Indian healthcare is fast growing and with significant chunk of it being in small, fragmented, informal sector; Artificial Intelligence (AI) is pegged as a magical tool for a better healthcare system. There is an inclination to merely mimic the US approach in the on-going policy making and legislative exercises, which can have serious fallouts for Indian healthcare. India needs a different approach to suite her unique requirements. In this regard, each of the five stages in AI development lifecycle has been analyzed in the light of current on-ground realities. These boil down to three fold challenges of how to increase adoption of digital health, prevent data silos and create maximum value from data. Availability of quality data for value addition without barriers and restrictions is the common denominator for leveraging the full potential of AI. This requires liberal policies enabling secondary use of data in developing countries with rapidly growing healthcare sector akin to India. This has to be carefully balanced with data privacy and security. Restrictive healthcare data policies and laws can slow down adoption of digitization, perpetuate status-quo, be biased towards the incumbent players, cause Industry stagnation and thus will do more harm than good. It is therefore the data policies that will make or break AI in Indian healthcare.