Indian Businesses AI Spending Data Readiness Explained: 69% Plan to Spend More, Only 3% Are Data-Ready

Illustrative image: a data centre — the infrastructure that AI spending buys into. This is not a photo of any surveyed company. Image: Wikimedia Commons / BalticServers, CC BY-SA 3.0.

TL;DR — Indian businesses AI spending data readiness explained in one line: 69% of Indian businesses plan to raise AI spending over the next 12 months, but only 3% say their enterprise data is fully ready to support AI at scale — so the money is moving faster than the foundations it needs, and firms with AI-ready data report strong returns 6.3 times more often.

📌 KEY HIGHLIGHTS

• The headline gap: 69% plan to increase AI spending in the next 12 months; only 3% describe their data as fully AI-ready, against 8% globally.
• Where the rest stand: 42% say their data is mostly ready and 44% say partially ready — so 86% sit in the middle, not at the finish line.
• Why it pays to fix data first: businesses with fully AI-ready data report broad or strong AI returns 6.3 times more often than those with only partially ready data.
• Adoption is past the pilot stage: over 60% have moved beyond planning, with 35% scaling pilots into production and 26% embedding AI across core processes.
• The second gap is people: only 25% report strong or very strong workforce readiness, while half call internal capabilities mixed.

Indian businesses AI spending data readiness explained: what the survey found

Dun & Bradstreet's AI Momentum Survey, reported in India on Monday 2 November 2026, captures Indian business at an awkward inflection point: ambition is no longer the problem, foundations are. Nearly seven in ten businesses plan to spend more on AI over the next year, and nearly 70% expect AI to drive new products, services, business models or operational improvements as soon as next quarter. But the survey's most quoted number is a small one — 3%. That is the share of surveyed Indian enterprises that describe their enterprise data as fully ready to support AI at scale, five points behind the 8% global figure.

The middle of the distribution tells the real story. Another 42% call their data mostly ready and 44% partially ready. In other words, almost every Indian business surveyed believes its data is somewhere on the journey — but only a tiny minority believes it has arrived. Dun & Bradstreet's India chief, Julian Prower, put it as a move "from AI adoption to AI advantage": as AI gets embedded deeper in operations and decisions, he said, "the quality of the underlying foundation will determine the quality of the outcomes," with trusted, connected, well-governed data and an AI-ready workforce the critical ingredients.

The numbers: ambition up, readiness lagging

Measure	India finding	Context
Plan to increase AI spending (next 12 months)	69%	Nearly 7 in 10 businesses
Data fully ready for AI at scale	3%	Global average: 8%
Data mostly / partially ready	42% / 44%	86% in the middle, not fully ready
Report broad or strong AI returns now	30%	46% see pockets of ROI; 10% say most pilots scaled with clear gains
Beyond planning / piloting	Over 60%	35% scaling pilots to production; 26% embedding AI across core processes
Strong / very strong workforce readiness	25%	Half describe internal capabilities as mixed

Illustrative image: a person using a phone-based AI tool — the kind of everyday AI use that enterprise data foundations have to support. Image: Wikimedia Commons, CC BY 2.0.

Why it matters for India readers

The return-on-investment link is the survey's most actionable finding. Firms with fully AI-ready data are 6.3 times more likely to report broad or strong returns than firms with only partially ready data. That reframes the 3% figure: it is not a statistic about IT hygiene, it is the reason two companies can buy the same AI tools and get very different results. For Indian businesses, the implication is sequencing — data cleanup, governance and workforce training before, or at least alongside, the next budget increase, rather than after it.

The timing sharpens the point. The survey lands in the same week India is debating the rules around AI: the telecom regulator TRAI has published draft guidelines on responsible AI use in telecom networks, with comments due by 27 November 2026, and the risks of unchecked AI agents were underlined by our AI agents spending cap bypass explainer, which showed what happens when agents act without proper guardrails. Spending more on AI while data and controls lag is exactly how those incidents happen — and the survey suggests most Indian firms know their foundations are not finished. Readers tracking the economics of AI may also want our informative compute AGI scaling explainer, on why measuring useful work, not total compute, is the better yardstick for AI investment.

Should you care?

✅ Verdict: Yes — if you run, buy or work with AI in India. The survey says the budget battle is already won; the data battle is not. ⏳ Before approving the next AI spend, ask the unglamorous question first: is our data actually ready, and are our people? The firms that answer yes are getting strong returns 6.3 times more often — that is the gap to close.

FAQs

What did the Dun & Bradstreet survey find about Indian businesses and AI spending?
It found 69% of Indian businesses plan to increase AI spending over the next 12 months, but only 3% describe their enterprise data as fully ready to support AI at scale, compared with 8% globally. Another 42% say their data is mostly ready and 44% partially ready.

Why does AI-ready data matter for returns on AI investment?
Because the survey links the two directly: businesses with fully AI-ready data report broad or strong AI returns 6.3 times more often than businesses whose data is only partially ready. Clean, connected, well-governed data is what turns AI pilots into consistent returns.

How many Indian businesses have moved AI beyond the pilot stage?
More than 60% have moved past initial planning and piloting, according to the survey — 35% are scaling pilots into production and 26% have embedded AI across multiple core business processes.

What is holding back Indian AI adoption — money or skills?
Neither money nor intent, on this evidence: budgets are rising and nearly 70% expect AI to drive new products or improvements next quarter. The constraints are data readiness (only 3% fully ready) and workforce readiness (only 25% strong or very strong, half mixed).

Takeaway: India Inc. is ready to spend on AI; it is not yet ready, by its own assessment, to get full value from it. Fix the data, train the people, then scale — in that order.

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Sources

BusinessToday, 2 Nov 2026 — Embracing AI advantage: 7 in 10 Indian businesses plan increased investment, finds study (Dun & Bradstreet AI Momentum Survey)
Free Press Journal, 2 Nov 2026 — 69% of Indian businesses plan to increase AI spending, but only 3% have fully AI-ready data (Dun & Bradstreet AI Momentum Survey)