エージェント型AI：2025年後半の職場革命

Key Takeaways

• Action, Not Just Talk: Agentic AI differs from LLMs because it has “agency”—the ability to use tools, browse the web, and execute complex workflows independently.
• The New Manager: Humans are shifting from “doing the work” to “managing the agents” who do the work.
• Productivity Boom: Early adopters report a 40% reduction in administrative overhead.

Introduction

For the last two years, we’ve been treating AI like a very smart intern who lives in a chat box. You ask a question, it gives an answer. It was passive. It was waiting for you.

But in late 2025, the intern got a promotion. And a set of keys to the office.

“Agentic AI” has emerged as the dominant trend of the year. These aren’t just chatbots; they are autonomous agents capable of planning, reasoning, and executing tasks across multiple apps without you holding their hand.

What differs “Agentic” from “Generative”?

Traditional Generative AI is like a Oracle: You ask it for wisdom, and it speaks. Agentic AI is like a Employee: You give it a goal, and it figures out the steps.

• GenAI: “Write an email to my team about the delay.”
• Agentic AI: “Check the Jira backlog for blocked tickets, identify the delay, email the stakeholders, and reschedule the Tuesday meeting to Friday.”

It doesn’t just generate text; it clicks buttons, sends API requests, reads databases, and solves problems when things go wrong.

The Major Players

Microsoft Copilot Agents Microsoft has gone all-in on this vision. With the new Copilot Studio, users aren’t just chatting with Copilot; they are building mini-agents. “Autonomous Triggers” allow these agents to wake up when a file changes or an email arrives.

• Example: A “Sales Agent” that watches your CRM. When a lead turns “Hot,” it automatically researches the company on LinkedIn, drafts a personalized intro email, and pings you on Teams for approval.

Google Gemini for Work Google’s strength is its ecosystem data fluidness. Their agents excel at multimodal tasks, analyzing video meetings in real-time and assigning action items to Jira or Asana automatically. They are blurring the line between “video call” and “project management.”

The “Human-in-the-Loop” Shift

This shift is fundamentally changing what it means to “work.” We are moving away from Prompt Engineering (trying to trick the AI into being smart) to Agent Orchestration (assigning goals and reviewing output).

In 2024, if the AI output was bad, you blamed your prompt. In 2025, if the Agent fails, you blame your workflow design.

The most valuable skill in 2026 won’t be coding or writing; it will be Delegation. The ability to break a complex problem into steps that an agent can reliably handle is the new literacy.

”The Self-Healing Calendar”

One of the most popular early use cases involves the “Executive Assistant Agent.” Unlike the “scheduling links” of the past (Calendly), these agents actively negotiate.

If a meeting runs late, the agent detects it. It looks at your next meeting. Is it critical? If no, it emails the participant: “Running 10 mins late, mind if we push?” It moves your lunch block. It informs your spouse you’ll be late for dinner. It “heals” your schedule in real-time, proactively managing your time asset without you ever opening the calendar app.

The Risks and Trust

Of course, giving an AI the keys to your email and bank account comes with risks. “Hallucinations” are annoying in a chat; they are catastrophic when an agent accidentally deletes a production database or emails the wrong client.

Trust is the new currency. We are currently in the “Trust but Verify” stage. Every agent action usually requires a “Click to Confirm” from a human. But as error rates drop, we will slowly take our hands off the wheel.

Agentic AI isn’t coming; it’s here. And for the first time, software isn’t just a tool we use; it’s a teammate we work alongside.