Artificial intelligence is no longer a backroom experiment for Indian food brands. In 2025, generative AI sits inside discovery flows, loyalty journeys and even the way restaurant chains design new campaigns. The shift is most visible in a sector that runs on thin margins and quick decisions. Restaurants and quick service brands now operate in a market where customers expect personalised menus on their phones, instant support on chat, and relevant offers every time they open an app.
The scale of this change is significant. The India foodservice market is estimated at about 85 billion dollars in 2025 and is projected to reach nearly 140 billion dollars by 2030, at a compound annual growth rate of just over 10 percent. Industry reports also suggest that the organised segment will grow faster than the unorganised, at more than 13 percent a year through 2028, as chains and digital first brands expand across cities. Online ordering is now a core channel. The online food delivery market alone is estimated at around 45 billion dollars in 2024 and could cross 320 billion dollars by 2033 if current projections hold, supported by a forecast annual growth rate of more than 23 percent. Against that backdrop, restaurant marketers are turning to generative AI to keep up with rising expectations and sharper competition.
Swiggy and Zomato set the tone for discovery
Food delivery platforms have been early adopters of generative AI in India. Their decisions shape what many customers see when they think about eating out or ordering in. Swiggy has outlined how it uses generative AI to build more intuitive ordering experiences, using a model that supports neural search and conversational queries. The company’s chief technology officer, Madhusudhan Rao, has written about Swiggy taking a lead in applying generative techniques to make discovery more natural for users who may not know exactly what they want to eat. In practice, that means moving away from strict keyword search toward prompts like “light dinner for two” or “spicy vegetarian snacks” and using models to map these to cuisines, dishes and nearby outlets.
Zomato has taken a similar approach with Zomato AI, a chat style assistant that answers open ended questions such as what to eat when feeling unwell or how to find high protein, low carb meals. It combines menu data, user preferences and context such as time of day to recommend dishes and restaurants. For partner brands, these interfaces change how visibility works. Being selected inside an AI powered recommendation carousel can be as important as appearing near the top of a list of restaurants.
For restaurant marketers, these moves underline a broader shift. Instead of planning only around search rankings and banner placements, they now consider how menus, photographs, descriptions and ratings will be interpreted by AI systems that assemble personalised suggestions in real time.
1. Cloud kitchen and QSR brands lean on AI for performance
2. Digital first operators and quick service restaurants are using generative AI and broader AI tools to sharpen marketing and retention.
Rebel Foods, which runs brands such as Faasos and Behrouz Biryani, has publicly discussed its use of AI in marketing. Its chief marketing officer, Nishant Kedia, has written and spoken about using AI to deepen user insights, improve targeting and optimise creatives. In recent interviews he has pointed to AI driven campaigns that have lifted marketing return on investment by 30 to 40 percent and allowed Rebel Foods to reach two to three times more customers with the same budgets.
Kedia has also argued that AI is reshaping marketing operations and that leaders need to understand how to deploy these tools effectively. For Rebel Foods, that includes using models to decide which brand to foreground for which customer, which offer to prioritise and how to sequence messages across in app notifications, email and ads.
Quick service chains are blending AI into both operations and engagement. Domino’s, for instance, has worked with martech platforms to use AI for more personalised cross channel communication in India, and globally has showcased generative AI projects that analyse large volumes of feedback to derive insights on customer sentiment and product tweaks. While those initiatives focus on experience, they feed back into marketing decisions about which messages resonate and which offers to amplify.
Smaller chains are experimenting with AI in more visible ways. The Burger Company, a domestic QSR brand, has introduced an AI powered human like avatar called Isha at some outlets to answer questions, take orders and guide customers through the menu. Its founder and chief executive Neelam Singh has said the aim is to stay ahead of the curve and remain relevant to younger customers by bringing advanced technology into tier two and tier three markets as well, while keeping the experience accessible.
These examples show how generative AI sits in the middle of both practical tasks such as routing offers and more experimental plays such as AI powered brand mascots.
Where generative AI touches the restaurant journey
On the ground, marketers describe a few recurring use cases.
First, content velocity. Restaurants need a steady stream of menus, banners, social posts, email copy and platform listings. Generative tools help teams produce draft versions faster, especially when adapting content for multiple languages or cities. Creative teams then refine the output for tone, accuracy and brand guidelines. For chains with dozens of outlets and frequent offers, this shift saves time and keeps campaigns more tightly aligned to calendar events and local tastes.
Second, personalisation in communication. AI systems analyse order history, cuisine preferences, time of day and device patterns to segment customers more precisely. Instead of sending a standard weekend discount, a brand can trigger targeted prompts such as dessert add on suggestions for users who tend to order sweets, or breakfast nudges for office goers who order early in the day. Generative models also help compose subject lines and message variants that match each segment’s behaviour.
Third, assistance and support. Chatbots and voicebots have become more conversational with the help of large language models. Zomato has reported that its AI support bot has been able to handle thousands of messages per minute while improving response times and customer satisfaction scores, a sign that generative models can take on routine support queries for high volume platforms. Smaller brands are plugging similar capabilities into WhatsApp and web chat to answer questions about delivery areas, menu options and offers without adding call centre capacity.
Fourth, experimentation in format. Some brands are exploring AI generated images and video for social media. While there is caution about overuse, generative visuals can help illustrate limited time products or festival menus at lower cost, especially for smaller chains that lack large photo shoots.
Indian context and the tier two shift
A growing share of restaurant growth is expected outside the big metros. Sector studies suggest that the organised food services segment is gaining ground as chains move into tier two and tier three cities, and industry reports highlight that the real differentiator will be how operators use technology and AI to drive consistency and resilience at scale.
Naveen Malpani, partner and consumer industry leader at Grant Thornton Bharat, has framed the challenge in those terms. He has argued that as restaurants expand beyond metros, the winners will be those who can use technology and AI to maintain quality, manage costs and handle complexity while serving varied local tastes.
Generative AI fits into this picture as a way to standardise some aspects of communication and experience even as menus and offers stay locally tuned. A chain can roll out a centralised AI driven playbook for email, push notifications and loyalty outreach, while allowing regional managers to feed in local festival calendars, city specific references and language preferences. For quick commerce storefronts that sell restaurant ready meals and ready to cook kits, AI also supports pricing and promotion decisions based on local demand patterns.
Small and mid sized brands test low cost options
For independent restaurants and smaller groups, the question is often one of access. Enterprise grade AI stacks may be out of reach, but consumer and prosumer tools have lowered the barrier.
Many restaurant owners now use generative AI within design platforms to create posters, menus and social media tiles. Others rely on AI templates built into marketing automation tools from Indian martech providers for basic segmentation and automated campaigns. For them, genAI is not a separate project but a feature that simplifies everyday work such as writing festival greetings, translating menus or drafting responses to online reviews.
Case studies in the Indian market illustrate this shift toward practical adoption. Wow! Momo’s WhatsApp based ordering and engagement, for instance, uses automation and conversational flows to move customers from discovery to repeat ordering, supported by a database of opted in users that receive targeted messages. While not all of that stack is generative, newer tools are making it easier to generate message variations and understand intent in chat conversations at scale.
Quick commerce platforms, which now handle a share of ready to eat and ready to cook orders, are also applying algorithms for inventory and promotion. Coverage of Swiggy Instamart and rivals has highlighted how these companies rely on recommendation systems and optimisation models to manage assortments and ad placements, making AI a part of the extended restaurant ecosystem.
Balancing automation with brand voice
Alongside enthusiasm, there are clear boundaries. Restaurant marketing teams are wary of losing their brand voice or cultural nuance in the process of automation.
In commentary on digital first food brands, Rebel Foods’ leadership has emphasised that while AI can handle a lot of optimisation, strategy and empathy must still come from humans who understand the brand’s positioning and the realities of food as a category that involves emotion, comfort and habit. This is especially important in India, where festivals, regional preferences and dietary rules shape what people eat and when.
Data privacy and transparency are also part of the conversation. As models draw on order history and behavioural data, marketers need to ensure that consent is managed in line with India’s data protection rules, and that communication remains appropriate. Some larger players have begun articulating internal guidelines on where generative AI can be used, for example restricting model generated responses in sensitive customer care situations to drafts that are then reviewed by humans.
Looking ahead, practitioners expect genAI to spread further across restaurant marketing, but in incremental ways rather than through a single breakthrough.
For large platforms and chains, the next phase is likely to involve deeper integration between generative models and existing data warehouses, so that AI can not only write copy but also reason over stock levels, pricing rules and customer lifetime value before suggesting offers. For medium sized brands, the focus will be on pre built solutions from martech vendors that package generative capabilities into campaign builders, loyalty tools and review management.
For all segments, the thread running through current experiments is continuity. Generative AI is helping restaurants keep conversations going with customers throughout the day, from early morning breakfast prompts to late night dessert suggestions, and across channels that now include apps, web, voice and chat. The tools may be new, but the goal is familiar: to stay visible, relevant and responsive in a category where decisions are frequent and loyalties can shift quickly.
As Nishant Kedia of Rebel Foods has put it, AI is reshaping how marketing operations run, and leaders who learn to use it well are likely to find more efficient ways to connect with customers at scale. For restaurant marketers in India, generative AI is less a distant trend and more a set of practical knobs and switches that can be tuned to extend reach, refine offers and maintain a consistent brand presence in a crowded and fast moving market.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.