New Delhi, April 10 -- AI safety is still widely misunderstood. Many teams continue to treat it as an extension of cybersecurity, add filters, tighten access, log activity, and assume the system is safe. But that approach only addresses part of the problem.

In 2026, understanding AI safety basics means recognising that safety is not just about protection mechanisms. It is about how AI systems are designed, deployed, and governed across their entire lifecycle.

This shift is especially relevant for teams building generative AI for startups, where speed often outpaces structured risk thinking.

Traditional controls still play a critical role. Access management, logging, infrastructure security, and API protections form the operational back...