India’s quick commerce market is shifting rapidly — from a race for speed to a competition for intelligence and personalisation. With the sector projected to hit $40 Bn by 2030, platforms are being pushed to move beyond discount wars and delivery timelines to stay competitive.

AI is no longer just an efficiency lever, it’s becoming central to competitive strategy in quick commerce. From hyper-personalised user journeys and GenAI-powered content to predictive fulfilment and agent-led product discovery, AI is transforming how platforms operate and how consumers engage with them.

According to Inc42’s State Of Indian Ecommerce H1 2025 report, while speed remains a critical differentiator, platforms must go beyond rapid delivery to truly stand out and that’s where AI will play a defining role.

Ishank Joshi, MD and CEO at a madtech platform, Mobavenue, too, believes that the future of quick commerce goes beyond speed and hinges on a deep understanding of consumers and engaging them meaningfully.

“AI is at the core of this transformation, enabling brands to personalise experiences, drive customer retention, and optimise operations,” Joshi said.

He sees quick commerce platforms boosting consumer loyalty by offering personalised rewards through AI-driven loyalty programmes. Besides simplifying the shopping experience, the technology is expected to aid q-commerce platforms in the areas of predictive demand forecasting, inventory optimisation, and wastage reduction for overall efficiency.

With AI opening a new realm of possibilities, let’s dive deeper into how quick commerce platforms are reimagining their edge and what it will take to win the next wave.

Leveraging AI To Personalise UX

As per a survey, a majority of customers (71%) purchasing online prefer personalised interactions. This is where AI-driven customisation is essential for quick commerce platforms to succeed. It can be achieved through advanced chatbots for customer support and by creating more relevant ads based on their choices and interests.

Besides, while recommendation engines........

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