The rapid growth of artificial intelligence (AI) is fundamentally changing the software engineering profession and white-collar jobs. This shift is creating a tension between higher productivity and a lack of job security for many professionals.

人工智能 (AI) 的快速成長正從根本上改變軟體工程專業與白領工作。這種轉變在提高生產力與許多專業人士缺乏工作保障之間造成了緊張關係。

The software engineering sector is currently very unstable because AI models are being released more frequently. For example, major AI releases grew from 18 in 2023 to 69 in 2025, which has caused stress for developers who feel they cannot keep up with the new technology. As a result, many developers have moved from writing code by hand to 'botsitting,' where they mainly manage AI-generated content. This has created two types of roles: 'AI engineers' who build the systems, and 'forward-deployed engineers' who help clients use these systems. While some experts believe technical skills are most important, others emphasize that the ability to turn technology into business profit is the key to staying employed.

軟體工程部門目前非常不穩定，因為 AI 模型的發佈頻率日益增加。例如，重大的 AI 發佈數量從 2023 年的 18 次增加到 2025 年的 69 次，這讓許多開發者感到壓力沉重，覺得無法跟上新技術。因此，許多開發者從手寫程式轉向「bot-sitting」（機器人看守），主要負責管理 AI 生成的內容。這創造了兩種角色：「AI 工程師」負責構建系統，而「前線部署工程師」則協助客戶使用這些系統。雖然部分專家認為技術能力最重要，但也有人強調，將技術轉化為商業利潤的能力才是維持就業的關鍵。

There is also a contradiction in how companies are hiring. Although some firms claim that AI is the main reason for job cuts, data from SignalFire shows that engineering roles remained strong in 2025, making up 55% of new hires at big tech firms. This happens because AI makes coding more efficient, which actually increases the total amount of work and the need for human supervision. However, this is not true for everyone. In Switzerland, job ads for entry-level positions fell by 32% compared to 2019-2022, suggesting that AI is replacing junior staff in finance and IT.

公司在招聘方面也存在矛盾。儘管部分公司聲稱 AI 是裁員的主因，但 SignalFire 的數據顯示，2025 年工程崗位依然強勁，佔大科技公司新進員工的 55%。這是因為 AI 提高了編碼效率，反而增加了總工作量以及對人工監督的需求。然而，情況並非對所有人都如此。在瑞士，入門級職位的招聘廣告比 2019-2022 年下降了 32%，顯示 AI 正在取代金融與 IT 行業的初級員工。

Finally, there is a gap in AI education. Even though more people are taking AI courses, employers say there is a shortage of 'builders' who can actually use AI in real-world projects. Consequently, schools are moving toward project-based learning. At the same time, business leaders argue for a 'human-plus-AI' approach. They assert that while AI can handle technical tasks, human judgment and authenticity are still irreplaceable. The general agreement is that professional value now depends on the ability to constantly learn, unlearn, and relearn new skills.

最後，AI 教育方面存在缺口。儘管更多人參加 AI 課程，但僱主表示缺乏能夠將 AI 實際應用於現實項目中的「構建者」。因此，學校正轉向以專案為基礎的學習。同時，企業領袖主張採取「人類 + AI」的方法。他們認定，雖然 AI 可以處理技術任務，但人類的判斷力與真實性依然不可替代。普遍共識是，專業價值現在取決於能否不斷學習、捨棄舊知並重新學習新技能。

In summary, AI is acting as a tool that increases productivity, but it also requires workers to completely change their skills and creates new challenges for those starting their careers.

總結來說，AI 扮演著提升生產力工具的角色，但它也要求工作者完全改變技能，並為剛開啟職涯的人帶來新挑戰。