Why Are 89% of Business Leaders Focusing on Data Modernization for AI?
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Synopsis
A recent report reveals a pressing need for Indian businesses to enhance data readiness, with 89% of data leaders advocating for data strategy modernization to ensure AI delivers its full potential. This article dives into the barriers faced and the strategic shifts necessary for impactful AI deployment.
Key Takeaways
- 89% of data leaders advocate for data modernization.
- 75% face pressure to derive value from data.
- 52% of organizations are adopting zero copy integration.
- 94% report issues with inaccurate AI outputs due to poor data.
- Data is estimated to be 26% siloed and inaccessible.
New Delhi, Dec 15 (NationPress) A significant need for improvement in data readiness among Indian enterprises has been highlighted, with 89% of leaders in data and analytics asserting that they must modernize their data strategies to enable AI to make a genuine impact, according to a report published on Monday.
The report, released by Customer Relationship Management Salesforce, indicates that 75% of business leaders are under growing pressure to extract value from data. However, they face challenges due to incomplete, outdated, and low-quality data, which stands as the primary obstacle.
This disparity between aspirations for data and the current reality is particularly critical in the age of agentic AI, the report emphasizes.
Technical teams are prioritizing timely, context-rich data, enhanced governance, and zero copy architectures to unlock trapped data that is scattered across systems.
Approximately 52% of organizations are implementing zero copy integration, allowing them to access data across various databases without the need to move, copy, or reformat it, as stated in the report.
Such organizations are 40% more likely to have fully integrated customer data sources and 22% more likely to achieve success with AI projects, according to the findings.
Moreover, about 9% of respondents indicated that translating business inquiries into technical queries is often prone to errors, while an overwhelming 95% expressed that performance would improve if data inquiries could be posed in their native language.
The report warns that inadequate data is undermining AI efforts, with 94% of leaders deploying AI in production reporting inaccurate or misleading results, and 50% noting significant resource wastage in training AI models with poor-quality data.
“AI cannot rectify the issues caused by incomplete data. For India to truly harness the potential of agentic AI, leaders must regard data as a strategic asset— unified, governed, and contextual,” stated Deepu Chacko, VP - Solution Engineering at Salesforce India.
Data and analytics leaders estimate that 26% of organizational data is siloed and inaccessible, with 75% believing that their most valuable insights are contained within this trapped data.
Point of View
It is imperative for Indian businesses to recognize the value of data as a strategic asset. The findings in this report serve as a wake-up call, highlighting the urgent need for modernized data strategies to enable AI to deliver genuine value. As we navigate this critical juncture, the focus must be on building a robust data foundation to harness the potential of AI.
NationPress
15/12/2025
Frequently Asked Questions
What percentage of business leaders believe data modernization is necessary for AI?
According to the report, 89% of data and analytics leaders believe that data modernization is essential for AI to deliver meaningful impact.
What is the main barrier to effective data utilization?
The primary barrier identified is the presence of incomplete, outdated, and poor-quality data.
How many organizations are adopting zero copy integration?
Approximately 52% of organizations are implementing zero copy integration to access data across various databases without the need to move or reformat it.
What impact does poor data have on AI efforts?
The report indicates that 94% of leaders with AI in production have reported inaccurate or misleading outputs, with 50% stating they wasted resources training AI models on bad data.
Why is data considered a strategic asset?
Data is regarded as a strategic asset because it can drive significant insights and value when unified, governed, and contextualized effectively.
