow, with a forecasted value of $236.03 billion by 2034, it is essential to explore the latest advancements in this field. According to a report by ResearchAndMarkets.com, artificial intelligence agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance, owing to significant improvements in natural language processing (NLP) applications.
The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth. For instance, companies like IBM and Google Cloud are investing heavily in AI research and development, which is expected to drive the growth of the AI agents market. In fact, the Asia-Pacific region is the fastest-growing, with a compound annual growth rate (CAGR) of 49.5%, fueled by rapid digital transformation in countries like China, India, and Japan.
Self-Learning and Autonomous Capabilities
Self-healing AI agents, equipped with self-learning algorithms, can continuously improve and optimize their performance by analyzing past data and experiences. These agents can adjust to changing conditions by independently learning new tasks or improving current procedures, enhancing decision-making skills and reducing the need for human oversight. This is particularly beneficial in complex and uncertain environments such as risk management, financial forecasting, and real-time customer service.
For example, Samsung has developed an AI-powered customer service platform that uses self-learning algorithms to improve its performance over time. The platform can analyze customer interactions and adjust its responses accordingly, providing a more personalized experience for customers. Similarly, Bank of America has developed an AI-powered chatbot that can help customers with their financial queries, using self-learning algorithms to improve its performance over time.
Tools and Platforms
Several tools and platforms support the development and deployment of self-healing AI agents. For instance, platforms like IBM Watson and Google Cloud AI Platform offer advanced machine learning and natural language processing capabilities that enable AI agents to learn and adapt autonomously. These platforms provide features such as automated model training, real-time data analysis, and integration with various business systems, with pricing models that often start with a free tier and scale based on usage.
The following table provides a comparison of some of the popular tools and platforms used for developing and deploying self-healing AI agents:
| Tool/Platform | Features | Pricing |
|---|---|---|
| IBM Watson | Automated model training, real-time data analysis, integration with business systems | Custom pricing based on usage |
| Google Cloud AI Platform | Automated model training, real-time data analysis, integration with business systems | Custom pricing based on usage |
| Microsoft Azure Machine Learning | Automated model training, real-time data analysis, integration with business systems | Custom pricing based on usage |
In addition to these tools and platforms, there are several best practices that organizations can follow to develop and deploy self-healing AI agents effectively. Some of these best practices include:
- Defining clear goals and objectives for the AI agent
- Developing a robust training dataset
- Implementing a feedback loop to improve the AI agent’s performance over time
- Monitoring and evaluating the AI agent’s performance regularly
By following these best practices and using the right tools and platforms, organizations can develop and deploy self-healing AI agents that can improve their operations, reduce costs, and enhance customer engagement. According to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives, which highlights the importance of developing and deploying self-healing AI agents that can provide personalized experiences to customers.
Regional Breakdown and Industry Adoption
The regional breakdown of the AI agents market reveals a diverse landscape, with different regions exhibiting unique characteristics and growth patterns. As of 2025, North America remains the largest market for AI agents, holding around 40% of the global share, driven by significant investments in AI research and development. The Asia-Pacific region is the fastest-growing, with a compound annual growth rate (CAGR) of 49.5%, fueled by rapid digital transformation in countries like China, India, and Japan.
Companies across various sectors, including customer service, healthcare, and finance, are adopting AI agents to optimize operations, lower costs, and improve customer engagement through personalized interactions. For instance, IBM Watson and Google Cloud AI Platform are being used by companies like Accenture and Deloitte to develop and deploy self-healing AI agents. These platforms provide features such as automated model training, real-time data analysis, and integration with various business systems, with pricing models that often start with a free tier and scale based on usage.
Industry Adoption
The adoption of AI agents is not limited to a specific industry, as companies across various sectors are recognizing the benefits of self-healing AI agents. Some of the key industries that are driving the growth of the AI agents market include:
- Customer Service: Companies like Amazon and Microsoft are using AI agents to provide personalized customer support and improve customer engagement.
- Healthcare: Companies like UnitedHealth Group and Cerner Corporation are using AI agents to improve patient outcomes and reduce healthcare costs.
- Finance: Companies like JPMorgan Chase and Goldman Sachs are using AI agents to improve risk management and optimize financial operations.
According to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives. This trend is driving the growth of the AI agents market, as companies recognize the need to provide personalized and efficient customer support. The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth.
Regional Market Share
The regional market share of the AI agents market is an important indicator of the growth and adoption of self-healing AI agents. The following table provides an overview of the regional market share of the AI agents market:
| Region | Market Share | CAGR |
|---|---|---|
| North America | 40% | 45.8% |
| Asia-Pacific | 30% | 49.5% |
| Europe | 20% | 42.1% |
| Rest of the World | 10% | 40.5% |
For more information on the AI agents market, you can visit the website of ResearchAndMarkets.com, which provides an in-depth analysis of the market trends and growth prospects. The report by ResearchAndMarkets.com states that artificial intelligence agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance, owing to significant improvements in natural language processing (NLP) applications.
In conclusion, the regional breakdown and industry adoption of self-healing AI agents are critical factors that are driving the growth of the AI agents market. As companies across various sectors recognize the benefits of self-healing AI agents, the market is expected to continue growing, with the Asia-Pacific region being the fastest-growing region. For companies looking to adopt self-healing AI agents, it is essential to understand the regional market trends and industry adoption patterns to make informed decisions.
Tools and Platforms
The development and deployment of self-healing AI agents rely heavily on the use of various tools and platforms. These platforms provide the necessary infrastructure for AI agents to learn, adapt, and interact with their environment. According to a report by ResearchAndMarkets.com, artificial intelligence agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance, owing to significant improvements in natural language processing (NLP) applications.
The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth. For instance, platforms like IBM Watson and Google Cloud AI Platform offer advanced machine learning and natural language processing capabilities that enable AI agents to learn and adapt autonomously. These platforms provide features such as automated model training, real-time data analysis, and integration with various business systems, with pricing models that often start with a free tier and scale based on usage.
Comparison of Tools and Platforms
A comprehensive comparison of the various tools and platforms available for self-healing AI agents is essential to understand their strengths and weaknesses. The following table provides a summary of some of the most popular tools and platforms:
| Tool | Key Features | Pricing | Best For | Rating |
|---|---|---|---|---|
| IBM Watson | Automated model training, real-time data analysis, integration with business systems | Custom pricing based on usage | Large enterprises | 4.5/5 |
| Google Cloud AI Platform | Automated model training, real-time data analysis, integration with Google Cloud services | $3 per hour for training, $0.006 per hour for prediction | Small to medium-sized businesses | 4.3/5 |
| Microsoft Azure Machine Learning | Automated model training, real-time data analysis, integration with Microsoft Azure services | $1.19 per hour for training, $0.0017 per hour for prediction | Large enterprises | 4.4/5 |
The following is a detailed listing of each tool and platform, including their key features, pros, and cons:
1. IBM Watson
IBM Watson is a cloud-based AI platform that provides advanced machine learning and natural language processing capabilities. It is widely used in various industries, including healthcare, finance, and customer service.
Key Features:
- Automated model training
- Real-time data analysis
- Integration with business systems
- Natural language processing capabilities
Pros:
- Highly scalable and flexible
- Supports a wide range of data sources and formats
- Provides advanced security and governance features
Cons:
- Can be complex to use and require significant expertise
- May require significant investment in infrastructure and resources
- Can be expensive, especially for large-scale deployments
Best For:
IBM Watson is best suited for large enterprises that require advanced AI and machine learning capabilities to drive business innovation and transformation.
Pricing:
IBM Watson offers custom pricing based on usage, which can vary depending on the specific requirements of the business.
2. Google Cloud AI Platform
Google Cloud AI Platform is a managed platform that provides automated model training, real-time data analysis, and integration with Google Cloud services. It is widely used in various industries, including retail, finance, and healthcare.
Key Features:
- Automated model training
- Real-time data analysis
- Integration with Google Cloud services
- Support for a wide range of data sources and formats
Pros:
- Easy to use and requires minimal expertise
- Scalable and flexible, with support for a wide range of data sources and formats
- Provides advanced security and governance features
Cons:
- May require significant investment in infrastructure and resources
- Can be expensive, especially for large-scale deployments
- May have limited support for certain data sources and formats
Best For:
Google Cloud AI Platform is best suited for small to medium-sized businesses that require advanced AI and machine learning capabilities to drive business
Case Studies and Real-World Implementations
As we delve into the world of self-healing AI agents, it’s essential to explore real-world implementations and case studies that demonstrate their potential. Building on the tools discussed earlier, such as IBM Watson and Google Cloud AI Platform, companies are leveraging these platforms to develop and deploy AI agents that can learn and adapt autonomously. For instance, IBM Watson has been used by companies like BMW to develop a chatbot that can help customers with queries and provide personalized recommendations.
The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth. According to a study, 81% of customers choose AI-driven self-service options before engaging with human representatives. This trend is expected to continue, with the global AI agents market valued at approximately USD 7.92 billion in 2025 and forecasted to reach USD 236.03 billion by 2034, growing at a compound annual growth rate (CAGR) of 45.82%.
Case Studies and Real-World Implementations
Several companies have successfully implemented self-healing AI agents in various industries. For example, Domino’s Pizza has developed a chatbot that can take orders and provide customer support. The chatbot uses natural language processing (NLP) to understand customer queries and respond accordingly. Similarly, Bank of America has developed an AI-powered chatbot that can help customers with banking-related queries and provide personalized financial recommendations.
Another example is Netflix, which uses AI agents to provide personalized recommendations to its users. The AI agents analyze user behavior and preferences to provide recommendations that are tailored to their interests. This has led to a significant increase in user engagement and retention. According to a study, 75% of Netflix users rely on recommendations to discover new content.
- Customer Service: AI agents are being used in customer service to provide 24/7 support and help customers with queries and issues.
- Healthcare: AI agents are being used in healthcare to provide personalized recommendations and help patients with disease diagnosis and treatment.
- Finance: AI agents are being used in finance to provide personalized financial recommendations and help customers with investment and portfolio management.
In terms of regional adoption, North America remains the largest market for AI agents, holding around 40% of the global share. The Asia-Pacific region is the fastest-growing, with a CAGR of 49.5%, fueled by rapid digital transformation in countries like China, India, and Japan. Companies like Alibaba and Tencent are leading the charge in AI adoption in the region.
| Company | Industry | Implementation |
|---|---|---|
| Domino’s Pizza | Food Delivery | Chatbot for ordering and customer support |
| Bank of America | Banking | AI-powered chatbot for customer support |
| Netflix | Entertainment | AI-powered recommendations for users |
For more information on AI agents and their applications, you can visit the IBM Watson website or the Google Cloud AI Platform website. These resources provide valuable insights and tutorials on how to develop and deploy AI agents using these platforms.
In conclusion, self-healing AI agents are being increasingly adopted across various industries to provide personalized experiences and improve customer engagement. With the global AI agents market expected to grow significantly in the coming years, it’s essential for companies to leverage these agents to stay ahead of the competition. By exploring real-world implementations and case studies, companies can gain valuable insights into the potential of self-healing AI agents and develop strategies for successful adoption.
Expert Insights and Future Developments
As we delve into the future developments of self-healing AI agents, it’s essential to consider the expert insights and market trends that are shaping the industry. According to a report by ResearchAndMarkets.com, artificial intelligence agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance, owing to significant improvements in natural language processing (NLP) applications. The increasing need for highly personalized experiences and the integration of AI agents into business processes are driving market growth.
The market size and growth projections of the AI agents market, which includes self-healing AI agents, are staggering. As of 2025, the global AI agents market is valued at approximately USD 7.92 billion and is forecasted to reach USD 236.03 billion by 2034, growing at a compound annual growth rate (CAGR) of 45.82%. Another source indicates that the market was valued at $3.7 billion in 2023 and is projected to reach $103.6 billion by 2032, with a CAGR of 44.9% from 2024 to 2032.
Self-Learning and Autonomous Capabilities
A study found that 81% of customers choose AI-driven self-service options before engaging with human representatives. This highlights the importance of self-healing AI agents in providing personalized and efficient customer service. Companies such as Amazon, Microsoft, and IBM are already leveraging self-healing AI agents to improve their customer service and overall business operations.
Regional Breakdown and Industry Adoption
North America remains the largest market for AI agents, holding around 40% of the global share, driven by significant investments in AI research and development. The Asia-Pacific region is the fastest-growing, with a CAGR of 49.5%, fueled by rapid digital transformation in countries like China, India, and Japan. Companies across various sectors, including customer service, healthcare, and finance, are adopting AI agents to optimize operations, lower costs, and improve customer engagement through personalized interactions.
For instance, IBM is using its Watson platform to provide self-healing AI agents for various industries. The platform offers advanced machine learning and natural language processing capabilities that enable AI agents to learn and adapt autonomously. Similarly, Google Cloud AI Platform provides features such as automated model training, real-time data analysis, and integration with various business systems, with pricing models that often start with a free tier and scale based on usage.
Tools and Platforms
Several tools and platforms support the development and deployment of self-healing AI agents. These platforms provide features such as automated model training, real-time data analysis, and integration with various business systems. Some of the popular tools and platforms include:
- IBM Watson
- Google Cloud AI Platform
- Microsoft Azure Machine Learning
- Amazon SageMaker
These platforms have different pricing models, but most of them offer a free tier and scale based on usage. For example, IBM Watson offers a free tier with limited features, while Google Cloud AI Platform offers a free tier with unlimited features for a limited time.
The following table provides a comparison of the pricing models of these platforms:
| Platform | Pricing Model | Free Tier |
|---|---|---|
| IBM Watson | Pay-as-you-go | Limited features |
| Google Cloud AI Platform | Pay-as-you-go | Unlimited features for limited time |
| Microsoft Azure Machine Learning | Pay-as-you-go | Limited features |
| Amazon SageMaker | Pay-as-you-go | Limited features |
In conclusion, self-healing AI agents are becoming increasingly important in various industries, and their market size and growth projections are staggering. The self-learning and autonomous capabilities of these agents make them highly valuable in complex and uncertain environments. The regional breakdown and industry adoption of AI agents show that North America is the largest market, while the Asia-Pacific region is the fastest-growing. Several tools and platforms support the development and deployment of self-healing AI agents, and their pricing models vary.
Expert Insights suggest that the integration of AI agents into business processes is driving market growth. The importance of self-healing AI agents in providing personalized and efficient customer service cannot be overstated. As the market continues to grow, we can expect to see more companies adopting self-healing AI agents to optimize their operations and improve customer engagement.
Conclusion
Conclusion: Embracing the Future of Autonomous Systems
The future of autonomous systems is rapidly unfolding, with self-healing AI agents at the forefront of this revolution. As we’ve explored in this blog post, the market for AI agents is experiencing exponential growth, with projected values reaching $236.03 billion by 2034, growing at a compound annual growth rate of 45.82%. This growth is fueled by the increasing adoption of self-healing AI agents across various industries, including customer service, healthcare, and finance.
One of the key benefits of self-healing AI agents is their ability to continuously improve and optimize their performance through self-learning algorithms. This enables them to adjust to changing conditions, make informed decisions, and reduce the need for human oversight. As ResearchAndMarkets.com notes, artificial intelligence agents are becoming vital tools across multiple sectors, driven by significant improvements in natural language processing applications.
To stay ahead of the curve, businesses and individuals must be aware of the latest trends and insights in the field. Some key takeaways from our research include:
- The Asia-Pacific region is the fastest-growing market for AI agents, with a CAGR of 49.5%.
- Companies like IBM and Google are offering advanced machine learning and natural language processing capabilities to support the development and deployment of self-healing AI agents.
- 81% of customers prefer AI-driven self-service options before engaging with human representatives.
As we look to the future, it’s clear that self-healing AI agents will play an increasingly important role in shaping the autonomous systems landscape. To learn more about the latest developments and trends in this field, visit our page at www.web.superagi.com. By staying informed and embracing the potential of self-healing AI agents, we can unlock new opportunities for growth, innovation, and success.
So, what’s the next step? For businesses and individuals looking to leverage the power of self-healing AI agents, we recommend:
- Staying up-to-date with the latest research and trends in the field.
- Exploring the various tools and platforms available to support the development and deployment of self-healing AI agents.
- Identifying areas where self-healing AI agents can add value and improve existing processes.
By taking these steps, we can unlock the full potential of self-healing AI agents and create a brighter, more autonomous future for all. The time to act is now – join the revolution and discover the limitless possibilities of self-healing AI agents.
