NEW DELHI — A comprehensive empirical study examining India’s artificial intelligence landscape reveals that 85 percent of AI developers in the country now rely heavily on public cloud infrastructure to build, train, and deploy next-generation models.

The report, titled "Competition, Innovation, and Market Structure in India’s AI Ecosystem: An Empirical Assessment," was released on Wednesday by public policy think-tank The Dialogue. Based on extensive survey data collected from AI startups, core software developers, enterprise adopters, and end-consumers across India, the publication maps out current market dynamics, infrastructural access, and systemic bottlenecks across the domestic AI value chain.

Compute Access and the Affordability Challenge

A central finding of the research is that 74.5 percent of surveyed AI developers feel there is currently sufficient choice among compute providers in the market. This suggests that market concentration among hyperscalers has not yet restricted developer access to essential processing power.

However, researchers noted that access does not necessarily equal affordability. As workloads scale from foundational prototyping to complex training runs, compute costs remain a sensitive variable that could hinder smaller startups if left unaddressed by market mechanisms or policy interventions.

Open-Source Software Acts as Market Equalizer

The study underlines a profound reliance on open-source ecosystems, with 96.2 percent of AI developers reporting the use of open-source tools. Furthermore, 62.2 percent indicated a high level of dependence on non-proprietary frameworks, while over 79 percent view open-source foundational models as at least a partial substitute for closed, proprietary alternatives.

This strong tilt toward open-source architectures serves as a vital equalizer within India’s tech ecosystem, significantly lowering capital entry barriers for early-stage entrepreneurs and independent researchers who lack massive compute budgets.

Structural Bottlenecks: Data Usability and Talent Deficits

Despite robust adoption metrics, the report highlights critical operational hurdles that threaten long-term sector competitiveness:

  • Data Quality and Access: 63.2 percent of developers cited a lack of standardized data formats as their primary operational obstacle. Furthermore, only 15 percent reported that public or government-held datasets were readily accessible and usable, indicating that data formatting and interoperability are as crucial as sheer volume.

  • Talent Crunch: Human capital constraints continue to limit expansion, with 47.2 percent of developers classifying talent availability as a major barrier to scaling operations. The report emphasizes the urgent need for targeted skilling initiatives and improved talent mobility frameworks.

Enterprise ROI and Market Outlook

On the demand side, Indian enterprises report measurable productivity gains from integrating artificial intelligence into their workflows.

Approximately 85 percent of surveyed businesses reported a net positive return on their AI investments. Specifically, 61 percent pointed to enhanced decision-making capabilities, while 55 percent cited faster service delivery timelines. Crucially, 67 percent of enterprise leaders described the current costs of deploying AI solutions as reasonable relative to the operational efficiencies gained.

The Dialogue’s findings indicate that while India’s developer base has successfully leveraged cloud resources and open-source tools to build momentum, sustaining international competitiveness will require policy focus on data governance, specialized talent pipelines, and domestic compute capacity.