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A CII–ISB study reported that 65.8% of surveyed Indian micro, small and medium enterprises (MSMEs) used AI tools, while 21% used enterprise resource planning (ERP) or customised business software to manage operations. Those figures describe two different kinds of technology use—not a measure of how many firms have integrated AI into their operations—and they are voluntary survey results, not estimates for all Indian MSMEs.
What the two percentages measure
The contrast in the headline is between reported use of AI tools and reported use of ERP or customised software for operational management. AI tools can be used for particular tasks; ERP and customised business software are categories of systems used to manage business operations. The study account does not provide exact definitions or questionnaire wording for either category, so it is not possible to determine precisely what respondents counted as use.
| Measure | Reported result | What it describes |
|---|---|---|
| AI-tool use | 65.8% of surveyed enterprises | Respondents who said they used AI tools; the specific tools and usage threshold are not stated. |
| ERP or customised business software | 21% of surveyed enterprises | Respondents who said they used this software to manage operations. |
Because the measures cover different categories, the percentages do not show that AI use is more effective, more deeply integrated or more valuable than business software. Nor do they establish that AI users lack operational software: the reported account does not give respondent-level overlap between the two groups or measure business outcomes caused by AI.
What surveyed MSMEs said they used AI for
The account reports three AI-use categories: business communication (34.9%), content creation (22.3%) and training (18.9%). It does not say whether respondents could select more than one category, so these figures should not be added together or treated as mutually exclusive shares.
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Who was surveyed—and what the results can show
Business Standard’s October 13, 2026 account of the CII–ISB study describes an analytical sample of 2,919 confirmed MSMEs across all 36 Indian states and Union Territories and 40 industry sectors. That breadth gives the results a wide respondent spread, but it does not make the sample representative of the country’s MSMEs.
The survey was voluntary and was not probability-weighted to represent all Indian MSMEs. The percentages should therefore be read as findings among participating enterprises, not as national adoption rates. A large sample and coverage across many regions and industries do not remove the limits of voluntary, non-probability-weighted participation.
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The available account does not state the exact fieldwork dates, recruitment procedure beyond voluntary participation, or the precise question wording and definitions. The underlying report was not independently available in the sources cited by the account. These limits make it inappropriate to infer how often or how extensively AI was used, or to generalise the reported rates to every MSME in India.
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The article also reports findings on other aspects of participating businesses: 74.9% were aware of at least one government scheme, while 42.6% said they used one. It says 32% held recognised certifications; among respondents without certification, 50.9% reportedly said customers did not require it and 30.4% cited lack of awareness.
In an export-focused analytical sample, 11.8% of MSMEs served international markets. That figure applies to the restricted export-focused sample, not necessarily to all 2,919 enterprises.
The study account identifies working-capital constraints, delayed customer payments and difficulty accessing finance as recurring challenges. It reports recommendations for stricter enforcement of payment timelines, wider use of TReDS, invoice financing and short-term bridge credit. It also describes five proposed national missions covering liquidity and payment discipline; an integrated digital journey for MSMEs; technology adoption with implementation support; skills development; and market access, quality and green competitiveness. These are recommendations attributed to the study, not independently demonstrated policy outcomes.
Rank #4
- Author: Bungay Stanier, Michael.
- Publisher: Page Two
- Pages: 244
- Publication Date: 2016-02-29
- Edition: 1
What the headline does—and does not—tell business owners
The findings suggest that respondents reported AI-tool use more often than use of ERP or customised software to manage operations. They do not reveal whether an individual business should adopt AI, which software it needs, or whether either technology will improve its results. The study account does not report a causal evaluation, compare implementation approaches or identify a specific technology provider.
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Source
The figures and study context above are reported in Business Standard’s October 13, 2026 account of a CII–ISB study. The account is the available source for the survey results; its figures should be understood with the participation and measurement limits described here.
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