How AI is anchoring the future of retail in India

The genesis of modern organised retail goes back to the early ’90s, during the opening of the Indian economy. Shoppers Stop, FoodWorld, Westside, and Pantaloons were the early green shoots. These were the times when satisfactory underperformance was acceptable to Indian customers. Crossroads Mall in Mumbai, Ansal Plaza in Delhi (both in 1999), followed by City Centre in Kolkata in the early 2000, kicked off India’s shopping mall culture. 

 By 2012, the liberalised norms allowed 100% foreign direct investment in single-brand retailing in India. This encouraged global brands Ikea, Apple, H&M, Swatch, Uniqlo, Christian Louboutin, and Louis Vuitton, among others, to enter India, resulting in an array of premium and luxury malls like Palladium, Emporio, U.B. City, Select City, DLF Mall of India, and now Jio Plaza in Mumbai. Acceptance of satisfactory underperformance in earlier times gave way to customer satisfaction and pleasure. 

 Now, in the age of AI, customer expectations have skyrocketed. Generative AI and agentic AI will completely redefine the retail industry globally and in India. Customer satisfaction has become passé. Indian retail customers expect delight at every touchpoint of the entire retail value chain. According to Honeywell’s 2025 Global Retailer Technology Survey, nearly 96% of Indian retailers have adopted AI, with the global average at 85%.

 Can AI enhance efficiency and deliver delight, while trimming the cost architecture of retailers? Let’s dive deep to understand how companies are reinventing their retail value chain to drive cost and value delivery efficiency at every touch point, leading to customer delight, loyalty, and increasing lifetime value.

 A retail value chain includes all those activities from ideation to customer service, with incremental value addition at every stage, leading to a cascading effect of customer delight.

 Ideation

Several retail companies in India are aggressively using AI for product styling based on fashion trends. For many of its private labels, like Roadster, HRX, and Anouk, Myntra uses AI to analyse data, project fashion trends, and design apparel, which then goes for production. Lenskart uses AI for virtual try-ons, collects data on frequently used styles, and thereby forecasts future styles. Stylumia, a fashion tech start-up, assists fashion houses in analysing data and predicting newer trends using machine learning and computer vision. With their demand sensing technology, they enable fashion houses to improve their profitability as well.

But most fashion retail brands globally use AI as an enabler in the ideation stage. Human creativity has the final say. Zara has recently hired the legendary fashion designer John Galliano, who comes with the fame of Givenchy and Dior behind him, as their creative director. The fashion label has also integrated RFID chips into every apparel’s security tag. It can track items carried into the trial room and what are finally bought. The acceptable styles, trends, and feedback go back to their design centres in real-time, where the role of human loops steps in.

AI enables efficiency, faster production turnaround, effective inventory management, customer delight, and thereby higher profitability.

 Sourcing

Both P&G and HUL in India collect store-level data and shelf images in millions and process them to predict and forecast SKU-wise demand and production. HUL has a connected nerve centre that coordinates, plans, sources, and delivers into stores in real time. With historical data and hyperlocal analytics, Blinkit optimises stocks across its 400+ dark stores.

Reliance Retail optimises demand forecasting, vendor collaboration, and sourcing. Amazon follows the anticipatory shipping policy. Using AI, they can predict the projections and ship materials in advance to their fulfilment centres. Sourcing from nearly the bottom 20% of Walmart’s 100,000 global suppliers is negotiated and closed by virtual chatbots.

 Warehouse & logistics

Most retail companies, both offline and online, have managed to optimise and make demand forecasting more efficient using AI. Retailers have realised that wealth is locked in inventory and the supply chain. AI has brought in supply chain velocity and optimised stocks at stores, thereby maximising top line and profitability. Globally, companies like Amazon have started using robotics in picking, sorting, and packing goods in the warehouse, thereby increasing speed and efficiency. The objective of using AI in warehouse and logistics management is to ensure higher fulfilment and thereby profitability. Amazon also uses computer vision to detect product defects, which can then be offloaded. Flipkart and Reliance Retail minimise wastage through demand-sensing technology. Meesho uses AI for route optimisation of its delivery vehicles and has reduced return logistics cost by 20%. Blinkit also uses advanced algorithms to optimise routes for its delivery boys on a real-time basis by analysing traffic.

Retail stores

Many big retailers and quick-service restaurants have already implemented and made billing frictionless. Flagship McDonald’s restaurants in India now have the scan and pay billing towers, which are convenient and time-saving.

It was a pleasant experience at the Uniqlo store in DLF Courtyard at Saket, New Delhi. There are self-scan and pay counters, and it takes a minute to pay and collect your product along with the invoice. You can pick a carry bag that is kept adjacent and leave. 

 Young fashion brand “Yousta” of Reliance Retail also has self-check-out counters to appeal to the Gen Z, for whom velocity, along with convenience in shopping purchase is crucial. Though Lenskart was a pioneer for implementing AI-driven “Virtual Try Ons,” now we have Myntra, Tata Cliq, Nykaa, L’Oréal, Caratlane, Ikea, and many more that have begun using Virtual Try Ons to increase sales.

Retail companies like Sephora India, Uniqlo, and Reliance Retail have moved to the next level using AI-driven heatmapping of customers in their retail stores. With video analytics, we track and analyse customers' journey paths, retention time on specific shelves, product interests, and emotional responses to study consumer behaviour, optimize layouts, identify warm and cold zones, and track gender movement, among other things. This helps retailers to maximize sales and profitability per square foot in a retail store.

The other key outcomes of using AI in retail stores are hyper-personalisation, dynamic pricing, and optimising inventory management. ABFRL’s luxury fashion brand multiband store “The Collective” uses Algonomy’s AI-driven personalization across all brands, which creates a connected customer profile across all online and offline channels. The store staff, therefore, has access to the customer's likes and dislikes and thereby guide him well to close a sale.

Customer service

AI is reinventing customer service to ensure delight at every consumer engagement point. Whether it is the user experience while browsing the website, interactivity with the AI assistants, or receiving a personalised offer, AI today has redefined customer service, wherein the prime objective is to ensure delight at every step. Satisfaction is now passe. 

Increasing use of blockchain technology has significantly improved retail security and given a boost to anti-counterfeiting. De Beers uses a blockchain platform called “Tracr” for ensuring the authenticity of diamonds, and Louis Vuitton has an Aura Blockchain Consortium to ensure their luxury fashion originality. Machine learning, large language models, and predictive analytics are being increasingly used to enhance customer experience at every touchpoint of the journey cycle. So service is no longer a post-buying support. It’s now perceived to be seamless across all touchpoints. The technology-driven gratification notwithstanding, the human loop with higher-order cognitive abilities like emotional connection and showing empathy would remain in vogue.

The Indian Gen Z and Alpha retail customers are digital and AI natives. According to the government Economic Surveys and MOSPI data, the disposable income in India has increased by almost 600% in the last 20 years. Our estimates suggest that the income of the top 20% of the Indian population might have increased by almost 1000% in the last two decades. Today’s Gen Z & Alpha are born in relatively more well-off families than their predecessors. It will not be wrong to say that they have, in a way, moved beyond Maslow’s basic physiological needs, which are already taken care of. Their shopping expectations are far larger than those of the earlier generations, the Millennials & the Gen X, their parents. Being discerning and well-informed, they are highly aspirational and demand experiential shopping even for necessities and other retail products. Artificial Intelligence is, therefore, a technology revolution which will help match the new age retail consumers’ experiential expectations.

(Das is associate professor, Marketing & Retail, Birla Institute of Management Technology; Mittal is assistant professor, marketing, BIT, Mesra, Ranchi (Noida Campus). Views are personal.)