AI Isn’t Here to Take Your Jobs—It’s Here to “Lend” Your Colleagues’ Skills
Hello everyone, I’m your financial observer. Recently, OpenAI released a quite interesting report titled “Workfront: How Workers Unlock New Ways of Working.” Many people’s first reaction upon hearing the word “AI” is, “Oh no, I’m going to lose my job!” or “My position is going to be replaced?”
But this report reveals a more subtle and realistic scenario: Your job is still there, but the “job description” for your role is being rewritten.
In simple terms, AI isn’t directly replacing you; it’s making tasks that you were previously “not supposed to do,” “couldn’t do,” or “didn’t have time for” much easier to complete. You start using AI to handle tasks from other departments, and before you know it, those tasks become part of your daily routine.
Below, I’ll break down the report into five key points to explain this new workplace logic in plain language.
1. Core Finding: From “Learning Skills” to “Lending Abilities”
In the past, when we talked about “crossing fields,” it meant you had to learn a new skill on your own—like a programmer having to take courses, read books, and practice. However, OpenAI has found that workers’ attitudes towards AI have completely changed. They’re no longer “learning” but rather “lending” their expertise.
The report uses a vivid term: “Borrowing Expertise.”
- Old approach: “I want to learn how to code, so I ask AI: ‘Please explain the basics of Python and give me some practice questions.’”
- New approach: “I’m a salesperson, but I need to write a simple data script. I ask AI: ‘Here’s the situation… here’s the context… just handle it for me and give me the code that works.’”
Data shows that when people ask AI to perform tasks outside of their regular job scope, the prompts they use are on average 20 characters shorter and more focused on providing the results rather than instructions. This indicates that people don’t want to be students; they want to act as “project managers,” outsourcing specialized tasks to AI, which acts like an “all-rounder intern.”
2. Behavioral Change: From “Giving It a Try” to “Making It the Norm”
The most surprising thing is not that people can use AI for other tasks, but that they are actually doing so and with increasing frequency. OpenAI tracked about 6,200 employees and found this astonishing trend:
- April: Only 13.1% of AI-related tasks were cross-functional.
- July: This proportion rose to 25.9%.
That’s nearly a doubling in just four months! This means that using AI for additional tasks is no longer a rare or novel activity; it’s becoming a repetitive part of the work process.
Another interesting statistic: If you used AI for a cross-functional task this month, there’s a 23.6% chance you’ll do it again next month; if you didn’t do it last month, the chance is only 8.4%. This shows that once a habit is formed, it tends to reinforce itself. If you find that using AI to generate legal summaries is quick and efficient, your next time you encounter a similar task, you’ll likely turn to AI instead of your legal colleague.
3. The “Office Diffusion Effect” of AI Use
The use of AI also has a strong social aspect, what the report calls the “office diffusion effect.” If a colleague in your workplace is already using AI for cross-functional tasks, the likelihood of you trying it yourself the next month is 3.1%, compared to 2.5% if no one else is doing it. Although the difference seems small, statistically, this demonstrates that observing others use AI is a stronger motivator for adopting new work methods.
Imagine:
- Scenario A: You use AI to write marketing copy in secret, feeling a bit unsure about its reliability.
- Scenario B: You see your colleagues in the next department using AI-generated marketing copy that gets praise from your boss and is highly efficient.
In Scenario B, the barrier to adopting new tools is lowered because others have already demonstrated its effectiveness. New tools are often adopted through peer pressure and herd mentality, not through individual heroism.
4. Which Tasks Are Most Suitable for Cross-Functional Use? Risk Determines the Boundaries
Not all professional tasks can be easily transferred to AI. OpenAI analyzed the likelihood of tasks being reused after the first use and found the following:
🔥 High-reliability tasks (easily transferred):
- Customer communication: 54.1% (more than half of users continued to use these tasks)
- Advertising/promotional copywriting: 44.2%
- Marketing material creation: 37.3%
❄️ Low-reliability tasks (more risky to transfer):
- Explaining financial information to customers: 15.0%
- Presenting business information: 14.9%
- Legal research: 9.9%
The reason for this difference is simple: Risk tolerance. Writing a marketing email or organizing customer communication materials can be tweaked if AI makes mistakes; the consequences are usually minor (a bit of embarrassment at most). However, legal research or financial explanations could lead to serious issues like hefty fines, legal disputes, or significant financial losses.
Therefore, AI’s impact on careers isn’t uniform. It breaks down barriers first in areas with lower risk and higher tolerance for errors.
5. What Does This Mean for Companies and Individuals?
This report serves as a wake-up call for both companies and workers, but the implications might be different from what you expect:
For workers:
- Your competitiveness depends on more than just your core skills. If you can use AI to quickly create marketing content, analyze data, or handle basic legal tasks, your value increases significantly.
- **The need for “T-shaped” (vertical expertise) to “π-shaped” (multi-disciplinary) or even “comb-shaped” (versatile) talents is growing. You need not only deep expertise in your field but also cross-functional skills acquired through AI.
- Be wary of skill degradation. If you rely too much on AI for cross-functional tasks, you may lose the ability to make critical judgments in your core area of expertise.
For companies:
- Job design needs to be rethought. Traditional departmental boundaries are being blurred by AI. People from marketing or customer service might be doing sales tasks. Companies need to ask themselves: Which tasks can be shared across departments? Which processes can be streamlined?
- AI strategies are about more than just buying tools; they’re about changing processes. If employees are using AI for cross-functional tasks, approval processes, collaboration methods, and performance evaluations must adapt.
- Professional judgment remains crucial. While AI can lend you skills, it can’t take on your professional responsibilities. In high-risk fields like finance, law, and healthcare, the value of those who make the final decisions will only increase with AI’s use.
Conclusion
OpenAI’s report highlights that in the AI era, career boundaries are becoming more fluid. You don’t need to worry about AI replacing you immediately, but you should be concerned if your colleagues are using AI to enhance their skills, making them more competent, faster, and more versatile. If you remain stuck in your own domain, you’re at risk.
Your job is still there, but the “container” for that job has changed.