"Is the AI model competition over? The real battle is between 'AI agents'"

# Are AI Model Competitions Over? The Real Battle Is Now Between AI Agents

The era of "which AI is smarter" has moved one step forward. The real topic now is 'AI agents' that use tools and handle tasks on their own.

From Model to Agent

Until now, AI was basically a tool that 'answered questions.' When users asked questions, it provided answers. But agents are different. They're given goals and then plan on their own, performing tasks like search, calculation, reservation, and code execution. They create results from start to finish.

Understanding Through Analogy

If traditional AI was like a "smart dictionary that answers questions," then agents are more like "a secretary who handles tasks." For example, if you say "prepare for a business trip next week," the agent searches for flights and hotels, organizes schedules, and creates necessary documents all on its own. Unlike simple answers, agents handle multiple steps to reach the goal.

Why Is the Focus Changing Now?

As AI model performance reaches a certain level, simply having "smarter answers" no longer provides differentiation. Now, the real differentiator is how well AI can be applied to actual work and deliver real results. This is why agents are gaining attention - the competition now focuses on what can be accomplished rather than which model is better.

Industry Is Rapidly Reorganizing

• Investment: Major tech companies are pouring massive resources into agent technology and infrastructure.
• Collaboration & Acquisition: Companies compete fiercely for partnerships, acquisitions, and talent acquisition.
• Application Expansion: Rapid expansion into customer service, coding, marketing, and office automation.
• Regulation: Discussions about safety and responsibility of AI that acts autonomously are intensifying.

What Needs to Be Prepared?

For both companies and individuals, the key is "ability to properly utilize AI." Beyond just using good models, the ability to design work in a way that agents can handle it becomes competitive advantage.

• Clear Instructions: The clearer the goals and constraints, the better the results.
• Verification Habits: Human verification of agent outputs remains important.
• Work Redesign: The ability to decide what tasks agents should handle and what humans should do is essential.

A smarter AI isn't the winner. The AI that "does work well" wins next time.

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