AI Agents in the Spotlight
An AI agent refers to an artificial intelligence program that can make decisions and act autonomously like a human. It responds to user requests or environmental changes, solves problems, and actively works to achieve specific goals. It’s not just a tool that executes commands, but an “intelligent entity” that can understand, analyze, and make decisions based on context.
For example, when you contact a customer service center, an AI agent can first understand your question, find the relevant answer, and respond or connect you to a human representative if needed. All of this is done through the AI’s autonomous judgment.
AI agents generally operate through the following process:
Perceiving the Environment: They receive and analyze inputs such as user instructions, surrounding conditions, or data.
Making Judgments and Decisions: They determine the appropriate action to take.
Executing Actions: They carry out the chosen action.
Learning from Feedback: They learn from outcomes to improve future responses.
Thanks to these characteristics, AI agents are being increasingly used not only for repetitive tasks but also for solving complex problems. They support humans efficiently in various areas such as customer service, schedule management, content recommendations, and security monitoring.
By utilizing AI agents, organizations can benefit from increased productivity, reduced costs, data-driven decision-making, and improved customer experience.
To better understand AI agents, let’s compare them to the more commonly discussed LLMs.
Category | LLM (Large Language Model) | AI Agent |
|---|---|---|
Concept | A natural language processing model trained on massive datasets. Used for text generation, translation, summarization, Q&A, etc. | An AI system that perceives the environment, plans, executes, and learns to achieve a specific goal. |
Examples | ChatGPT, Claude, Gemini, LLaMA | AutoGPT, AgentGPT, ReAct, LangChain Agent |
1. Roles and Capabilities
Category | LLM | AI Agent |
|---|---|---|
Primary Role | Language-focused tasks like answering questions, generating or summarizing documents | Performs goal-directed tasks autonomously (e.g., collecting info online, summarizing, emailing results) |
Functional Scope | Performs only instructed tasks, limited in external perception and decision-making | Can perform actions like using tools, storing state, and handling complex operations |
Example Tasks | “Recommend a movie”, “Translate this sentence” | “Analyze a product → Search Google → Create report → Send email” |
2. Components
Category | LLM | AI Agent |
|---|---|---|
Core Technology | Transformer-based language model | LLM + tools + memory + behavior control logic (e.g., planning & execution) |
Standalone Capable | ✕ (Requires prompts to operate) | ✓ (Can autonomously complete multi-step tasks after receiving a prompt) |
Put simply, LLMs are one of the components of AI agents. AI agents are systems that extend the capabilities of LLMs with plugins, tool usage, memory, and decision making to perform more complex tasks.
How Are AI Agents Used in Real Life?
AI agents are now easy to spot in our daily lives. They've evolved beyond simple chatbot functions and are establishing themselves as intelligent assistants capable of predicting human behavior and making autonomous decisions. Here are some real world examples:
Customer Service Chatbots
One of the most widespread forms of AI agents is customer service chatbots. These are commonly seen in online stores, banks, and telecom companies. They can quickly respond to basic inquiries like tracking deliveries, handling payment errors, or processing refund requests. More advanced bots go beyond giving answers they understand customer intent and automate necessary tasks. They work 24/7, independent of business hours, which improves customer satisfaction and reduces labor costs. ARGOS also offers chatbot services.
However, not all chatbots are AI agents. Depending on their capabilities, some may be classified as AI agents, while others remain simple automated response systems.
Personal Assistant Apps (e.g., Google Assistant, Apple Siri, Amazon Alexa)
AI assistants embedded in smartphones or smart speakers are classic examples of AI agents. They recognize voice commands and perform tasks such as setting alarms, playing music, checking the weather, and sending messages. For instance, if you say, “Schedule a meeting at 10 AM tomorrow,” the assistant will add it to your calendar and set a reminder. These assistants improve over time by learning from repeated interactions and adapting to user preferences.
What Will AI Agents Be Capable of in the Future?
AI agents already do impressive work, but they are expected to become far more capable and human-like. Future AI agents will function as around-the-clock personal assistants who know you better than anyone.
Microsoft Copilot is a prime example of a real world AI agent. Microsoft integrated AI into its Office suite (Word, Excel, PowerPoint, etc.), creating Copilot to assist users with their work.
Copilot is not just a tool it understands instructions and independently determines appropriate actions. This makes it stand out from traditional automation tools.
The AI Agent Market in 2025
The AI agent market is growing rapidly. According to Research and Markets, the market is expected to grow from $5.1 billion in 2024 to $47.1 billion in 2030, with a compound annual growth rate (CAGR) of 44.8%.
Although AI agents are used across many sectors, the customer service and support sector is expected to hold the largest share.
Why?
Today’s customers provide instant feedback when inconvenienced. To process such fast and high volumes of inquiries, dedicated AI agents are essential. These agents provide fast, accurate, and personalized responses 24/7.
This leads to improved customer satisfaction and increased brand awareness. From the company’s perspective, AI handles repetitive tasks, cutting operational costs and allowing staff to focus on more complex issues. Since AI agents integrate easily with CRM systems, adoption is relatively frictionless for businesses.
Regional Trends
North America (U.S. & Canada) is projected to hold the largest market share in 2024. The region's quick adoption of new technologies, solid digital infrastructure, and significant investments by tech giants like Google, Microsoft, and IBM drive growth. For example:
IBM develops AI solutions for banks and healthcare institutions.
Walmart uses AI agents to optimize supply chains and improve customer service.
North America’s legal and regulatory frameworks also support the AI ecosystem.
Asia Pacific is expected to be the fastest-growing region during the forecast period. This growth is fueled by rapid digitalization, technological advancements, and a growing pool of tech-savvy talent.
In China, companies like Alibaba and JD.com use AI agents to enhance customer service and reduce logistics costs.
In Japan, SoftBank operates a customer support system combining robotics and AI, reflecting high national interest in automation.
Frequently Asked Questions (FAQ) About AI Agents
Q1. What does an AI agent do?
An AI agent understands goals, analyzes situations, uses tools, and performs tasks autonomously. It acts as a virtual assistant that processes tasks rather than just answering questions.
Q2. Is ChatGPT an AI agent?
The base version of ChatGPT is a powerful LLM but not a full AI agent. However, when integrated with plugins, memory, and APIs (e.g., ChatGPT Pro or Custom GPTs), it takes on AI agent-like characteristics.
Q3. What are the 5 types of AI agents?
Simple Reflex Agents React only to current conditions.
Model-Based Reflex Agents Use internal models to consider past states.
Goal-Based Agents Plan actions to achieve specific goals.
Utility-Based Agents Choose actions that maximize expected utility.
Learning Agents Improve performance through experience and feedback.
Q4. Are chatbots AI agents?
Not necessarily. Most chatbots are rule-based or reactive systems that follow predefined flows. In contrast, AI agents can reason autonomously, use tools, and perform multi-step tasks.
Q5. Is ChatGPT the most powerful AI?
GPT-4 and successors are among the most powerful language models. However, true AI “power” lies in autonomy, integration, and adaptability areas where custom AI agents may outperform ChatGPT depending on the context.
Q6. What is the difference between Custom GPTs and AI agents?
Custom GPTs are fine tuned language models tailored for specific tasks or tones but still rely on user prompts. In contrast, AI agents decide what, how, and when to act often without ongoing user input and can use external tools and memory to complete tasks.
In the next post, we will introduce the vulnerabilities of AI agents and ARGOS’s proposed solutions.
