Why domain depth beats generic AI inside a GCC
Anyone can buy a general assistant. Your edge is people who know banking risk, clinical ops, automotive software, or retail supply chains well enough to spot a wrong answer in seconds.
That is why industry-aware AI work keeps showing up in GCC research as a differentiator. The model is common. The judgment is not.
What to hire and build for
- Domain experts paired with ML / platform engineers
- Evaluation sets built from real cases, not toy prompts
- Vertical workflows (claims, PV cases, SDV modules) not only chat
- Feedback loops from frontline users into model improvement
What fails
- AI team with no industry counterparts
- “One bot for everything” mandates
- Ignoring regulated constraints until late
30 / 60 / 90
- 30: Pick one vertical workflow with painful error cost.
- 60: Build a small eval set and a mixed domain-AI squad.
- 90: Ship an assistive system that domain leads trust in daily use.
Takeaway
Generic AI is table stakes.
Domain depth is how an India center becomes hard to replace.
If your charter is industry-specific, we can help shape the first pod mix.