Dun & Bradstreet AI survey: 69% of Indian firms to spend more, 3% data-ready

About 69% of Indian businesses plan to increase their spending on artificial intelligence over the next 12 months, but only 3% say their company data is fully ready to support AI at scale, according to Dun & Bradstreet's AI Momentum Survey, released on Monday, 2 November 2026. Globally, 8% of businesses described their data as fully AI-ready. The survey found a strong link between data and results: Indian businesses with fully AI-ready data were 6.3 times as likely to report broad or strong returns on their AI investment as those whose data was only partly ready. The global survey covers 10,000 businesses in 32 countries every quarter.

Indian companies have been among the most enthusiastic about AI. Boards want it, vendors are selling it, and many firms have run trials of chatbots, document tools and forecasting systems. This survey points to the gap between that enthusiasm and what is needed to make AI pay off at scale.

AI systems are only as good as the data they are fed. For a business, being "data-ready" means that its records on customers, suppliers, products and finances are accurate, consistent, connected across departments and properly governed, so that an AI tool can use them safely. In many Indian companies, especially older and mid-sized ones, data sits in separate systems, spreadsheets and paper files, with different formats and gaps. An AI model built on that kind of data tends to give unreliable answers, which is why so many pilots never move into everyday use.

The survey's return-on-investment finding makes the point in business terms. The small group of firms that have sorted out their data are far more likely to say AI is paying off. For the rest, the message is that the next rupee spent on AI may be better spent on cleaning, connecting and managing data than on new tools.

For technology vendors and IT services companies, this is also an opportunity: data engineering, integration and governance work is the unglamorous layer that has to be built before AI can deliver. For managers, it suggests measuring AI projects by whether the underlying data is ready, not only by the number of pilots launched.

Peepals calculation: the global share of fully AI-ready businesses (8%) is about 2.7 times India's (3%) (8 divided by 3). India's share fell by one percentage point from the 4% reported in the August 2026 findings. Our calculation from the reported figures; the survey did not explain the change.

Short-term: Companies planning bigger AI budgets for the coming year are likely to face pressure to show results, which puts the spotlight on data quality and governance.

Long-term: Firms that invest in organising their data now are better placed to get returns from AI; those that skip it risk spending more on tools that do not deliver.

Who is affected: Indian businesses of all sizes planning AI projects, their technology and data teams, IT services and software vendors, and employees whose work AI tools are meant to support.

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