When AI Agents Become the New Workforce, Are We Ready?

Published on Sin Chew Daily on the 28th May 2025

1. How I Stepped into the World of “Agent Economy”

In the past six months, my work methods have changed significantly. I now use AI not only for writing, processing data, and managing tasks, but have also started learning LLM Ops (Large Language Model Operations) and utilizing Low Code platforms like Dify.ai, n8n, and Langflow. These tools are integrated into my personal workflow, media operations, and even parts of my business processes—automated through AI Agents.

As I experimented, I found myself becoming less dependent on Word documents or Excel and more engaged in building AI Agents. I started planning use cases and workflows, thinking from the perspective of what an Agent can do instead of doing tasks myself. That was the beginning of my journey with AI agents—assisting with work, and eventually making decisions with them.

At some point, I realized I had become "dependent" on them for creativity and analysis. I no longer ask, “Will AI replace me?” Instead, I wonder, “Can I use AI to replace parts of myself and do better?”

This shift has turned me into a believer in the Agent economy—not only in theory but in action. This article is my attempt to explore how individuals can enter this new economy and how we should prepare ourselves to transform our knowledge and skills into agents, ready for a new competitive market.

2. AI Agents: From Tools to Economic Entities

AI Agents are no longer just tools. They are becoming digital workers capable of making decisions and executing actions autonomously. For example, OpenAI’s Operator can automatically complete webpage writing and online shopping tasks. Chinese companies like Monica, developed by Manus, help with task management, business analytics, and more. These Agents are the foundation of the "Agent Economy," where we no longer just delegate tasks—we delegate workflows and even authority.

3. The Dual Shift of the Market and Workplace

According to a Forbes report, AI Agents are redefining workflows and management models. EY (Ernst & Young) has already implemented Agent-based task collaboration. IBM has thousands of AI projects running across various departments. While not all of them will succeed, their sheer scale proves this is not a passing trend.

CrowdStrike predicts that by 2024, 500 million new apps will be developed globally—equivalent to the total built over the past 40 years. This explosive growth requires not only software engineers but also new types of roles like AI Agent Designers and Orchestrators.

These changes mean that whether you're an executive, manager, or freelancer, you must understand how to use and delegate to AI Agents. The most important career skill in the next decade may not be learning to code, but learning how to collaborate with AI.

4. How to Find Your Place in the Agent Economy

Unlike past technological changes, this is not optional. Here's what I’ve learned through personal trial and error:

● Skill Transformation into AI Agents Turn your expertise into repeatable, structured formats to develop agents that can deliver professional services.

● Use Low Code Platforms to Practice Start building with Dify.ai, n8n, Langflow, etc. These platforms are like digital LEGO, enabling you to build bots for websites, emails, or customer service.

● Build a Personal Brand & Integrate with AI Turn your expertise into modules and connect them to Agents. You can even commercialize your skills through APIs.

● Keep Learning LLM Ops Architecture Learning how to chain knowledge and data with tools is essential. Knowing how to prompt and operate various tools is becoming a core competence.

5. This Is “Personal Re-Industrialization”

AI Agents are not just a new tech—they represent a new economy. In the industrial era, being a “worker” meant trading time and energy for wages. In the AI era, the equivalent is “value creation through automation.” Your value lies in how well your agents perform, how well you manage them, and how effectively they serve your goals.

● Break Down Your Value Chain Dissect your job into automatable steps. Identify where AI can take over and start with repetitive tasks.

● From Product Maintenance to Value Creation In the future, you’ll act like a startup. Your time, knowledge, and experience are assets. If you were your own “company,” how would you create value with your agent team?

● Agent Economy Means Scalable Income and Influence Real Agent Economy is not one-to-one service, but API-based, platform-based, and community-based scalability. If you want recurring revenue and passive income, this is the road.

Many people ask, “Is it too late to get into AI?”

The answer is: it’s already happening, but you still have time to catch up. If you’re not participating, you’re already being outpaced by those who are.

So don’t just be replaced by AI—convert yourself into an AI Agent. This isn’t just survival. It’s a chance for personal value reinvention.

當AI Agent成為新職場主力，我們準備好了嗎？

一、從個人感受出發：我如何踏入「Agent 經濟」的世界

近半年來，我的工作方式已經出現徹底的改變。我開始大量使用AI，不只是用來寫稿、整理資料，更進一步投入學習LLM Ops（大型語言模型運營架構），並嘗試用Low Code平台如DiFY.ai、n8n、Langflow，將我個人的日常工作、自媒體營運、甚至某些業務流程轉化為可自動執行的AI Agent。

這些實驗一開始只是嘗試性的，但慢慢地，我發現自己幾乎每一個專案的起點，不再是打開Word文件，而是打開AI Agent Builder。我開始不再親自去完成每一個細節，而是設計出邏輯與流程，交由AI代理完成初步的工作——然後我再進行優化與判斷。

說得更直接一點，我個人已經開始「依賴」AI進行創作、營運與分析。我不再問自己「AI會不會取代我」，而是每天都在思考「我可以讓AI幫我取代哪一部分的我」。

這樣的轉變，讓我開始真正理解——所謂的「Agent 經濟」並非口號或理論，而是一種新型態的經濟生態，它正如浪潮般席捲全球每一個創作者、工作者與企業經營者。

本文將從我這段親身經歷出發，帶大家看看什麼是AI Agent，為什麼我們正在走向一個以Agent為核心的新經濟時代，以及我們應該如何準備自己，把知識與專業變成Agent，在市場中重新獲得價值。

二、AI代理：從工具到經濟體的演進

AI代理不再僅僅是輔助工具，它們已成為能夠自主決策和執行任務的數位實體。例如，OpenAI的Operator可以自動完成網頁填寫、線上購物等任務，而中國初創公司Monica開發的Manus則能獨立處理網站建設、股票分析等複雜工作。這些代理的出現，標誌著AI從輔助角色轉變為經濟活動的主體。當AI成為某種形式的「員工」或「分身」，新的工作邏輯與經濟結構也隨之誕生。

三、AI代理經濟的崛起：市場與職場的雙重轉型

據《Forbes》報導，AI代理正在重新定義生產力和決策流程，推動企業向更高效的運營模式轉型。例如，EY（安永）已部署150個AI代理，協助8萬名稅務專業人士處理數據收集和合規性工作，顯著提升了效率；IBM則利用AI代理取代了數百個人力資源相關職位，雖然這些崗位被裁撤，但同時也創造了新的程式設計、行銷與數據分析職位。然而，這場轉型也帶來了結構性的挑戰。CrowdStrike在2024年底宣布裁員500人，其中一個原因正是內部AI工具提升了運營效率，減少了對部分職位的依賴。我相信，未來的工作模式將徹底改變。那些重複又重複、需要依賴人工操作的任務——無論是資料錄入、報表處理，還是客服回應——都會逐步由AI Agent取代。這就像幾十年前工廠引入自動化機械臂，取代了大量重型與重複性工序，今天的AI Agent，正是數位時代的「知識型機械臂」。

四、個人如何在AI代理經濟中找到立足點

與其被動等待改變，不如主動擁抱未來。以下是幾個我實際經驗與觀察後的建議：

技能轉化為AI代理

將自己的專業知識和技能模組化，開發成AI代理。例如，顧問可以訓練一個諮詢Bot、設計師可以設計出品牌策略Agent、教師可以創造互動學習助教Agent。

利用Low Code平台開始實踐

使用如DiFY.ai、n8n、Langflow等低代碼工具，無需高深程式技術，也能建立功能性的AI代理流程，幫你處理網站、問卷、客服等任務。

建立個人品牌並與AI整合

將你擁有的影響力、粉絲與內容，與你的Agent結合，透過平台分發、網站上架，甚至是API介接，形成新型態的「知識即服務」商業模式。

持續學習與理解LLM Ops架構

明白如何維護你的代理、如何接入更大的知識庫、如何結合記憶體、插件、甚至多模態技術，是未來不可缺少的能力。

五、擁抱AI代理經濟的未來，不只是跟風，而是一場「個人再工業化」

AI Agent不僅是一種新技術，更是一種新的經濟核心力量。它不單會改變我們工作的方式，甚至會改變我們「定義自己是誰」的方式。對我而言，這場轉變像是一種「個人再工業化」：過去只有企業才有資本和資源去自動化流程、訓練人員、擴張業務，但現在，一個人只要擁有清晰的專業流程、足夠的數據範本與合適的AI平台，就可以擁有自己的「數位工廠」，批量產出屬於自己的服務型Agent，24小時無間斷地運作。但要真正進入這場新經濟，我建議每個讀者可以從三個層面思考與實踐：

從技能出發，拆解你的價值鏈

把你日常的工作內容拆開來看：哪些部分是可預測的？有哪些邏輯可以標準化？這些部分，就是最適合由AI Agent接手的開始點。你不需要一開始就把整份工作自動化，只要從最痛苦、最重複的環節著手，便足以讓AI介入成為生產力提升的槓桿。

從產品思維看待自己，不再只是「工作的人」

未來的你，應該像是一個創業者。你的時間、知識、經驗是原料，而AI是你的代工廠與經紀人。問問自己：如果我是一個「產品」，我可以為誰創造價值？我能否複製這個價值，並在平台上被搜尋、被選用、被訂閱？

用平台而非個人時間去累積收入與聲譽

真正具規模的Agent經濟，不是靠一對一的服務實現，而是透過API、網站、社群、第三方平台，讓Agent自動被呼叫、自動完成任務、自動回報成果。這正是「可擴展性」的開始，也是真正讓一個人擁有無限工作能量的來源。

我們或許會懷疑：「AI真的能做這麼多嗎？」但實情是，它已經在做了，只是還沒輪到你參與而已。你不參與，代表別人會比你更早在這場遊戲中掌握分配權。如果說20世紀是工廠、企業與大規模生產的時代，那麼21世紀的後半段，將是個人智慧、流程知識與AI共同營運的時代。而AI Agent，正是這場數位經濟裡最值得投資的「數位資產」。別等到你的技能被人家的Agent取代，才後悔沒有早點把自己轉化為Agent。與其害怕被AI取締，不如開始讓AI為你工作。這不只是生存之道，更是讓個人價值再進化的機會。