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Artificial intelligence agents are programs that can receive information, perform analysis, and independently solve problems to achieve specific goals.
Unlike regular programs that follow predetermined rules, AI agents make decisions using logic and rational thinking.
Advanced and relatively autonomous agents are widely used in various fields: from customer service in online chats to managing complex corporate systems.
In call centers, they help serve customers by analyzing their requests and offering solutions. And only when the AI decides that more complex intervention is required, the request is transferred to the operator.
AI agents can also be used to analyze large amounts of data, make predictions, and improve marketing strategies.
One of the promising projects in this area is Google Project Astra, which will be launched in 2025. Its goal is to create multimodal AI agents that can perceive the environment in real time and help people with everyday tasks, such as shopping or planning trips.
AI agents are already actively used in business. For example, KPMG uses them to automate routine audit processes, which frees up employees' time for more important tasks.
LinkedIn has implemented a Hiring Assistant tool that automates up to 80% of routine recruiting tasks, allowing recruiters to focus on the strategic aspect of hiring.
In supply chains, AI agents from GEP help manage risks, such as analyzing weather forecasts and planning the closure of seaports in logistics chains.
However, despite the obvious advantages, the implementation of AI agents is associated with a number of risks.
One of the main ones is the threat of data leaks, since such systems can process large volumes of sensitive information. Attackers may try to capture AI agents and use them for their own purposes.
To minimize risks, organizations need to implement control mechanisms. This includes creating maps of AI agent interactions, tracking their actions, and integrating them with information security systems.
It is also important to develop systems to detect anomalies in the actions of AI agents so that in case of incorrect transactions or suspicious actions, the system can be quickly stopped and analyzed.
In addition, even the most advanced AI systems need constant human monitoring, especially when they make decisions that may affect the security or privacy of data.
As such, AI agents are a powerful tool for automation and business efficiency that will soon transform the service and business sector. However, it is essential to implement such technologies taking into account the risks to ensure the long-term effectiveness and reliability of AI.
(the text translation was done automatically)
Unlike regular programs that follow predetermined rules, AI agents make decisions using logic and rational thinking.
Advanced and relatively autonomous agents are widely used in various fields: from customer service in online chats to managing complex corporate systems.
In call centers, they help serve customers by analyzing their requests and offering solutions. And only when the AI decides that more complex intervention is required, the request is transferred to the operator.
AI agents can also be used to analyze large amounts of data, make predictions, and improve marketing strategies.
One of the promising projects in this area is Google Project Astra, which will be launched in 2025. Its goal is to create multimodal AI agents that can perceive the environment in real time and help people with everyday tasks, such as shopping or planning trips.
AI agents are already actively used in business. For example, KPMG uses them to automate routine audit processes, which frees up employees' time for more important tasks.
LinkedIn has implemented a Hiring Assistant tool that automates up to 80% of routine recruiting tasks, allowing recruiters to focus on the strategic aspect of hiring.
In supply chains, AI agents from GEP help manage risks, such as analyzing weather forecasts and planning the closure of seaports in logistics chains.
However, despite the obvious advantages, the implementation of AI agents is associated with a number of risks.
One of the main ones is the threat of data leaks, since such systems can process large volumes of sensitive information. Attackers may try to capture AI agents and use them for their own purposes.
To minimize risks, organizations need to implement control mechanisms. This includes creating maps of AI agent interactions, tracking their actions, and integrating them with information security systems.
It is also important to develop systems to detect anomalies in the actions of AI agents so that in case of incorrect transactions or suspicious actions, the system can be quickly stopped and analyzed.
In addition, even the most advanced AI systems need constant human monitoring, especially when they make decisions that may affect the security or privacy of data.
As such, AI agents are a powerful tool for automation and business efficiency that will soon transform the service and business sector. However, it is essential to implement such technologies taking into account the risks to ensure the long-term effectiveness and reliability of AI.
(the text translation was done automatically)
