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Q: As COO of one of India’s largest digital marketplaces, how do you see AI reshaping product discovery, trust, and decision-making for millions of MSMEs on platforms like IndiaMART?
For a platform of our scale, we have integrated AI deeply into core workflows to fasten discovery, enrich engagement, and streamline operations. Our focus is to deploy AI where it truly impacts buyers, sellers, and our teams. Key areas include:
- Discovery: Today, we handle 29M+ unique annual enquiries, with AI driving higher match
- relevance. First-response times have halved for AI-assisted sellers, and vernacular/Hinglish null results have also reduced. AI isn't a bolt-on for us but has been woven into our DNA for years. Our AI models handle ~65 lakh misspelled/Hinglish queries every month, across 9 Indian languages, reducing null results and improving relevance
- Behavior-Led Recommendations & Matchmaking: ML algorithms analyze buyer intent signals for precise seller leads, by understanding location, product fit, or order value. Personalized two- way matching elevates relevance for both sides.
Trust & Risk Management: AI detects suspicious listings, blocks spam leads, and flags policy violations early, fortifying fraud prevention. Specification & Attribute Extraction: NLP extracts from unstructured data to auto-populated product attributes, easing seller onboarding and enriching catalogs.
Q: IndiaMART operates at the intersection of startups, MSMEs, and enterprise buyers. From and operational and ecosystem perspective, how can AI act as a growth equalizer for small businesses in India’s evolving digital economy?
Artificial intelligence serves as a powerful growth catalyst by democratizing access to advanced insights, technologies, and opportunities that were once the exclusive domain of large enterprises. For micro, small, and medium enterprises (MSMEs), AI-driven solutions such as automated lead management, dynamic pricing strategies, and sophisticated customer profiling create a more level playing field. These technologies streamline operations, enhance business visibility, and facilitate connections between small businesses and enterprise clients.
By integrating AI into core processes, MSMEs can scale efficiently, uphold quality standards, and actively participate in global supply chains.
Q: As India builds its Digital Public Infrastructure and the IndiaAI ecosystem, how can large digital platforms collaborate with governments and startups to accelerate responsible and inclusive AI adoption, especially for MSMEs?
As India scales its Digital Public Infrastructure (DPI) and the IndiaAI Mission, the collaboration between large digital platforms, the government, and startups can help in building an AI-first ecosystem. The public-private partnership is already happening, with platforms like Microsoft and Google collaborating with Bhashini (India & AI translation mission) to create voice-based tools. This will allow a small shop owner or a micro-sized business to manage inventory or file GST via voice in their local language, bypassing literacy and technical barriers.
In addition to this, large fintech platforms can provide MSMEs with AI-driven credit scoring, enabling cash-flow-based lending instead of traditional collateral-based loans. This can address one of the most
significant issues of credit access in the MSME ecosystem. Not only government, but industry bodies catering to sector-specific MSMEs and businesses can collaborate with large enterprises to create sector-specific AI playbooks.
For a platform like us, we are already integrating AI tools to better connect MSMEs with buyers. This Includes:
- Lead management: The LMS (lead management system) flags AI-Prioritized Leads, instead of just a list based on their past behavior, allowing the seller to focus their efforts. In addition to this, it also allows one-click actions such as payment reminders, sharing a catalogue, or responding to an inquiry with pre-set templates, all automated.
- Better customer support: To further enhance the user journey, our chatbot and voice bot for sellers and buyers helps in making their journey better at IndiaMART. A buyer can simply state his/her requirement, and the bot will automatically create a buying requirement for the buyer. Additionally, the voice bot also supports users in resolving common platform queries an connect them to the customer agent, wherever needed.
Q: What are the biggest operational, cultural, and adoption challenges organizations face when embedding AI into core platforms, and how should leaders approach this transition at scale?
The challenges of upskilling and reskilling in the workforce remain and will be addressed, as organisations innovate with AI tools. In addition to this, the selective choice of which tools are better for my organisation remains another area of discussion, as the AI tools are also evolving and better with usage.
AI has tremendous potential, if used ethically and responsibly. More than a challenge, it is a great tool for the augmentation of operations and sales. It becomes a helping hand for the teams, especially at sales and servicing businesses like ours, on the ground. The voice AI Agents can help in setting up sales and client meetings, by looking at the current calendars, thus saving a lot of time for the sales and servicing team.
In addition to this, AI agents support training teams, where questions from teams are answered on the fly, supporting the improvement and preparation for customer meetings with a single click and auditing meetings to help identify the gaps for continuous improvement. This is becoming a great tool to enhance quality of service at unprecedented speed and scale. Deep convergence of AI and security is an equally big opportunity, where AI is no longer just an
innovation layer, but an integral part of the cyber defense fabric. As we scale our platform to support increasing buyer-seller interactions daily, manual or rule-based systems alone won’t suffice.
We believe that AI will increasingly become our first line of defense, enabling real-time anomaly detection, behavioral threat analytics, and dynamic risk scoring. For instance, instead of flagging spam or fraud reactively, we’ll have AI models that proactively learn evolving attack patterns, detect subtle signals of abuse, and auto-mitigate threats before they impact users
Q: Looking ahead, what does India’s AI-powered marketplace ecosystem look like by 2030, and what capabilities should platform and business leaders start building today to stay relevant and resilient?
For organisations to stay relevant and resilient, having an AI-first approach is essential.
- AI-First Operating Models: Shifting to an invent-first approach is essential. Start mapping internal workflows to identify where AI Agents can take over coordination roles. A shift in the leadership style from managing tasks to orchestrating AI systems that manage those tasks is needed, to ensure agentic AI readiness within the organisation.
- Talent &Upskilling: Building AI maturity-indexes and employee playbooks to bridge the talent gap. This has to start now, so in the coming few years, investment in upskilling can pay off.
- Multilingual & Multimodal Strategy: India’s next 500 million internet users will not be English- first. Investment in multimodal capabilities (Voice + Image + Text) to tap these next 500 billion users so your platform can speak and hear regional.
- The Data Mindset: Data is the fuel for AI, and with time, Data Privacy and Sovereignty will become non-negotiable. Thus, Privacy-by-Design approach, where data architecture is compliant with the DPDP Act and can interoperate with public data sets, will be paramount too.
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