What if a small Indian manufacturer could reduce unexpected machine breakdowns by 40% without completely changing its production setup?
This is already happening. A mid-sized Indian industrial gearbox manufacturer saw this improvement using artificial intelligence (AI) to keep track of its machines and spot possible problems before they occurred.
For years, AI adoption was largely associated with big corporations that had the budgets, technology and specialised teams to implement it. That is changing. Today, Indian micro, small and medium enterprises (MSMEs) are finding practical ways to use AI for manufacturing, customer research, marketing and business expansion.
These businesses are not always building complicated AI systems. Some are using easy-to-use tools to understand customers, while others are using machine learning to improve production and day-to-day efficiency.
The following three case studies explore how Indian businesses are approaching AI, what they have achieved or are working towards, and what other MSMEs can learn from their experiences.
Why Are Indian MSMEs Turning to AI?
India has more than 63 million MSMEs, making the sector a major contributor to employment, manufacturing and economic activity. However, many smaller businesses operate with limited budgets, small teams and relatively basic digital systems.
This creates everyday challenges. Business owners spend hours managing customer enquiries, preparing documents, researching markets and handling repetitive office tasks. Manufacturers also deal with equipment failures, production delays and quality-control issues.
AI offers ways to address some of these problems without necessarily requiring large technology investments.
For example, generative AI tools can help businesses prepare product descriptions, analyse customer feedback and draft marketing content. Manufacturing companies can use machine learning to monitor equipment, identify defects and predict when machines need maintenance.
The World Economic Forum’s 2025 AI Playbook for India’s MSMEs highlights the opportunity to make AI more accessible to smaller businesses. However, success depends on choosing tools that solve real business problems rather than adopting technology simply because it is popular.
The following examples demonstrate how different MSMEs are approaching this opportunity.
3 Real Examples of MSMEs Using AI to Grow
Case Study 1: How an Indian Gearbox Manufacturer Used AI to Reduce Machine Downtime
Manufacturing businesses depend on machinery working reliably. Even a minor machine failure can interrupt production, increase maintenance costs and delay customer orders.
A mid-sized Indian industrial gearbox manufacturer was facing repeated machine problems involving bearing corrosion, wear and tear on gear surfaces and problems with the lubrication system. These issues were affecting production and increasing maintenance costs.
Instead of relying only on regular maintenance schedules, the company introduced an AI-powered system that predicts machine problems with the support of a technology partner.
The system used temperature and vibration sensors with machine-learning tools. These sensors kept track of important machine readings, while the algorithms analysed collected data to identify early warning signs of possible breakdowns.
This allowed maintenance teams to look into problems before they led to major equipment breakdowns.
The results were significant:
- 40% reduction in unplanned machine breakdowns.
- 30% decrease in maintenance costs.
- Improved equipment reliability and production efficiency.
These results were documented in the World Economic Forum’s Transforming Small Businesses: An AI Playbook for India’s MSMEs.
What can other MSMEs learn from this?
Predictive maintenance is especially useful to businesses that depend on expensive machinery and face repeated machine breakdowns.
Rather than immediately spending money in complete factory automation, manufacturers can identify essential machines, review the data their machines provide and explore tools that monitor specific machines.
The important lesson is that AI does not always need to transform an entire business. Solving one expensive operational problem can deliver meaningful value.
Case Study 2: How Ansh Creations Used AI to Understand Customers and Develop Better Products
AI is not limited to manufacturing. Small consumer brands can also use it to understand customer preferences and improve their decisions about new products.
Ansh Creations, a skincare business based in Ahilyanagar, Maharashtra, is an interesting example.
Founder Aarti Joshi started using AI tools to improve activities that were already part of her everyday business tasks. These included writing product descriptions, preparing Instagram captions and understanding customer requirements.
She started using tools such as ChatGPT, Google Gemini and DeepSeek.
One particularly useful application involved analysing customer reviews and online market discussions. Instead of manually reviewing large amounts of customer feedback, AI helped identify recurring customer preferences and skincare needs.
The findings showed that customers wanted for more specialised products catering to dry, oily and sensitive skin. This helped the business refine its product offerings and improve product-market alignment.
According to the MCCIA report Empowering MSMEs with AI: Experiences from 100 Champions, the business reported nearly a 30% improvement in product-market alignment.
What can other MSMEs learn from this?
Small businesses often have valuable customer information but limited time to analyse it.
AI-assisted research can help identify common complaints, product preferences and changing customer needs. This information can support decisions about product development, marketing messages and customer engagement.
However, AI-generated insights should always be checked against genuine customer feedback. The technology can identify patterns, but business owners still need to understand their customers and make the final decisions.
Ansh Creations demonstrates that AI can support growth even without advanced manufacturing systems or large technology investments.
Case Study 3: How Supertech Laminates Used AI to Strengthen Its Export Strategy
For many Indian manufacturers, business growth is not limited to increasing domestic sales. International markets can offer opportunities to reach new customers and expand revenue.
However, entering export markets requires businesses to understand international demand, identify potential opportunities and make informed commercial decisions.
Supertech Laminates, an Indian manufacturing business, provides an example of how AI-assisted insights can support this process.
According to the Wadhwani Foundation, the company began using AI-powered tools to refine its export strategy. The objective was to make better use of business data and identify opportunities for international expansion.
The company is targeting markets including South Asia and the UAE as part of its broader expansion ambitions.
Its stated goal is to reach $10 million in revenue by 2028.
It is important to understand that this is a future business target, not revenue already achieved through AI adoption.
The published account does not specify every AI tool or provide an independently measured figure for revenue directly generated by AI. Nevertheless, the example highlights an important application: using better data and AI-assisted insights to support business expansion decisions.
What can other MSMEs learn from this?
Manufacturers considering international expansion can use AI-assisted research to explore potential markets, understand customer segments and organise information about competitors and demand.
These insights can make early research more efficient. However, they should complement actual market validation, export regulations, pricing analysis and knowledge of local business conditions.
For an MSME looking beyond its existing customer base, AI can become a useful decision-support tool rather than simply another technology expense.
What Do These Three MSME Case Studies Teach Us About AI Adoption?
These examples show that there is no one-size-fits-all approach for MSMEs to benefit from artificial intelligence.
| Business | AI application | Business value |
| Indian gearbox manufacturer | Predictive maintenance | Fewer breakdowns and lower maintenance costs |
| Ansh Creations | AI-assisted customer research | Better understanding of customer preferences |
| Supertech Laminates | AI-assisted export strategy | Better-informed international expansion planning |
Although they operate in different industries, the three businesses follow a similar approach: they are connecting technology with specific business needs.
The MCCIA’s 2025 report, which shares the experiences of 100 MSME AI champions, also reports improvements in productivity, operational efficiency and customer engagement among businesses included in the report.
There are three important lessons here:
- Start with a business problem: Identify where time, money or opportunities are being lost before selecting an AI tool.
- Choose applications that fit your operations: A manufacturing business may benefit from predictive maintenance, while a consumer brand may find customer research more useful.
- Measure actual outcomes: Track improvements in time, costs, quality, customer engagement or sales instead of judging success by the number of AI tools adopted.
AI adoption should be linked to actual business performance, not treated as a trial of new technology without a clear goal.
Where Should an Indian MSME Start With AI?
For a business that has never used AI in its daily work, getting started may seem difficult. However, businesses do not have to start with expensive software or advanced automation.
A more simpler approach is to identify one area where AI can make everyday work easier.
Start With One Repetitive Business Problem
Look at tasks that take up a lot of time without helping the business grow directly.
These might include:
- Writing product descriptions and marketing content.
- Preparing customer responses and email drafts.
- Researching competitors and potential markets.
- Organising business information and reports.
- Analysing customer reviews and feedback.
Easy-to-use generative AI tools can assist with many of these activities. Employees should still review the outputs before using them in customer-facing or business-critical situations.
Match AI Adoption to Business Readiness
Not every business needs the same AI solution.
A small retail business might begin with AI-assisted content creation and customer communication. A growing business with organised customer records could try customer data analysis and marketing automation.
Manufacturers with the right digital systems and machine data can explore predictive maintenance or automated checks for product quality.
The right solution depends on the business’s current work processes, available data, budget and technical skills and resources.
Measure Results Before Expanding
Before implementing a new AI tool, establish what improvement the business expects.
For example:
- Has the time required to complete a task decreased?
- Are customer enquiries being handled more efficiently?
- Has production downtime reduced?
- Are marketing activities generating better engagement?
- Has the business reduced repetitive manual work?
Compare performance before and after implementation. If the results justify the investment, the business can gradually expand its use of AI.
This approach helps MSMEs maintain control over costs while making decisions based on measurable results.
How the Right Digital Strategy Can Help MSMEs Make Better Use of AI
AI tools alone do not create a successful growth strategy. Businesses also need to understand their customers, find new market opportunities and build systems that support long-term growth.
For example, AI-assisted marketing may help a business prepare content faster, but that content still needs a clear strategy to attract the right audience. Similarly, customer data becomes more valuable when businesses use it to improve engagement and retention.
This is where a structured digital growth approach becomes important.
At Red Honey Group, the focus is on helping businesses identify what makes them unique and translate it into memorable online experiences. Through measurable, testable and scalable digital strategies, businesses can build better customer relationships, improved business performance and sustainable growth.
For MSMEs exploring AI, the goal should not simply be to adopt more tools. It should be to make better business decisions and create measurable value from technology.
Frequently Asked Questions About AI for MSMEs
1. How can AI help small businesses grow?
AI can help small businesses improve productivity, automate repetitive tasks, analyse customer preferences and make better business decisions. Depending on the application, it can also support marketing, customer service, manufacturing and market research.
2. What are the best AI applications for Indian MSMEs?
Useful applications include generative AI for content creation, AI-assisted customer research, automated customer communication, predictive maintenance, quality inspection and business data analysis. The best application depends on the business’s industry and requirements.
3. Can small businesses afford AI implementation?
Yes. Many small businesses can begin with accessible AI tools and subscription-based services. However, advanced applications may require additional investment in software, infrastructure, training and integration.
4. How can manufacturing MSMEs use AI?
Manufacturing MSMEs can use AI for predictive maintenance, production monitoring, defect detection, quality control and demand forecasting. These applications can help reduce downtime, improve consistency and support more efficient operations.
5. Does AI require technical expertise?
Basic generative AI tools can often be used without advanced technical knowledge. However, specialised applications involving machine learning, industrial sensors and automated production systems generally require technical expertise and appropriate infrastructure.
Conclusion: AI Is Becoming a Practical Growth Tool for Indian MSMEs
The experiences of these three businesses show how MSMEs using AI to grow are approaching technology in different ways. From reducing manufacturing downtime to understanding customer preferences and exploring international markets, AI is helping businesses address specific operational and commercial challenges.
However, successful adoption is not about using the most advanced technology. It is about identifying the right problem, selecting an appropriate solution and measuring the results.
For Indian MSMEs, AI represents an opportunity to improve efficiency, compete more effectively and build more scalable businesses. The businesses that approach it with a clear strategy and realistic expectations will be better positioned to turn technological possibilities into meaningful growth.
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