Everyone wants AI to cut costs.
And honestly, I get it.
Software is expensive, but running software is often even more expensive. One estimate I keep seeing is that for every $1 spent on software, companies may spend around $6 on services, implementation, support, and operations.
So the promise of AI agents is very tempting: less manual work, fewer handovers, faster execution, lower cost.
But here is the dilemma I keep thinking about.
AI is getting very good at “junior work”.
Drafting. Summarising. Research. First-pass analysis. Basic coding. Customer support. Document review.
For many companies, the question becomes: if an AI agent can do this faster and cheaper, why hire the junior person?
But then, where do seniors come from?
Expertise is not downloaded. It is earned.
People become good by doing the boring first drafts, making mistakes, sitting in meetings they barely understand, watching how senior people think, getting corrected, and trying again.
If we remove too much of the junior layer, we may save cost today but damage the talent pipeline tomorrow.
This matters especially in Asia, where entry-level jobs are often the first bridge into the professional economy.
So maybe the question is not whether AI should replace juniors.
The better question is:
How do we redesign junior roles so people learn with AI, not disappear because of AI?
Because a company with no juniors today may become an industry with no experts tomorrow.