Buy-buy AI: Why India's retailers are betting big on AI-powered growth

The concluding part of the series looks at how artificial intelligence is transforming every aisle with algorithms, from product discovery to logistics and marketing

Last month, French beauty giant L’Oréal teamed up with artificial intelligence (AI) powerhouse Nvidia to supercharge research, drive innovation, and scale up AI-powered ads and product recommendations. 

 

Meanwhile, luxury titan LVMH is leaning on AI to ride out softening demand as it looks to boost sales, retain customers and court new ones, and stay ahead of shifting trends.

 

Both hope AI can reveal what traditional tech doesn’t. 

 

“Retail has always been a data-rich industry, making it a natural fit for AI innovation,” says Dahnesh Dilkhush, executive director, customer success, Microsoft India and South Asia. So, retailers are increasingly turning to it to unlock the value in that data. 

ALSO READ PART I: AI in currency: How it is quietly rewriting the rules of modern banking

 

Across India’s diverse retail landscape — ranging from digital-first companies like Flipkart, Zepto, and Meesho to brands like Nike, Starbucks, and even heritage ones like Raymond and Godrej — AI is reshaping how consumers shop, goods move, and businesses think. 

 

What was once a space dominated by basic business software, point-of-sale type of systems, and seasonal trends is rapidly becoming a high-velocity engine for real-time intelligence. For offline retailers, even CCTV footage is being scanned ‘intelligently’ to comprehend footfalls and what buyers may want.

 

AI that feels human

 

At ecommerce major Flipkart, AI doesn’t just recommend; it converses, guides, and adapts. 

 

“Whether you’re speaking, typing, or snapping a photo, our multimodal search understands you. It’s how we bring intelligence into the everyday experience,” says Sandhya Kapoor, senior vice-president and head of the central platform at Flipkart. 

 

She adds that tools like Flipkart’s skin analyser, virtual try-on, augmented reality, and hyper-personalised recommendations are enhancing user experience and helping them make informed choices. “We’ve seen a 21 per cent increase in product purchases through skin analyser alone.” 

ALSO READ PART II: From cancer detection to treatment, how AI is transforming health care

 

AI is helping Flipkart mimic human behaviour — auto-filling repeat orders, resolving delivery hiccups before customers notice, and enabling sellers in Tier-II cities with catalogue automation and price 

 

optimisation. “These are not just proof of concept (PoC) projects. They represent a combination of production-grade deployments and long-term foundational investments,” Kapoor says. 

 

Curiosity to commitment

 

It’s not just large retailers who are adopting AI to build efficiencies. Even micro and small retailers want to invest in AI and machine learning (ML), according to Chennai-based Cloud software company Zoho. Its survey of small retailers revealed that 60 per cent of them plan to adopt AI and ML by 2030 to stay competitive.

 

“Indian enterprises are moving from curiosity to commitment when it comes to AI. The narrative has shifted from asking, ‘What can AI do?’, to, ‘How fast can we scale it?’” says Anirban Nandi, head of AI, products and analytics, Rakuten India, subsidiary of the Japanese ecommerce to tech conglomerate, the Rakuten Group.

 

Leading retailers are embedding AI across their operations: In-demand forecasting, fraud detection, dynamic pricing, customer segmentation, and generative content creation.

 

Meesho uses Azure OpenAI to improve customer effort scores (or ease of interacting with the platform) by 20 per cent. Quick-commerce company Blinkit uses AI to generate recipes from grocery items, boosting engagement. And Bengaluru-based fashion ecommerce company Myntra has MyFashionGPT, an assistant to drive multi-category purchases. Similarly, Bewakoof.com (an Aditya Birla venture) is using Google Cloud’s GenAI capabilities to let users design T-shirts.

 

Retailers are also picking up conversations for intelligent insights. 

 

Messaging platform Gupshup’s senior director, global marketing, Vartika Verma, says brands now map conversations across the customer lifecycle for a seamless, contextual experience. Clients like Tata Cliq, Flipkart, and Unilever use Gupshup’s conversational AI. “Retailers are shifting from basic bots to intelligent, pre-trained AI agents that offer fast, end-to-end support and integrate directly into business systems,” she adds. 

 

AI in the aisle

 

AI’s reach isn’t limited to ecommerce. Brick-and-mortar stores, too, are turning into data mines — bringing online-level intelligence into physical retail environments. 

 

Founded in 2015, Staqu Technologies has developed an AI-powered audio and video analytics platform, Jarvis GPT, which, it claims, is able to provide actionable insights from CCTV footage.

 

“Retailers can track footfall trends, movement patterns, heat maps, and even optimise staff deployment based on live in-store activity,” says Atul Rai, cofounder and CEO, Staqu. “The platform flags anomalies and thefts, turning surveillance systems into proactive tools for both operations and security.” 

 

The startup says the platform is being used by Raymond stores, Starbucks, Being Human, Porsche, and Crocs, besides other brands.

 

Rewiring legacy retail

 

Raymond, a 100-year-old brand, has embraced AI with rare agility. 

 

“We’ve adopted a federated, Cloud-native strategy using AWS, Azure, and Google AI, across retail, human resource (HR), marketing, and manufacturing functions,” says Ravi Hudda, chief digital and information officer, Raymond Group. 

 

Virtual try-ons, voice-based shopping, and predictive inventory models are now standard across its 1,650 stores that are present in 600 cities and towns.

 

Since integrating AI, Raymond has seen a 25 per cent rise in conversion rates (potential customers who end up buying) from its virtual try-on; a 35 per cent uplift in campaign performance through GenAI content; and 20 per cent better inventory accuracy.

 

“AI is no longer just an enabler. It’s a multiplier. And beyond metrics, AI is changing how retailers think,” says Nandi of Rakuten.

 

Even categories like furniture are leaning on AI to boost footfalls and sales. 

 

At Godrej Interio, AI is redefining the way Indians buy furniture. “Imagine a ‘product ATM’ — a 24x7 digital kiosk outside our store where customers can configure and buy furniture,” says Swapneel Nagarkar, executive president and business head at Godrej Interio.

 

Godrej Enterprise Group has committed ₹1,200 crore to its digital and AI initiatives over the next 3–5 years. Tools like visual search and 3D rooms allow customers to visualise how furniture will look in their homes. The result: Tech-enabled furniture now accounts for 30–35 per cent of Godrej’s sales, and is projected to contribute around ₹250 crore in revenue over the next 2-3 years.

 

Powering the shift

 

Underpinning this transformation are AI platforms from the world’s biggest tech players — AWS, Google Cloud, Microsoft Azure — combined with proprietary engines. Open-source tools like PyTorch and TensorFlow, and frameworks like LangChain (used for building training AI models and apps) are enabling advanced use cases, including semantic search and AI agents.

 

Return on investment? “Upwards of 40 per cent for early adopters,” says Nandi. 

 

According to Google, Myntra leveraged GenAI to address the gap in understanding search behaviour in non-metro areas, where 60 per cent of the lifestyle and fashion searches occur. 

 

“Leveraging Google AI, it transliterated high-volume English keywords into ‘Hinglish’ to better capture local search intent. This approach led to a 27 per cent drop in cost per order and 17 per cent higher return on ad-spend (ROAS), boosting Myntra’s expansion into non-metro markets,” says Naren Kachroo, head, go-to-market for generative AI, Google Cloud India.

 

AI is reinventing how products are marketed and designed. 

 

L’Oréal’s AI-powered platform, Noli, acts as a beauty matchmaker, analysing millions of skin profiles and product formulations to give users hyper-personalised recommendations.

 

Meanwhile, Ajio’s Vidbaker tool converts static product images into dynamic video ads at scale — 100-plus videos in an hour — resulting in improved conversions and higher ROAS. Zepto is using AI-powered Veo Craft to add motion to static images, cutting creative production time from weeks to hours.

 

Even luxury retail — historically wary of digital dilution — is betting big on AI. 

 

LVMH, home to Dior and Tiffany, is using agents to support sales associates with deep customer histories. Its AI tool, MaIA, processes over 2 million internal requests per month and helps with product design, pricing, and marketing personalisation.

 

A recurring theme across retailers — large, mid, and small — is a decisive shift from pilots to production. “The scale of automation is expanding due to Agentic AI, with the potential to automate 60 per cent of the processes,” says Digvijay Ghosh, partner, consumer products and retail at the consultancy, EY-Parthenon. 

 

AI is part of retailers’ sales, marketing, HR, finance, customer services, and fulfilment operations. Still, the journey is uneven. According to EY, while 34 per cent of Indian enterprises have completed PoCs, only 15 per cent have moved to scaled deployment.

 

As retailers dig deep into data to know what shoppers want, how much they invest in AI will depend on its impact on sales and bottom line. As Kapoor of Flipkart puts it: “The next chapter of ecommerce will be shaped by how intelligently and quickly platforms respond to changing consumer and seller needs.”

 

In a world where your camera can talk to you about footfall, where your favourite store knows your exact fit, and where a static image can be reborn as a personalised ad, the retail revolution is not just digital. It’s intelligent. And it’s only just getting started. 

Smart retail

 

How AI is being used

 

• Personalised recommendations: To comprehend buyer needs and improve conversion rates
• Chatbots and natural language processing: For customer services via AI-powered chatbots and assistants
• Adaptive advertising: To auto-adjust pricing based on customer behaviour
• Augmented reality: AI-driven AR tools to enhance online shopping experience
• Product tagging and cataloguing: Efficient inventory management by automating this process
• Visual search: To enable users to search products based on images rather than text

 

Sources: Nasscom, industry

 

The writer is a New Delhi-based independent journalist