69% of Indian firms plan to raise AI spending, but data gap holds back scale
Synopsis
Seven in 10 Indian businesses plan to raise AI budgets, yet only 3% have enterprise data that is fully AI-ready — less than half the global average of 8%. A Dun & Bradstreet report quantifies the cost of that gap: firms with fully ready data are 6.3 times more likely to report strong ROI. India's AI ambition is real, but the data foundation beneath it remains precarious.
Key Takeaways
69 per cent of Indian businesses plan to increase AI spending over the next 12 months , according to a Dun & Bradstreet report released on 2 November 2026 .
Only 3 per cent of Indian firms describe their enterprise data as fully AI-ready, compared with 8 per cent globally.
44 per cent of Indian businesses describe their data as only partially ready, and 42 per cent as mostly ready.
Firms with fully AI-ready data are 6.3 times more likely to report broad or strong returns on AI investment than those with partially ready data.
More than 60 per cent of respondents have moved beyond planning; 35 per cent are scaling pilots to production and 26 per cent have AI embedded across core processes.
Nearly seven in 10 Indian businesses — 69 per cent — plan to increase artificial intelligence (AI) spending over the next 12 months, yet only 3 per cent describe their enterprise data as fully ready to support AI at scale, according to a report released on Monday, 2 November 2026 by data and analytics firm Dun & Bradstreet. The findings point to a widening ambition-execution gap that could blunt returns on what is shaping up as a major technology spending cycle.
The Data Readiness Problem
The report's starkest finding is the chasm between AI investment intent and data preparedness. While 69 per cent of Indian firms intend to raise AI budgets, just 3 per cent rate their enterprise data as fully AI-ready — well below the 8 per cent global average. A further 42 per cent described their data as mostly ready, and 44 per cent as only partially ready, meaning the overwhelming majority are attempting to scale AI on an incomplete foundation.
The stakes are quantifiable. According to the report, businesses with fully AI-ready data were 6.3 times more likely to report broad or strong returns on investment compared with companies whose data was only partially ready. That multiplier underscores why closing the readiness gap is not a back-office concern but a strategic priority.
Where Indian Businesses Stand on AI Adoption
Despite the data shortfall, Indian enterprises have moved decisively beyond the planning stage. More than 60 per cent of respondents have progressed past ideation: 35 per cent are scaling pilot projects into full production, and 26 per cent report AI embedded across multiple core business processes. Separately, nearly 70 per cent of Indian firms believe AI will contribute to new products, services, business models, or operational improvements within the next quarter.
This positions India as a high-ambition market, even if the underlying data infrastructure has not yet caught up with the deployment pace.
What Dun & Bradstreet Said
Julian Prower, Executive Vice President of Global Business Operations & Transformation and Managing Director & CEO for India & Taiwan at Dun & Bradstreet, described the moment as a critical turning point. 'India has reached an exciting inflection point in its AI journey. The ambition is clearly visible, and businesses are increasingly seeing tangible returns from their AI investments,' he said.
Prower added that the next phase of growth would hinge on the quality of underlying data infrastructure. 'The next chapter will be about moving from AI adoption to AI advantage. As enterprises embed AI more deeply across operations and decision-making, the quality of the underlying foundation will determine the quality of the outcomes,' he said.
Why the Gap Matters for India's AI Ambitions
India's corporate AI push is unfolding against a backdrop of significant government-level investment in digital infrastructure and a globally competitive talent pool in data science. Yet the Dun & Bradstreet findings suggest that structural data quality issues — fragmented legacy systems, inconsistent data governance, and siloed enterprise architectures — remain the primary constraint on translating intent into measurable business value.
Notably, India's 3 per cent fully-ready rate compares unfavourably even with a global average that itself reflects widespread unpreparedness. This is not merely a technology problem; it is a data governance and organisational readiness challenge that will require deliberate investment alongside AI tools themselves.
What Comes Next
With AI spending set to accelerate across sectors, the businesses that address data readiness systematically — rather than deploying AI models on messy inputs — are likely to widen their competitive advantage. The report signals that the coming year will be decisive: firms that treat data infrastructure as a prerequisite, not an afterthought, stand to capture the 6.3x returns differential that the research identifies. All others risk compounding the current gap.
Point of View
But the 3 per cent data-readiness figure is the real story and it is sobering. India is effectively building on sand: deploying AI tools at scale while the underlying data infrastructure remains fragmented and ungoverned. The 6.3x returns differential is not an abstraction; it is the compounding cost of skipping the foundational work. What is missing from the mainstream coverage is that this is as much a management and governance failure as a technology one — CIOs and CFOs have co-signed AI budgets without committing equivalent resources to data quality programmes. Until boards treat data readiness as a capital investment rather than an IT hygiene issue, the ambition-execution gap will widen even as spending rises.
NationPress
2 Nov 2026
Frequently Asked Questions
What did the Dun & Bradstreet AI report on India find?
The Dun & Bradstreet report found that 69 per cent of Indian businesses plan to increase AI spending over the next 12 months, but only 3 per cent consider their enterprise data fully ready to support AI at scale. The report also found that firms with fully AI-ready data are 6.3 times more likely to report strong returns on investment.
How does India's AI data readiness compare globally?
India's data readiness significantly lags the global average. Only 3 per cent of Indian firms describe their data as fully AI-ready, compared with 8 per cent globally. A further 44 per cent of Indian firms describe their data as only partially ready.
Why does data readiness matter for AI investment returns?
According to the Dun & Bradstreet report, businesses with fully AI-ready data are 6.3 times more likely to report broad or strong returns on AI investment than companies with only partially ready data. Poor data quality limits the accuracy, reliability, and scalability of AI models, directly undermining ROI.
How far along are Indian businesses in actually deploying AI?
More than 60 per cent of Indian firms surveyed have moved beyond the planning stage. Of these, 35 per cent are scaling pilot projects into production and 26 per cent report that AI is already embedded across multiple core business processes.
What sectors or business areas does the AI impact cover?
Nearly 70 per cent of Indian firms believe AI will contribute to new products, services, business models, or operational improvements within the next quarter, suggesting broad cross-sector applicability rather than concentration in any single industry.
