Indian companies are ready to spend more on artificial intelligence, but most of them still do not have the data to make it pay at scale. Nearly seven in 10 Indian businesses (69%) plan to increase AI spending over the next 12 months, yet only 3% say their enterprise data is fully ready to support AI at scale, according to the latest Dun & Bradstreet AI Momentum Survey released on 2 November 2026.

The India figure trails the global average of 8%, and it is a point lower than the 4% Dun & Bradstreet reported for India in its August 2026 edition, even as adoption and returns have moved up over the same period.

Key findings of the Dun & Bradstreet AI Momentum Survey for India

• Spending intent: 69% of Indian businesses expect to raise their AI budgets in the next 12 months, and nearly 70% expect AI to drive new products, services, business models or operational improvements in the coming quarter.
• Data readiness: 3% say their data is fully AI-ready, 42% mostly ready and 44% partially ready.
• Returns: 30% report broad or strong ROI from AI, 46% see returns in pockets of the business, and 10% say most pilots have scaled with clear gains.
• Maturity: More than 60% have moved beyond planning and piloting; 35% are scaling pilots into production and 26% have embedded AI across multiple core processes.
• Skills: Only 25% rate their workforce readiness as strong or very strong, while about half describe it as mixed.

Why data, not budgets, is India’s AI bottleneck

The survey draws a direct line between data foundations and business results. Indian businesses with fully AI-ready data were 6.3 times more likely to report broad or strong ROI than those whose data was only partially ready. In other words, the companies already getting the most out of AI are the ones that cleaned, connected and governed their data first.

That matters as Indian enterprises shift from chatbots and pilots to agentic AI, where autonomous systems act on company data in real time. Poor data quality that a human analyst could catch can quickly turn into a wrong action when an AI agent is in the loop. The finding echoes other recent research on how quickly Indian consumers are adopting AI tools, which raises the pressure on businesses to keep up.

What Dun & Bradstreet said

“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,” said Julian Prower, Executive Vice President, Global Business Operations & Transformation, and Managing Director & CEO, India & Taiwan, Dun & Bradstreet.

He added that the next chapter will be about moving “from AI adoption to AI advantage”, and that “trusted, connected and well-governed data, combined with an AI-ready workforce, will be critical to scaling AI responsibly and effectively.”

What it means for Indian CIOs

For technology leaders, the message is that the next rupee of AI budget may deliver more if it goes into data engineering, data governance and skilling rather than another model or pilot. Three practical priorities stand out:

• Fix the foundation: build a single, trusted view of customer, supplier and operational data before scaling AI use cases.
• Govern for agents: set clear rules on data lineage, access and quality, since AI agents will act on whatever data they are given.
• Close the skills gap: with only a quarter of firms confident in workforce readiness, training business and IT teams together is as important as buying tools.

About the survey

The Dun & Bradstreet AI Momentum Survey is a quarterly global study that tracks enterprise AI adoption, investment, deployment and business outcomes across about 10,000 businesses in 32 countries, with a dedicated India cut.

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