89% of India’s Tech Leaders Prioritise Data Modernisation for AI Success

Salesforce, the world’s #1 AI CRM*, has announced findings from its latest State of Data and Analytics report, revealing that 89% of India’s data and analytics leaders believe their organisations must modernise their data strategies for AI to deliver meaningful impact. While 75% of business leaders are under increasing pressure to drive business value with data, the report highlights that incomplete, outdated, and poor-quality data remains their biggest barrier. This gap between data ambition and data reality becomes even more critical in the agentic AI era.

To close the gap, savvy technical leaders are focusing on the fundamentals: timely, context-rich data, stronger governance and zero copy  architectures that unlock trapped, distributed data regardless of where it resides. On their journey to becoming agentic enterprises, they’re also embracing emerging solutions like agentic analytics, that bring reliable insights into the flow of work.

Deepu Chacko, VP - Solution Engineering at Salesforce India, said: “AI cannot fix what incomplete data creates. For India to truly unlock the promise of agentic AI, leaders must treat data as a strategic asset — unified, governed, and contextual. The companies that modernize their data foundations today will be the ones that scale AI responsibly and lead the economy tomorrow. Agentic AI isn’t the next technology — it's the next revolution. AI agents handle routine tasks so humans can focus on creativity, relationships, and impact”.

Key data from the report:

• Existing data foundations strain to support business ambitions: Nearly two-thirds of business leaders (66%) describe their organizations as data-driven. Yet just as many (52%) data and analytics leaders say their companies struggle to drive business priorities with data, exposing a gap between data maturity perceptions and reality.
• About half (51%) of business leaders say they can reliably generate timely insights.
• Nearly half (54%) of data and analytics leaders say their companies occasionally or even frequently draw incorrect conclusions from data with poor business context.
• Incomplete, out-of-date, or poor-quality data remains the number #1 factor preventing organizations from being truly "data-driven."
• Poor data derails the path to becoming an agentic enterprise: AI has quickly become the top data priority — and the biggest stress test for existing data foundations. For Indian respondents, AI capabilities have consistently ranked as the #1 data priority, same as they did in 2023's State of Data and Analytics report.
• As a result, 56% of data and analytics leaders feel pressure to implement AI quickly.
• Yet 39% lack full confidence in the accuracy and relevance of their AI outputs, likely because of the disconnected, out-of-date data it draws from.
• While 89% of data and analytics leaders theoretically agree that AI's outputs are only as good as its data inputs, their reality is a bit more complicated. Data and analytics leaders estimate over a quarter (25%) of their organizational data is untrustworthy.
• Businesses are feeling the consequences of training AI on faulty data foundations.
• 94% of data and analytics leaders with AI in production say they've experienced inaccurate or misleading AI outputs.
• More than half of data and analytics leaders (50%) at companies training or fine-tuning their own models report they've wasted significant resources doing so with bad data.

Even high-quality data is useless if it’s trapped.

89% of data and analytics leaders believe unified data is key for meeting customer expectations, but struggle with trapped data As a result:

• Data and analytics leaders estimate that 26% of their company’s data is siloed, inaccessible, or otherwise unusable.
• More concerning, 75% of data and analytics leaders believe their most valuable business insights reside within this inaccessible 26%.
• The ramifications are widespread, with over 8 in 10 data and analytics leaders citing reduced AI capabilities, obscured customer views, reduced personalization, and missed revenue opportunities as a result.