- Why Next-Generation AI Will Change the “Way of Work” Itself
- What is an AI Agent? (Basic Concept)
- Why AI Agents are Gaining Attention
- Critical Differences Between AI Agents and Conventional AI
- Structure of Work Suitable for AI Agents
- How AI Agents Change Work
- Points to Note When Introducing AI Agents
- AI Agents are Not “Automation of Everything”
- Service Introduction: Applying “AI Agent Thinking” to Business
Why Next-Generation AI Will Change the “Way of Work” Itself
Recently, the term “AI Agent” has become increasingly common in the context of Generative AI. However, this concept is not just about a new AI tool.
An AI Agent changes the “position” of AI in relation to work, carrying an impact qualitatively different from conventional AI utilization. This article structurally explains what an AI Agent is, why it is gaining attention, and how it will change work—independent of specific products or services.
What is an AI Agent? (Basic Concept)
An AI Agent refers to an AI that autonomously executes a series of actions toward a pre-defined goal while judging the situation.
Conventional Generative AI was a “passive” entity that:
- Responded to instructions input by humans.
- Produced one-off outputs.
In contrast, an AI Agent is characterized by its ability to handle the flow of work itself, which includes:
- Understanding the objective.
- Collecting necessary information.
- Thinking through the procedures.
- Evaluating results and deciding on the next action.
Why AI Agents are Gaining Attention
The reason is that AI is evolving from a “presence that helps with tasks” to a “presence that bears a portion of the job.”
In conventional AI use, the basic interaction was a single round-trip: Instruction → Output. However, actual work consists of a continuous series of multiple steps, such as: Research → Organization → Analysis → Judgment → Revision.
The value of an AI Agent lies in its ability to handle this continuous process under a single objective.
Critical Differences Between AI Agents and Conventional AI
- Goal-Oriented: An AI Agent starts from “what it wants to achieve.” The means are not fixed and change according to the situation.
- Autonomous Choice of Action: Humans do not need to instruct it step-by-step on what to do next.
- Adjusts According to Situation: It can look at intermediate results and change its approach. Through this, AI moves closer from being an “object of operation” to a “partner in collaboration.”
Structure of Work Suitable for AI Agents
AI Agents demonstrate their power in work where:
- The goal is clear, but the procedures are not fixed.
- Information gathering and organization are repeated multiple times.
- There is a lot of preparation required before a human makes a judgment. (e.g., Creating research reports, updating periodic reports, primary organization of inquiries.)
How AI Agents Change Work
From “Task Units” to “Work Units” Previously, AI was used for task units like “calculation,” “summarization,” or “writing.” With AI Agents, you can entrust AI with work units such as “summarizing monthly reports” or “organizing inquiries to identify trends.”
How Human Roles Will Change The center of gravity in work moves “upstream”:
- Doing the task → Setting the objective.
- Thinking of procedures → Evaluating results.
- Creating output → Making decisions.
Points to Note When Introducing AI Agents
AI Agents are not omnipotent.
- Vague goals lead to runaway behavior: If the goal is unclear, it repeats wasted actions.
- Evaluation criteria are necessary: Humans must provide the standards to judge “if the result is good.”
- Final responsibility remains with humans: The AI prepares the materials, but the human makes the decision.
AI Agents are Not “Automation of Everything”
Understanding AI Agents as “something that automates everything” leads to failure. Their essence is to collectively handle the steps necessary for humans to think.
As a result:
- Humans can have a bird’s-eye view of the whole.
- Humans can concentrate on judgment.
- Quality becomes easier to stabilize.
Service Introduction: Applying “AI Agent Thinking” to Business
We have transformed the concept of “AI handling intermediate steps so humans can focus on judgment” into a user-friendly service.
By linking Excel and ChatGPT, we expand the scope of automation—which previously relied on manual labor or Macro/VBA—to include statistical processing, analysis, summarization, and visualization.
By integrating an AI Agent-like role into your Excel operations, you can perform data shaping, key point extraction, and reporting via natural language instructions.