Summary of Key Points
This article explores the impact of AI on employment through various events, such as Amazon's dismissal of its AGI team, GitHub's introduction of the Copilot enterprise dashboard, the progress of AI without a surge in unemployment rates, and the decreasing proportion of young people entering high-AI industries. It highlights that AI does not directly replace existing jobs but rather changes the way companies hire: the focus shifts from asking "Can AI do my job?" to "How important is this task to the company's goals?" As AI improves efficiency, companies are gradually reducing recruitment, especially for entry-level positions, making it more difficult for new graduates to enter the workforce.
Detailed Analysis
1. Are Those Who Develop AI the First to Be Laid Off?
The fact that Amazon eliminated its AGI team does not mean AI is no longer important; company officials even stated that large-scale AI models are "one of the most critical tasks." The key is that companies are looking for AI projects that provide real value to customers, not just the technology itself. For example, if an AI project is still in the research phase or not closely related to the company's core business (such as e-commerce or cloud services), its priority may be lowered. Even if you are an expert in AI development, your team might be cut if their work does not align with the company's main goals. This indicates that job security depends on the value the task adds to the company's objectives, not on the technical complexity.
2. Can Bosses Now Monitor AI Usage?
GitHub's new Copilot dashboard is designed for managers to track employees' use of AI—whether they are simply using it to complete small tasks or to handle entire projects—and to compare the productivity of those who use AI. Previously, managers could only assume that employees were skilled in AI; now, with concrete data available, they can see whether using AI allows someone to perform the work of two people. This means that being able to use AI is no longer just a boast on a resume but a measurable indicator of productivity that affects hiring decisions.
3. Despite Rapid AI Progress, Unemployment Rates Remain Stable?
There are two reasons why unemployment rates have not increased despite the rapid development of AI:
1. Companies are hesitant to rely entirely on AI: While AI can write code efficiently, who is responsible for errors? Tasks involving internal data and audits still require human oversight.
2. The reduction in jobs is gradual and silent: For instance, if two team members leave, the remaining employees might be asked to handle more work with the help of AI, and no new hires are made. These changes do not make headlines or affect unemployment statistics, but the number of available positions has indeed decreased.
4. It's Getting Harder for New Graduates to Enter the Workplace?
AI is particularly effective at tasks that new graduates typically perform, such as researching information, making minor code adjustments, and writing basic content. As senior employees use AI to handle these tasks, companies no longer need as many entry-level positions. Research by Anthropic shows that the proportion of young people (22-25 years old) entering high-AI industries has decreased by 14% compared to 2022. It's not that jobs have disappeared, but rather that the entry barriers have increased—new graduates no longer have opportunities to gain experience in basic roles.
5. Early Signs of Change
For ordinary employees, layoffs are not the first warning sign. Earlier indicators include:
- Companies starting to track AI usage (e.g., asking how much work is done with AI each week);
- Open positions left vacant after previous employees leave;
- A decrease in campus recruitment and internships;
- Managers discussing both AI usage and employee productivity during meetings.
These changes indicate that companies are reevaluating their staffing strategies based on the role of AI.
Conclusion
The impact of AI on employment is not about being laid off today, but rather about no longer hiring people for the same jobs in the future. Instead of worrying about being replaced by AI, it's more important to ask: How important is your current role to the company's goals? Have you improved efficiency through AI? And will the company still need to hire new employees for your tasks? These are the practical questions to consider.