India's biggest obstacles to building a competitive AI ecosystem are shortages of specialised talent and poor data usability, rather than excessive market power by large technology companies. The study, Competition, Innovation, and Market Structure in India's AI Ecosystem, surveyed 308 stakeholders, including startups, business users and consumers. About 47.2% identified talent availability as a significant barrier to competitiveness, making it one of the top challenges alongside customer adoption.
The data problem is even more striking. 63.2% of AI developers surveyed identified a lack of data standardisation as their biggest challenge, considerably higher than concerns about copyright (44%) or data scarcity (42%). This suggests that India does not necessarily suffer from simply having too little data; instead, much of the available data is difficult to access, standardise, structure or use effectively for AI development. Only 15% of respondents considered government-held datasets readily accessible.
The study also highlights India's strong dependence on open-source AI. As many as 96.2% of AI startups and developers surveyed said they rely on open-source models or tools, with 62.3% describing that reliance as high. This is significant because it suggests Indian AI companies are building much of their innovation on accessible global technology rather than developing expensive foundation models entirely from scratch. That approach can lower barriers to entry, but it also makes access to high-quality data and skilled engineers even more important.
The broader message is that India's AI challenge is increasingly about execution capacity rather than simply technology availability. India has a large technology workforce and a growing startup ecosystem, but frontier AI requires specialised skills for training, deployment, evaluation and scaling. At the same time, companies need clean, standardised and accessible datasets to build reliable applications. The findings therefore point toward priorities such as AI talent development, better data standards, easier access to public datasets and stronger open-source infrastructure—areas that could matter more for India's AI competitiveness than simply trying to build bigger models.
