How India's MSMEs Can Turn AI Potential into Performance

Artificial Intelligence (AI) is actively transforming industries by simplifying and streamlining operations, personalising customer experiences, and improving decision-making. While large corporations have rapidly scaled their AI initiatives, India’s Micro, Small and Medium Enterprises (MSMEs) are still catching up. Their challenge isn’t so much awareness; it’s execution.

Despite the growing availability of AI powered tools from chatbots and automated invoicing to predictive analytics, adoption among MSMEs remains limited. The primary roadblock isn’t access to technology but a lack of digital readiness. For AI to be truly effective, MSMEs need to build foundational capabilities: structured and centralised data systems, integrated digital workflows, and a workforce that is comfortable using tech-enabled tools. Without these pillars in place, even the most sophisticated AI solutions fail to deliver results.

One of the most significant barriers is the digital skills gap. Unlike larger enterprises with dedicated IT departments, MSMEs typically operate with lean teams and minimal technical expertise. Many business owners and managers juggle various platforms for accounting software, inventory systems, customer databases without fully understanding how to leverage or integrate them. AI implementation is not a plug-and-play exercise; it demands strategic alignment with business operations and clear problem-solving objectives.

Equally crucial is the issue of data quality and accessibility. AI systems rely on clean, well-structured, and centralised data to function optimally. Yet many MSMEs continue to work with fragmented records, legacy tools, or even manual, paper-based processes. In such environments, AI cannot perform meaningful analysis or automation. Investing in digitisation like starting with consistent data entry, cloud-based storage, and basic system integration is a necessary first step toward AI readiness.

Another critical hurdle is technology fragmentation. It is not uncommon for MSMEs to use siloed tools for different functions such as payroll, inventory, customer service, and finance that do not communicate with one another. This lack of integration creates data silos and inefficiencies, making it nearly impossible for AI tools to generate holistic insights. While APIs and interoperable SaaS platforms are now widely available, awareness and adoption among small businesses remain low.

Infrastructure challenges further complicate the picture, especially for MSMEs outside major urban centers. Inconsistent internet connectivity, limited bandwidth, and lack of access to cloud-based services restrict the scalability of even basic AI applications. This is where telecom operators and technology providers must play a more active role by  offering bundled solutions that combine reliable connectivity, cloud access, and AI-powered business tools designed specifically for MSMEs.

Cost perception is another persistent concern. For many MSMEs, AI is seen as a high-risk investment with uncertain returns. However, the landscape is changing. A growing number of AI solutions are now available through subscription-based and pay-as-you-go models, allowing businesses to start small and scale as needed. Entry-level tools for customer service, lead management, invoice processing, and inventory alerts are both accessible and affordable. What MSMEs need most is the confidence that these tools will deliver measurable value. This is where solution providers must step up, offering pilot programs, trial periods, and real-world case studies that demonstrate tangible impact.

Perhaps one of the most overlooked factors is the need for contextual relevance. Many AI tools are designed for large global enterprises and fail to address the unique realities of small, localised businesses. MSMEs need tailored solutions like a chatbot that supports regional languages, an invoice scanner built for local compliance norms, or an AI dashboard that works with low data volumes and simplified workflows. Innovation in this space must account for ground-level business diversity.

The encouraging sign is that early adopters are already proving AI’s potential, even at a modest scale. A mid-sized real estate firm, for instance, implemented an AI-driven chatbot to manage customer inquiries. This resulted in  faster response times, improved lead conversion, and greater productivity without hiring additional staff. Similarly, a pharmaceutical company used AI to automate inventory tracking and expiry monitoring across its distribution chain. The outcome: reduced wastage, better stock visibility, and improved compliance all while freeing up staff to focus on quality work and fulfilment.

These examples make one thing clear that AI adoption doesn’t require massive capital or complex infrastructure. It begins with identifying a clear use case , automating FAQs, digitising records, segmenting customer data and gradually expanding as results become visible. With the right tools and mindset, MSMEs can turn small AI wins into lasting business advantages.

The path forward for MSMEs is not about a complete digital overhaul, it’s about taking phased, strategic steps. Start by solving one repetitive or time-consuming task. Choose a solution that integrates easily with existing systems, measure the impact and scale thoughtfully. This method not only reduces risk but also builds internal capability over time.

In the evolving digital economy where agility and personalisation are becoming key differentiators, AI offers MSMEs the ability to compete on a more level playing field with larger players. The question is no longer whether MSMEs should adopt AI, but how quickly  they can begin. With the right support from policymakers, industry associations, and solution providers, India’s MSMEs can transition from AI spectators to active participants driving productivity, innovation, and inclusive economic growth.

The time to act is now.

(The author is the Managing Director at Tata Teleservices Limited. The views expressed in this article are personal and do not represent the opinions or positions of Outlook Business.)