What Hidden Risks Do AI Agents Pose?
In our previous content, we explored the definition, roles, FAQs, and real-world applications of AI agents.
Today, we take a step further to examine what AI agents actually do, the security, ethical, and legal issues they can raise, and how ARGOS proposes to mitigate these risks.
How Capable Are AI Agents?
AI agents act as proxies in real-world workflows by autonomously making decisions and executing actions based on Multi-Channel Platform (MCP) connections.
Examples of what AI agents can do include:
Sending emails and messages automatically
Accessing internal systems and extracting information
Executing payments and fund transfers
Initiating, renewing, or canceling contracts
Changing system settings and deleting files
Resetting logs and modifying security configurations
As you can see, the scope of what AI agents can do is vast—far beyond basic automation. They now act as replacements or assistants for human roles.
Then Why Are Their Capabilities Still Limited?
Most of the examples listed above involve tasks that require clear human authorization. Despite having autonomy, AI agents cannot take action without a verification process. This creates a paradox—AI has powerful capabilities, but without proper approval mechanisms, these very abilities become a risk.
Many companies deliberately restrict the range of AI execution due to operational risks.
Why? Because the biggest issue is the lack of user consent.
AI can execute tasks automatically once permissions are granted. However, humans ensure mutual confirmation before making critical decisions. Without clear user consent, canceling a contract or transferring funds becomes a major risk.
No matter how advanced an AI agent becomes, it should never act without the user’s clear approval—especially in areas like finance, healthcare, or legal contracts where consent can make or break legal disputes.
Examples:
Auto transaction approval: Transactions may proceed without the user's knowledge
Personal data usage: AI may access and process sensitive information without proper oversight
Due to the potential for thousands of errors per second, AI agents are generally restricted from:
Accessing sensitive personal data
Automating tasks without human involvement
Managing contracts or transactions that entail legal responsibility
Modifying high-risk system settings or accessing critical logs
The Potential Risks of AI Agents
Although AI agents bring innovation across industries and daily life, we cannot overlook the risks. Their autonomy and automation introduce growing complexity that demands strict regulations and transparent systems.
It’s crucial to address these challenges alongside the benefits.
1. Security Vulnerabilities & Fraud Risks
One of the biggest concerns is vulnerability to security breaches and fraud. AI relies on large datasets to make decisions, but if this data is flawed, decisions can be incorrect.
Worse, hackers may exploit AI systems to access internal data or trigger unauthorized actions. AI is especially vulnerable to unexpected inputs or novel attack vectors, making it a high-risk component in cybersecurity.
“When AI makes decisions on behalf of people, those decisions can translate directly into financial losses.”
— Edward Tian, CEO of GPTZero
2. Data Quality & Bias
Another key risk is data quality and algorithmic bias. Since AI decisions are trained on past data, inaccuracies or biases in the data will lead to distorted outcomes.
For instance, some lending algorithms have been found to disadvantage specific races, genders, or regions—resulting in serious social and legal consequences.
3. Unclear Accountability
Legal disputes often arise from AI bias. The major legal and ethical problem is that when AI causes harm to rights or assets, it’s unclear who is responsible—the developer, the deploying company, or the operator?
There’s still no global consensus, and many countries lack legal frameworks to determine accountability.
4. Loss of User Control
As AI makes autonomous decisions, users may lose control over important actions. AI could make sensitive decisions without user knowledge, and this increasing autonomy may weaken human judgment and authority.
This violates the foundational principle of “human-centered” technology. Therefore, it's vital to establish approval processes that ensure explicit user consent before AI performs any proxy actions like financial transactions.
Users must be able to monitor how their data and assets are being managed.
5. System Conflicts and Instability
Lastly, system conflicts and instability are significant concerns. In complex environments where multiple AIs interact, unexpected clashes can occur.
Inconsistent global standards, differences in message formats, or communication delays can cause AI decision processes to break down.
AI agents are powerful tools, but without careful safeguards, they can jeopardize system stability and trust. They are a double-edged sword that requires a structured safety framework.
Is AI the “Ultimate Solution” for Automation?
AI agents are often seen as the pinnacle of automation, but not all automation requires AI.
For repetitive tasks or rule-based processes, traditional tools like RPA (Robotic Process Automation), workflow engines, or scripts may be more efficient and cost-effective.
However, AI agents shine in areas like:
Unstructured data (e.g., language, images, audio)
Real-time judgment (e.g., fraud or anomaly detection)
Contextual, adaptive interactions (e.g., personalized assistants)
Ultimately, AI agents are indispensable for complex, real-time, unstructured tasks—but choosing the right tool for the right context is key.
AI isn’t the answer to automation; it’s one of many precise instruments.
AI as a Proxy – The Ethical Responsibility
AI agents are no longer just tools. They act as proxies that carry out tasks based on a user’s intent.
They analyze user data, make decisions, and interact with other systems or agents—all with minimal human input.
Thus, we must ask ethical questions such as:
Does the AI reflect the user's intent?
Does it align with social values and norms?
Is it free from bias against specific groups?
Poor AI decisions don’t just lead to errors—they erode trust. That’s why responsible design is essential.(Axios)
AI agents must operate transparently, and users must understand how decisions are made.
Legal liability for AI mistakes must also be clearly assigned to avoid ethical and legal issues.
ARGOS’s Approach: Consent, Control, and Responsibility
ARGOS proposes a framework centered on user consent to mitigate these risks.
AI agents or MCPs are capable of executing a wide range of tasks. But when they perform sensitive operations like payments, contract termination, or account deletion without explicit user consent, they pose serious security and accountability risks.
To prevent such risks, most current AI agent systems disable or remove sensitive functions—limiting their full potential.
This structural problem doesn’t arise because AI might make a mistake—but because it can make that mistake too quickly and at scale.
Without human involvement, these risks are unmanageable.
Today, we briefly explored the risks of AI agents. ARGOS is actively developing technologies to ensure frameworks are in place to keep AI under control.
In the next content, we will introduce ARGOS’s specific solutions and architectures, and how they are being implemented.
AI agents are powerful, capable tools. But their potential can only be safely realized on a foundation of responsibility, consent, and human oversight.
Technology will continue to evolve—but the responsibility for its use remains with humans.
