New Ecosystem research highlights how Indian enterprises are moving from AI pilots to value-driven adoption

As artificial intelligence moves beyond experimentation, Indian enterprises are increasingly focused on translating AI investments into measurable business outcomes. A new research report by Ecosystem, titled “Making AI Work: Strategy, Data, and the Power of Ecosystems,” examines how organisations across the Asia-Pacific and Japan (APJ) region, including India, are adopting Agentic and Generative AI, and the challenges that continue to slow value realisation.

Commissioned by Snowflake, the study draws insights from more than 700 business and IT leaders across APJ. The findings indicate that Indian organisations are actively piloting and deploying AI across customer-facing and operational functions, but continue to face structural challenges around data, governance and return on investment.

Customer experience leads AI use cases in India

According to the research, Indian enterprises are prioritising AI initiatives that directly impact customers. The most commonly evaluated use cases include interacting with customers across channels (69%), generating marketing content (65%), and improving chatbot responses (58%). AI is also being deployed across marketing and communications, operations and IT functions, signalling a shift from siloed experimentation to broader organisational use.

However, while near-term efficiency gains remain important, enterprise conversations are increasingly focused on the long-term strategic value of AI. As organisations attempt to scale beyond pilots and re-engineer processes to become AI-native, demonstrating clear ROI has emerged as a persistent challenge.

The research found that 77% of Indian organisations cite ROI measurement as the biggest barrier to scaling AI initiatives, while 66% expressed concerns around regulatory and compliance requirements.

Commenting on the findings, Vijayant Rai, Managing Director – India at Snowflake, said, “Business leaders are shifting towards determining real business value from AI. As AI goes mainstream and organisations move from isolated applications to AI-driven co-innovation, it becomes more important than ever to build a trusted, scalable, and reliable data foundation before AI can succeed. To embed AI deeply within their business strategy, enterprises need structured roadmaps and guidance to translate insights into solutions to derive optimum results.”

Data readiness remains a key constraint

Despite growing interest in AI, foundational data challenges continue to limit progress. Indian respondents identified data quality (60%), data security (54%) and data accessibility (50%) as the primary roadblocks to effective AI adoption.

These constraints reflect operational realities on the ground. According to the study, only 23% of Indian organisations have fully integrated AI into their overall business strategy, highlighting a gap between ambition and execution.

The research also points to the growing importance of unstructured data in AI initiatives. Across all surveyed countries, only 38% of organisations have invested in technologies that enable analysis of unstructured data, limiting their ability to support more advanced AI use cases.

Ecosystems and partnerships gain importance

As enterprises grapple with data complexity and governance challenges, the research highlights a growing reliance on partner ecosystems. According to the findings, 83% of Indian organisations are either engaging with or planning to engage technology partners to support AI strategy, implementation and data readiness.

Dhiraj Narang, Director and Head of Partnerships – India at Snowflake, said, “As organisations in India are beginning to recognise the strategic value of AI, they are actively turning to the partner ecosystem for domain expertise, platform skills, trusted advice, and proven frameworks to turn their AI ambitions into reality. To leverage AI for business growth, it is essential to have a strong, connected ecosystem including cloud providers, advisory firms, system integrators (SIs), value-added resellers, data and application providers, to drive ROI from their AI investments.”

Moving from experimentation to impact

To help organisations overcome ROI challenges, the research outlines a set of best practices focused on scaling AI responsibly. These include balancing short-term wins with long-term value creation, measuring ROI across the full AI lifecycle, integrating fragmented AI tools, strengthening data and skills foundations, and recognising the cost of delaying AI adoption.

Taken together, the findings suggest that Indian enterprises are entering a more mature phase of AI adoption—one where success is less about deploying models and more about execution discipline, data readiness and ecosystem collaboration. As AI becomes embedded into core business processes, organisations that align strategy, data and governance are likely to be better positioned to turn AI ambition into sustained business value.