As the global enterprise landscape pivots from the experimental charm of GenAI to the operational rigour of autonomous agentic systems, the boardroom conversation has shifted from "what is possible" to "what is profitable." While 2024 was the year of the pilot, 2025 and the roadmap toward 2026 are being defined by a ruthless focus on "Radical ROI" and the structural integrity of data.
Recent data from Snowflake’s “The ROI of Gen AI and Agents 2026” report highlights a significant shift in the maturity of AI adoption. According to the global survey of over 2,050 leaders, the transition to production-scale AI is accelerating, with Indian enterprises emerging as frontrunners in both optimism and execution.
The ROI Shift: From Assistance to Autonomy
The real paradigm shift in the ROI equation is from GenAI, which is mainly a co-pilot of human activity, to Agentic AI, capable of independent execution of multi-step workflows. This represents a move for today’s organisations from incremental productivity gains to re-engineering business processes structurally.
"Companies today have higher expectations for concrete business results than before. In the end, it all boils down to ROI. Businesses investing in any technology will demand specific business outcomes," commented Mr. Vijayant Rai, Managing Director - India, Snowflake. He points to the clear expectation for strong ROI for GenAI in the Indian market, where 71% of respondents reported high ROI from their GenAI projects compared to a global average of 61%.
High expectations for ROI from GenAI projects are being accompanied by a quick transition to production. About a third of Indian respondents already have use cases in production, with another third expected to follow in the next 12 months. Globally, Snowflake's latest data indicates that more than 70% of its 13,300 customers, i.e., approximately 9,100 organisations, are now using AI features available on the platform. "The trend to use has been extremely rapid. Businesses are no longer experimenting; they are implementing AI at scale," he added.
The Data Dilemma: Why Pilots Stall
Despite the momentum, many CIOs find themselves hitting a "data wall." The transition from a successful pilot to a production-grade autonomous agent often fails not because of the AI model, but because of the data it consumes.
Mr. Rai identifies two systemic challenges in why a governed, high-quality data foundation remains the number one challenge for CIOs trying to move beyond the pilot phase. First is the tendency to "retrofit" AI into legacy systems. "AI needs to be designed across workflows, not added in a fragmented way," he explains. Second is the lack of semantic context. Without a unified, governed data layer, AI outputs remain inconsistent and difficult to scale. "Many AI projects fail because context and semantics are not built into the architecture. Even good data may not lead to the right outcomes," Mr. Rai warns.
The 2026 Roadmap: Secure-by-Design
As enterprises look toward 2026, the strategy is evolving toward a "secure-by-design" framework. This involves moving away from the "collect everything" mentality and toward a curated, holistic view of the data estate. Snowflake’s financial results for the fourth quarter of fiscal 2026 underscore this shift, reporting a 30% year-over-year growth in product revenue to $1.23 billion, driven largely by AI-led consumption.
Sridhar Ramaswamy, CEO of Snowflake, emphasised that the current era reflects a shift from AI promise to reality. "Snowflake delivered another strong quarter... reflecting the strength of our strategy focused on landing new customers and expanding them into strategic, long-term relationships," he stated during the earnings call.
Brian Robins, CFO of Snowflake, added that the company's momentum is fueled by deepening engagement. "We now have 733 customers spending more than $1 million on a trailing 12-month basis, and a record number exceeding $10 million," Robins noted, signalling that large-scale AI deployment is now a capital-intensive, high-stakes priority for the Global 2000.
Building the Connected Ecosystem
The final piece of the agentic puzzle is the integration of external data. In an autonomous future, internal data is rarely enough. To make accurate decisions, agents need access to third-party datasets and ecosystem-wide information.
The vision for 2026 is a connected data ecosystem where friction is minimised. By leveraging marketplaces to access external data without the traditional baggage of complex integrations, organisations can finally move toward scalable, agentic workflows.
For the modern CIO, the directive is clear: ROI is no longer a downstream concern. It is a byproduct of a disciplined data foundation. As Mr. Rai concludes, "Combined with AI capabilities, this enables scalable agentic workflows and prepares organisations for an autonomous, secure-by-design future."
