India report says AI governance needs continuous control layer in production

While much of the global AI conversation fixates on model size and training runs, this Indian report zeroes in on the far more mundane but critical question of how enterprises actually keep AI under control once it is embedded in workflows. The call for a dedicated control layer built from evals, guardrails and observability echoes what leading labs are doing internally, but applies it to banks, insurers, manufacturers and government departments.

For the AGI race, that is important because most catastrophic failure modes and systemic risks are likely to emerge from messy, distributed deployments rather than a single lab event. If large Indian IT and consulting players start productizing these control layers, they could become de facto standards for how enterprise AI is monitored and constrained across the Global South. That would give India leverage in AI governance debates that goes beyond its current role as a talent and services hub.