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A voluntary survey of 2,919 Indian micro, small and medium enterprises (MSMEs) found that 65.8% said they used artificial-intelligence tools, while 21% said they used enterprise-resource-planning (ERP) systems or customised business software to manage operations. The figures, reported by Business Standard on October 13, 2026, describe participating businesses—not a statistically representative estimate of all Indian MSMEs.
What the two percentages actually measure
The headline compares two different forms of technology use. “AI use” covers respondents who said their enterprise used AI tools. “Business-software use” refers specifically to ERP or customised software used to manage operations. Because the categories measure different things, the 65.8% figure cannot be read as evidence that 65.8% of MSMEs have integrated, company-wide digital systems.
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| Measure | Reported share | What it represents |
|---|---|---|
| AI-tool use | 65.8% | Surveyed enterprises reporting use of AI tools |
| ERP or customised business software | 21% | Surveyed enterprises using software to manage operations |
The report does not provide the questionnaire wording or operational definitions for either measure. It also does not say whether respondents could select more than one AI-use category.
How surveyed MSMEs said they used AI
Among the AI-related uses reported in the account, business communication was the largest category at 34.9%. Content creation accounted for 22.3%, and training for 18.9%.
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- Business communication: 34.9% of surveyed enterprises.
- Content creation: 22.3%.
- Training: 18.9%.
These percentages should not automatically be added together or treated as a ranking of exclusive choices. The published account does not establish whether an enterprise could report several uses, nor whether the percentages use all surveyed MSMEs or only those reporting AI use.
Why AI use can outpace operational software
AI tools can often be adopted one task at a time—for drafting messages, producing marketing material or helping with staff training—without changing how a business records sales, inventory, purchasing, payroll or cash flow. ERP and customised systems require a broader decision: selecting or building software, migrating data, defining processes, training staff and maintaining the system.
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That difference explains how a business may use an AI assistant while still relying on spreadsheets, paper records or separate applications for core operations. The survey does not show that AI use is ineffective, casual or unprofitable. It also does not measure outcomes caused by AI, such as productivity, revenue or cost savings. It reports technology-use responses.
How representative is the study?
The analytical sample contained 2,919 confirmed MSMEs across all 36 Indian states and Union Territories and 40 industry sectors. That geographic and sector spread gives the findings broad coverage among participants, but it does not turn the results into a national adoption rate.
Participation was voluntary and the survey was not probability-weighted. Businesses that chose to respond may differ systematically from those that did not—for example, in connectivity, formal registration, interest in technology or access to support. Consequently, the 65.8% and 21% figures should be described as reported results for surveyed enterprises. A larger sample alone would not remove the selection limitation.
Other findings reported alongside technology adoption
The wider study found that 74.9% of surveyed MSMEs were aware of at least one government scheme, while 42.6% said they used one. It reported that 32% held recognised certifications. Among respondents without certification, 50.9% said customers did not require it and 30.4% cited lack of awareness.
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- Author: Bungay Stanier, Michael.
- Publisher: Page Two
- Pages: 244
- Publication Date: 2016-02-29
- Edition: 1
In a separate export-focused analytical sample, 11.8% of MSMEs served international markets. That percentage uses the restricted export-focused denominator and should not be generalized to every enterprise in the main sample.
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What problems and policy measures the report highlights
According to the Business Standard account, the study identifies working-capital constraints, delayed customer payments and difficulty accessing finance as recurring MSME problems. It recommends stricter enforcement of payment timelines, wider use of the Trade Receivables Discounting System (TReDS), invoice financing and short-term bridge credit.
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The report also proposes five national missions, as reported by the newspaper:
- Liquidity and payment discipline.
- An integrated digital journey for MSMEs.
- Technology adoption backed by implementation support.
- Skills development.
- Market access, quality and green competitiveness.
These are recommendations attributed to the study; the published account does not independently evaluate whether each measure would produce the proposed results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the headline does—and does not—tell business owners
The contrast is a signal that basic AI access and integrated operational digitisation are not the same milestone. An MSME considering software should first map the processes it needs to control—orders, stock, invoicing, receivables, purchasing and reporting—then assess data quality, staff capacity, implementation help and financing. Adopting an AI tool alone will not create a shared operational record, while installing an ERP system without training and process ownership can leave the system unused.
For policymakers and support providers, the reported gap points toward implementation assistance, skills and finance rather than simply promoting more tools. However, the survey cannot establish how many enterprises combine AI with ERP, which systems they use, how frequently they use them or whether adoption improved performance.
Important unanswered questions
- The exact fieldwork dates and recruitment procedure beyond voluntary participation.
- The questionnaire wording and definitions of “AI tools,” “ERP” and “customised business software.”
- Whether AI-use categories were mutually exclusive.
- The proportion of respondents using both AI tools and operational software.
- Any measured effects on productivity, revenue, costs or resilience.
The underlying CII–ISB report was not independently located in the available publication listings, and no named researcher quotation was provided in the newspaper account. Those details should be verified before treating the figures as a population estimate or drawing causal conclusions.
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