The statement "Certain industries will be replaced by AI" is only half true. 

While AI will indeed replace a significant amount of "work content," it is rare for an entire industry to vanish across the board. Instead, industries are undergoing internal division of labor, restructuring, and upgrading. 

Replacing Functions, Not All Roles 
Multiple economic studies indicate that AI will impact approximately 40% to 60% of jobs. In these cases, some processes will be automated, while others will see productivity boosted by AI. 
Highly repetitive tasks—such as data entry, basic customer service, and routine report writing—are easily taken over by AI. However, the same industry will simultaneously create new roles focused on supervising AI, designing processes, and integrating systems. 

The Risk is Real, But It’s Not Doomsday 

Analysts estimate that AI and automation may "expose" hundreds of millions of jobs to replacement risks, particularly in white-collar administration, customer service, and certain areas of programming. 
At the same time, research from the World Economic Forum and major banks predicts that AI-related transformations will create new job categories. These include machine learning engineers, AI safety and ethics experts, and digital transformation consultants. 

Why Humans Retain the Advantage 

Currently, AI excels at standardized, predictable, and data-driven tasks. For work requiring empathy, complex communication, cross-domain judgment, and creative strategy, AI remains a tool for assistance rather than a total replacement. 

Many studies emphasize that "Human-Machine Collaboration" will become the mainstream model: Humans set the direction, make decisions, and bear responsibility, while AI handles calculation, generation, and analysis. 

How to Respond: Don't Fear Replacement, Learn to Utilize It 

The group facing the highest career risk is often not "people affected by AI," but "people who don't know how to use AI." Within the same job function, individuals who master AI tools will possess significantly higher productivity and competitiveness than their peers. 

Practical actions include: 

Learning to deconstruct work into automatable and non-automatable components. 

Mastering at least one AI tool (e.g., Generative AI, RPA, Data Analysis). 

Strengthening "non-programmable" capabilities, such as communication and problem definition. 


Personal Perspective: Reframe "Displaced" as "Restructured" 

Instead of asking, "Will Industry X be replaced by AI?" you should ask: "Which part of this industry's value chain is most susceptible to automation, and can I position myself on the side that designs and controls these systems?" 

Thinking this way offers far more actionable value than abstractly worrying about being "replaced."