Big Tech has AI, but Indian MSMEs need something more—Desi AI
Many micro, small, and medium enterprises (MSMEs) in the country feel that the existing
AI
solutions are not tailored to their specific needs, and they require products that are simple, affordable, and customised for different segments of the
MSME
sector. Experts and industry stakeholders emphasise that this differs from the needs of larger firms, highlighting the necessity of developing sector-specific and needs-based AI solutions for MSMEs.
In May 2025, NITI Aayog released a report titled 'Enhancing Competitiveness of MSMEs in India', which underscored the challenges faced by MSMEs in leveraging technology and innovation to drive growth. The report identifies key areas of concern, including limited access to formal credit, barriers to technology adoption, and low awareness of government schemes.
According to the NITI Aayog report, 59% of India's MSMEs face 'financial limitations that hinder their ability to invest in AI, which include the high costs of AI tools, computer infrastructure, and training.' The report also said that 91% of India's MSMEs felt that 'AI should be democratically available and affordable'.
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Existing AI solutions often don't align with specific operational needs of MSMEs, says Anoop G Prabhu, CTO and Co-founder of Vehant Technologies.
MSMEs span multiple sectors, each with unique challenges and workflows, requiring tailored solutions, says Prabhu. 'A MSME might need customer flow analytics, while a manufacturing unit may prioritise workers' safety compliance and process monitoring. Similarly, with other AI solutions, logistics players may focus on PPE detection, intrusion, fire & smoke detection, and cargo scanning through x-ray baggage scanner systems. These customised and industry-fit AI solutions will deliver effective results across diverse and specialised use cases,' Prabhu explains.
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Experts assert that the Indian MSMEs should prioritise 'Desi AI'—AI solutions made in India for India. If Indian tech companies don't focus on customisation and cost-effectiveness, a large segment of MSMEs will likely remain underserved, missing out on the opportunity for transformation, they add.
Similarly, Manoj Dhanda, Founder and CTO of Utho Cloud, agrees that MSMEs' way of working is very different from big companies. Most AI models cater to large enterprises with extensive resources, but small businesses have different needs, says Dhanda, adding that they require AI solutions that are accessible, affordable, easy to implement, and tailored to their specific use cases.
'That's why customisation becomes important not in the AI model itself but in how it's used. For example, say they want to make a chatbot. Now bots work in general, but someone still needs to train or configure them according to the specific business flow, like what messages to send, how to respond, and what kind of customer data to pick,' adds Dhanda.
Sushant Rabra, Partner and Head of Digital Strategy at KPMG in India, emphasises that tailored AI solutions, rather than generic imports, are key to unlocking productivity, competitiveness, and sustainable growth for MSMEs. This approach can drive the next wave of innovation in the MSME sector, he adds.
'The priority must be on scalable, plug-and-play solutions that minimise complexity while maximising business value. Delivering measurable impact through accessible, purpose-built AI will define the next chapter of India's enterprise transformation,' adds Rabra.
Kanishk Maheshwari, Co-founder & Managing Director, Primus Partners, agrees that each specific MSME sector requires a different set of AI tools to maximise its productivity and efficiency. 'A textile MSME would prefer tools that would aid in inventory prediction, while a food processing unit would probably benefit more from tools that help in shelf-life tracking. In such a scenario, having custom-built tools to cater to unique issues faced by different MSMEs would help maximise the benefit of AI for them,' adds Maheshwari.
Scaling up Desi AI solutions
Experts say that to effectively scale AI in the MSME sector, solutions should be locally developed to address specific needs, transparently priced for better cost management and supported by reliable on-ground service for ongoing assistance.
Prabhu says that the AI solutions can be scaled for growing MSMEs by focusing on modularity, affordability, and ease of integration. 'We believe the key lies in building AI products that are not only powerful but also flexible and adaptable to different stages of a business's growth. Our smart city solutions are near-edge compatible, cost-efficient, cloud operable, and hybrid model and support cloud-based architecture,' adds Prabhu.
Dhanda highlights that the biggest need for AI adoption is cloud infrastructure, the backbone of AI. This foundational infrastructure is crucial for supporting AI solutions, says he. 'In India, we have over 138 operational data centres that can handle thousands of GPU workloads; we can easily understand how much data and how many AI models we can host. So, we have a large data centre infrastructure, and any AI workload can be scaled very easily, whether it's for MSMEs, corporates, or any other community. Nowadays, with the kind of infrastructure we have, you don't need to invest in capex,' adds Dhanda.
Experts say that scaling AI adoption among MSMEs requires a three-pronged approach: co-creation of solutions with MSMEs to ensure alignment with their needs; public-private partnerships to build robust support infrastructure; and affordability through government-backed incentives.
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