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Google’s latest white paper defines an AI Agent as a large model application that can observe the world, utilize tools, and take actions to achieve specific goals. It not only possesses autonomy but can also actively infer the next action strategy to achieve the final goal. In simple terms, an AI Agent is an intelligent system capable of working independently, with the following main characteristics:
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Autonomy: An AI Agent can operate independently without direct human intervention, making decisions and taking actions based on preset goals and tasks.
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Perception: Through sensors and other devices, an AI Agent can perceive information about the surrounding environment, such as traffic conditions and user inputs.
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Decision-making: Based on the perceived information, an AI Agent can use built-in algorithms or machine learning models to make decisions and determine the next action plan.
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Action: According to the decision results, an AI Agent can perform corresponding actions, such as controlling a car to accelerate, decelerate, turn, or answer user questions.
Therefore, some believe that AI Agents will significantly impact workers, as companies like Microsoft and Amazon have recently announced layoff plans, resembling a significant overhaul. It seems a race between humans and machines is about to begin; in the future, those whose performance levels are not as good as AI Agents may be eliminated. However, our understanding of the impact of AI Agents is more long-term. The rise of AI Agents is not simply about replacing human jobs, but will profoundly change work processes and business models. Everyone must rethink the essence of work tasks and reorganize job roles; only companies and individuals who can adapt to this process will become the winners of the future.
AI Agents demonstrate broad application potential in various fields, including but not limited to:
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Autonomous Driving: Autonomous vehicles are a typical application of AI Agents. They can perceive surrounding traffic conditions, road information, etc., and formulate driving strategies based on this information to achieve autonomous driving.
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Smart Homes: Smart home assistants are also significant applications of AI Agents. They can understand user voice commands and control various smart devices in the home (such as lighting, temperature, audio, etc.) to provide personalized services.
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Customer Service: AI chatbots, as a form of AI Agent, are widely used in customer service. They can answer user questions, provide basic information and interactive services, alleviating the burden on human customer service.
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Industrial Automation: In the industrial sector, AI Agents can be used for controlling and managing automated production lines, improving production efficiency and product quality.
For example, in the past, ordering food on a mobile phone was done by ourselves, without realizing the decision-making process involved. However, if this task is handed over to AI, several AI Agents would need to collaborate: one AI Agent analyzes our dining habits and discovers personal preferences; another selects suitable price points based on our spending level; another interacts with various apps to find corresponding restaurants and dishes; one AI Agent is responsible for horizontal comparisons and providing the best suggestions; and possibly another AI Agent communicates with you to introduce and complete the order. In this process, it may also require additional AI Agents to evaluate health, weight loss, and other factors. In other words, because human strengths are difficult to categorize and the communication cost between people is too high, in the past, managers tended to assign multiple work tasks to one person in an organization. Many hiring or job-setting processes in companies are also vague. However, the emergence of AI Agents has given us a deeper understanding of work tasks. Interactions between AI Agents are highly efficient, and since each AI Agent has different strengths, we can and need to break down work into different steps and assign them to different AI Agents to collaborate for the best results. At this point, the HR department becomes even more critical, and the head of HR will become one of the most crucial managers in the company. They must work with the IT department to reevaluate the work required for each position in the company and consider how these tasks can be linked together to form efficient processes. It is worth noting that although the capabilities of AI Agents are increasingly powerful, not all jobs will be replaced by them. Just as even with the advanced robotic arms, Tesla’s Gigafactory still requires human workers and machines to cooperate to produce electric vehicles. In the future, companies will also need to determine which tasks are suitable for automation by AI Agents and which should be completed by human employees. This collaboration between humans and machines will become the new normal in business operations. Of course, this also places new demands on human employees’ abilities; we need to possess stronger complex decision-making skills, empathy, and creativity, and engage in more strategic thinking to maximize value in a human-machine collaborative environment. It is easy to imagine that companies that refuse to change and are unwilling to use AI Agents will soon be eliminated by those that heavily utilize them. However, effectively using AI Agents is not easy; blind use may lead to more chaotic internal processes in enterprises. Just like many companies once thought that IT integration meant storing all information on computers, only to find that when communication was needed, they still printed materials, resulting in more investment and lower efficiency. Therefore, companies should reconstruct business processes based on AI, rather than simply delegating parts of existing processes to AI. We believe that future business processes should be reversed; instead of centering on employees and letting AI enhance their efficiency, they should center on AI’s capabilities, forming smooth transitions and workflows between humans and AI Agents. Each employee should act like a contractor or manager, responsible for evaluating and supervising the work of AI Agents, identifying gaps, and intervening to solve problems when AI encounters obstacles. Moreover, only when humans continuously provide feedback to AI can AI become stronger, achieving a collaborative evolution between humans and machines.
Palantir, whose stock price soared last year, is a great example. They restructured their processes by integrating AI Agents into their data analysis platform, achieving rapid data processing and insight generation. This allowed Palantir to significantly shorten project cycles and improve decision-making efficiency, with tasks that previously took five to six weeks now completed in just one week.
However, the rise of AI Agents also comes with a series of security risks. Gartner analysts point out that the new functionalities of AI Agents expand the attack surface for cyberattacks, posing more complex security challenges for organizations. The following are the main security risks brought by AI Agents:
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Expanded Attack Surface: AI Agents access critical systems and undertake sensitive tasks, making them easy targets for cyberattacks.
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Data Leakage: Due to their autonomy, AI Agents may inadvertently expose confidential information, especially in the absence of appropriate oversight.
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Ethical and Privacy Issues: The decisions made by AI Agents may be influenced by biases in training data, leading to unfair outcomes for individuals.
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Compliance Challenges: AI Agents must adhere to data protection regulations such as GDPR; non-compliance poses legal risks.
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Unauthorized Operations: AI Agents may be hijacked by attackers to perform harmful operations.
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Resource Consumption: AI Agents may overload systems, leading to denial-of-service (DoS) attacks.
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Coding Errors and Supply Chain Risks: Relying on external code and libraries may introduce security vulnerabilities.
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Exploitation Vulnerabilities: AI Agents can execute complex attacks, increasing cybersecurity risks.
In response to these challenges, organizations need to adopt various strategies to address the risks posed by AI Agents, such as comprehensively mapping AI Agent activities, implementing anomaly detection and real-time remediation, integrating identity and access management, and creating continuous monitoring systems. These measures can not only enhance security but also ensure that AI Agents operate within ethical and legal frameworks. However, I want to emphasize that from a long-term perspective, all companies will eventually become human-machine hybrid companies, and those with evolutionary capabilities will be the truly promising ones. In other words, to become the ultimate winner, your business processes need to have closed-loop feedback and feedback-based improvement mechanisms, continuously iterating and optimizing to excel in business and stand out in competition. In summary, AI Agents, as the new generation of artificial intelligence technology revolution, are gradually changing the way we work and our life scenarios. With the continuous advancement of technology and the expansion of application scenarios, AI Agents will play an increasingly important role in the future.
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