I used to casually order from Swiggy, or Zomato, when I had nothing to munch on in between the meals, or when I was not carrying a meal at all. A few months ago, I opened my usual food delivery app after a long day. I hadn’t eaten since noon, it was raining, and I felt too tired to cook. I expected the usual scroll-fest, but something strange happened. Before I could even tap “Regular Thali,” the app showed me my favourite dish—Jain Thali with extra raita, salad and sweet, from the place I always order from on rainy evenings.
That’s when I realized that my food app knew me better than I liked to admit. Not just what I ate, but when, why, and how I liked it. That’s how AI works in food delivery apps. This technology quietly runs in the background, reads patterns, and enables you to make quick choices, because you get to get everything at a click.
What AI is really doing inside your favourite delivery app?
In an easy to understand, concise way – AI technology understands your food cravings. If you search for pasta, it will show you all available flavours, from all the restaurants in your city, some with free delivery, some with flash deals, and the best possible delivery fleet. It relieves you from hogging and hunting and saves a lot of effort and time.
AI will never show you how hard it worked to make it happen. It will never show you calculations or algorithms that run behind the scenes, plus it never fails, just in case the app faces some serious test cases (exceptional), and logistics almost become invisible.
When you use the app, it feels like it is actually talking to you, asking you about your preferences at every step, customizing offers to meet the image you have in your mind, and not letting you go with a query.
AI makes you forget the sense of time. If you study with your friends and crave for a pizza or a chocolate shake at 2 AM in the midnight, the app (which never sleeps), will acquaint you with the restaurants that are operating in your vicinity around that hour.
It does not make you feel the absence of talking to a real human customer care representative, handling everything automatically, or on demand.
Your pizza arrives before the movie starts, not midway, because AI tracks traffic, driver availability, kitchen prep time, even weather disruptions, and adjusts everything on the go. It knows that there is going to be a spike in ice cream orders at 10 PM on a humid night. It prepares the system before the rush hits. This keeps restaurants ready, inventory stocked, and ETAs accurate. Chatbots answer most queries smoothly. Some platforms offer voice-based ordering, where you say, “Send me my usual burger and fries,” and it gets done.
Which companies have integrated AI into their core?
Zomato and Swiggy in India use AI for everything from generative AI-powered voice ordering to hyperlocal delivery. Uber Eats knows when you’re likely to order based on your mood and even the local weather. Domino’s uses AI in self-driving pizza delivery and predictive order tracking. DoorDash fine-tunes ETA predictions using historical traffic patterns, driver behaviour, and restaurant prep times.
But It’s Not All Smooth Sailing
Everything that AI touches does not turn into gold. If your order is wrong and you’re upset, a bot isn’t going to make you feel heard. I once argued with one for 20 minutes over a missing sauce. It kept repeating, “I’m sorry to hear that.”
Sometimes AI recommendations can be weirdly biased. Order vegetarian once, and suddenly every suggestion is paneer. AI needs better data diversity.
AI requires investment, but then it makes everything else look easy. AI uses your data – Names, locations, order times, preferences, payment methods. If that data isn’t protected, it becomes a liability. GDPR and similar laws are helping, but enforcement and transparency vary.
The Technology Behind It
All of it needs to be stitched together by a serious food delivery app development company that understands delivery challenges.
- Machine Learning
- Natural Language Processing
- Image Recognition
- Route Optimization Algorithms
- Cloud Infrastructure (like AWS or Google Cloud)
- IoT Sensors