Most Indian Brands Use AI as a Buzzword, Not a Strategy
Here’s the uncomfortable truth about AI in Indian marketing: most brands slapping “AI-powered” on their products couldn’t explain what their AI actually does if you put a gun to their CMO’s head.
That’s not an exaggeration. It’s the defining pattern of Indian marketing in 2025-2026. Every pitch deck has an “AI strategy.” Every product launch mentions machine learning. Every brand wants you to believe they’re on the cutting edge. The reality? Most of them are running basic if-then rules and calling it artificial intelligence.
But here’s what makes this analysis different from the usual “AI is overhyped” take: a handful of Indian brands are using AI in ways that are genuinely brilliant, quietly transforming how 1.4 billion people discover products, order food, and spend money. The gap between who’s doing it right and who’s faking it tells you everything about where Indian marketing is actually headed.
And then there’s Fevicol, sitting in the corner, building campaigns so creatively perfect that they make the entire AI conversation feel irrelevant. We need to talk about that, too.
The Three Brands Actually Using AI (Not Just Talking About It)
Before we get to the fakers, let’s give credit where it’s earned. Three Indian brands have built AI systems that genuinely change user behaviour, not just marketing slides. The difference? Their AI is invisible to the user. You don’t see a badge saying “AI-powered.” You just notice that the app somehow knows what you want before you do.
That’s the first marker of real AI in marketing: if the brand has to tell you it’s using AI, it probably isn’t using it well.
Myntra: Where Personalisation Actually Means Something
Myntra’s “My Stylist” and personalisation engine isn’t a gimmick. It’s a system processing over 300 million data points daily to predict what you’ll buy before you search for it. The company’s recommendation algorithm analyses your browsing patterns, purchase history, return behaviour, time spent on product pages, and even the order in which you scroll through images.
Here’s what most people miss: Myntra’s AI doesn’t just recommend products. It changes the entire storefront layout based on who’s browsing. Two users opening the Myntra app at the same time in the same city see completely different homepages, different product grids, different promotional banners. The app isn’t showing you a catalogue. It’s showing you your catalogue.
The results speak for themselves. Myntra reported a 35% increase in conversion rates from personalised recommendations in their FY2025 earnings. Their repeat purchase rate sits at 75%, compared to the industry average of 45-50% for fashion e-commerce. That’s not marketing. That’s behavioural science deployed through infrastructure.
The Psychology Layer
Myntra’s AI exploits the mere exposure effect: we prefer things we’ve seen before. By tracking what you lingered on (even without clicking), the algorithm resurfaces similar items in different contexts. You feel like you’re discovering something new. You’re actually being shown a refined version of what you already wanted. The decision feels like free will. It isn’t.
Swiggy: The Recommendation Engine That Knows You’re Hungry Before You Do
Swiggy’s recommendation engine is the most sophisticated piece of AI marketing infrastructure in Indian consumer tech. It doesn’t just suggest restaurants. It predicts your order based on time of day, weather, past ordering patterns, what your neighbourhood is ordering, and how long it’s been since your last meal.
The company processes approximately 2.5 million orders daily through a system that adjusts restaurant rankings in real time. If it’s raining in Koramangala, you’ll see more biryani and soup options. If you typically order dessert on Fridays, your Friday evening homepage leads with sweet shops. If you haven’t ordered in three days, you’ll get a push notification timed exactly to your usual ordering window.
This is where AI in marketing stops being a buzzword and becomes a revenue engine. Swiggy’s personalised push notifications have a 3.2x higher conversion rate than generic promotional messages. Their restaurant recommendation algorithm drives 40% of all first-time orders from a new restaurant, meaning the AI is literally shaping which restaurants succeed on the platform.
Real AI in marketing is invisible. If a brand has to tell you it’s using AI, it probably isn’t using it well.
Flipkart: Search That Reads Between Your Typos
Flipkart’s AI investment goes deeper than most people realise. Their visual search feature, where you take a photo of something and the app finds similar products, processes over 10 million visual searches monthly. But the real intelligence is in their natural language processing.
Flipkart’s search engine understands Indian vernacular in ways that would make Google’s engineers jealous. Search “red kurta like Alia wore in Rocky Aur Rani” and you’ll get results. Search “phone under 15k with good camera” and the NLP engine parses the budget constraint, the feature priority, and the implied comparison intent, then ranks accordingly. This isn’t a keyword match. It’s comprehension.
Their AI-powered pricing engine adjusts prices across 150 million products in real time during sale events, responding to demand signals, competitor pricing, and inventory levels faster than any human merchandising team could operate. During Big Billion Days 2025, Flipkart reported that AI-driven dynamic pricing contributed to a 28% increase in gross merchandise value compared to the previous year.
| Brand | AI Application | Measurable Impact | User Visibility |
|---|---|---|---|
| Myntra | Hyper-personalised storefront | 35% higher conversion | Invisible |
| Swiggy | Predictive ordering engine | 3.2x notification conversion | Invisible |
| Flipkart | Vernacular NLP + dynamic pricing | 28% GMV increase | Invisible |
| Average brand | “AI-powered chatbot” | Unknown/unmeasured | Badge on website |
The Majority: Where “AI-Powered” Means Absolutely Nothing
Now for the uncomfortable part. For every Myntra building genuine machine learning infrastructure, there are 50 Indian brands slapping “AI-powered” on products that run on basic rule engines, pre-programmed decision trees, or, in some spectacular cases, literal Excel formulas with a chatbot skin.
You’ve seen them. The “AI-powered skincare analysis” that asks you five questions and recommends the same three products to everyone. The “AI-driven marketing platform” that’s really just a scheduling tool with some analytics dashboards. The “AI chatbot” that can’t understand anything beyond the 40 pre-written responses its developer loaded in.
A 2025 NASSCOM survey found that 87% of Indian companies claimed to use AI in some form. When researchers dug deeper, only about 12% had any genuine machine learning models in production. The rest were using the term to describe automation, basic analytics, or, in some cases, nothing at all beyond the label.
The Anatomy of a Tech-Wash
Here’s how the typical Indian brand “adopts AI”:
- Surface: Brand launches product with “AI-powered” in the name. Press releases mention machine learning. The website gets a new badge.
- Strategy: The real objective isn’t AI implementation, it’s perception management. “AI-powered” adds ₹50-200 crore to a startup’s valuation in investor conversations. It’s not a feature. It’s a fundraising strategy.
- Psychology: This exploits the authority bias. Consumers trust technology they don’t understand. “AI-powered” sounds sophisticated, rigorous, and intelligent, even when the actual technology is neither. It’s the lab coat effect applied to software.
- System: This is tech-washing, the marketing equivalent of greenwashing. An entire ecosystem of startups, agencies, and marketing teams has learned that the three most profitable letters in Indian business aren’t ROI. They’re A, I.
Reality Check
If a brand’s “AI feature” could be replicated with a Google Form and an IF statement in Google Sheets, it’s not AI. It’s marketing. And that distinction matters, because consumers are making purchase decisions based on the implied sophistication of technology that doesn’t exist.
The D2C beauty space is the worst offender. At least eight Indian D2C skincare brands currently market “AI skin analysis” tools that are functionally identical: a quiz that buckets users into three to five skin types and recommends products from their existing catalogue. There’s no computer vision. No machine learning model. No data training. Just a flowchart dressed up in futuristic language.
And it works. That’s the infuriating part. According to a Redseer Consulting report from late 2025, D2C brands using “AI-powered” language in their marketing saw a 22% higher click-through rate on ads compared to identical messaging without the AI claim. The label isn’t a capability. It’s a conversion optimisation hack.
The Fevicol Exception: Why the Best Marketing Needs Zero AI
And then there’s Fevicol.
While India’s marketing industry trips over itself to sound technologically advanced, Ogilvy and Pidilite have been quietly producing the most effective, most awarded, most culturally resonant marketing in the country for decades. Without a single mention of AI. Without a recommendation engine. Without a personalisation algorithm.
Fevicol’s “Toofan” ad during the 2023 Cricket World Cup didn’t need machine learning to go viral. It needed exactly one insight: Indians will watch anything that combines cricket with humour. The ad racked up over 50 million views organically. No AI targeting. No programmatic optimisation beyond standard media buying. Just a devastatingly good creative idea executed with precision timing.
Their decades-long “Fevicol ka jod” campaign is a masterclass in what AI can never replicate: cultural intuition at the molecular level. The brand understands Indian humour, Indian relationships, Indian daily life in a way that no amount of data processing can manufacture. The bus ad. The furniture ad. The wedding ad. Each one works because someone in a room understood something fundamentally true about how Indians think, not because an algorithm processed a billion data points.
Fevicol’s marketing proves an uncomfortable truth for the AI evangelists: the most powerful marketing technology ever invented is a good idea in the right cultural context.
This matters because it exposes the central lie of the tech-washing movement. The assumption driving AI adoption in Indian marketing isn’t “AI will make our marketing better.” It’s “AI will make our marketing easier.” And those are fundamentally different things.
Myntra, Swiggy, and Flipkart use AI to solve genuinely complex problems: how do you show 300 million users each a uniquely relevant experience? How do you predict demand across 500 cities in real time? That’s infrastructure. That requires AI.
But for the vast majority of Indian brands, the marketing challenge isn’t a data problem. It’s a creativity problem. And slapping AI on a creativity problem doesn’t solve it. It just makes the mediocrity sound more expensive.
Tech-Washing: The System Behind the Scam
Let’s zoom out. What’s really happening here isn’t about individual brands making bad decisions. It’s about an entire system that incentivises the appearance of intelligence over the reality of it.
The Incentive Structure
Indian startups operate in a funding environment where “AI-first” companies receive 2.3x higher valuations than comparable non-AI companies, according to a 2025 analysis by Tracxn. That’s not a technology premium. That’s a vocabulary premium. Use the right words in your pitch deck and you’re literally worth more money.
Marketing agencies have caught on. A mid-tier digital agency in Mumbai told us (off the record) that they now include “AI-powered” in every proposal by default, even when the actual deliverable is a standard social media calendar built in Notion. Why? Because clients expect it. Clients who don’t fully understand AI have been trained by the market to demand it. So agencies sell it. Everyone performs intelligence. No one actually builds it.
The Venture Capital Feedback Loop
Here’s the system: VCs want AI companies. Founders rebrand as AI companies. Media covers the “AI revolution.” Consumers associate AI with quality. Brands add AI labels. Consumers buy more. VCs see consumer demand for AI. VCs fund more AI companies.
At no point in this loop does anyone ask: “Does the AI actually work?”
That’s not a bug. It’s the design. The system works perfectly for everyone except the consumer, who’s paying a premium for technology that often doesn’t exist.
The Expert Counterargument (And Why It Falls Short)
The strongest pushback goes like this: “Every technology goes through a hype cycle. AI labelling is just early-stage market education. Brands that claim AI today will build real AI tomorrow.”
It’s a reasonable argument. And it’s wrong.
Greenwashing didn’t lead to environmental progress. It delayed it. When every brand claims to be “sustainable,” the word loses meaning, and consumers can’t distinguish genuine environmental commitment from packaging. The same thing is happening with AI. When every chatbot is “AI-powered,” the label stops signalling quality. It signals nothing.
Worse, tech-washing creates a market where genuine AI investment looks identical to marketing theatre. Myntra spending ₹200 crore on ML infrastructure looks the same in a press release as a D2C brand spending ₹2 lakh on a quiz tool. The noise drowns out the signal. And that hurts the companies actually doing the work.
Is Your Brand’s AI Real? A Diagnostic
The Brand Crush AI Authenticity Test
Answer these five questions about your brand’s “AI” feature. Be honest. No one’s watching.
- Can you name the specific ML model your AI uses? (Not “machine learning.” The actual model architecture.)
- What data is your model trained on, and how often is it retrained? (If the answer is “never” or “what do you mean?”, you don’t have AI.)
- Does your AI improve its output over time without human intervention? (If someone manually updates the rules, it’s automation, not AI.)
- Can you measure a specific business metric that changed because of the AI? (Not “engagement went up.” A specific, attributable number.)
- Would removing the AI change the user experience in a measurable way? (If the product works identically without it, the AI is decoration.)
If you answered “no” to three or more questions, you don’t have an AI strategy. You have an AI label. There’s a difference, and your customers will eventually notice.
The Verdict: Stop Performing Intelligence and Start Building It
AI in Indian marketing splits cleanly into three categories. The builders (Myntra, Swiggy, Flipkart) who’ve invested in genuine infrastructure that changes user behaviour. The fakers (most of the market) who use AI as a label for basic technology. And the exception (Fevicol) that proves the most powerful marketing tool isn’t technology at all, it’s creative brilliance rooted in cultural understanding.
The system behind the faking, tech-washing, is the real villain here. Not individual brands. Not individual marketers. The incentive structure that rewards the appearance of AI over its reality. VCs, agencies, media, and consumers have all co-created a market where saying “AI” is more profitable than building AI.
That’s going to change. As consumers get more sophisticated and regulators catch up (India’s Digital Personal Data Protection Act is already forcing transparency around algorithmic decision-making), the gap between AI marketing and AI reality will become a liability, not an advantage.
After reading this, you’ll never see an “AI-powered” label the same way again. And that’s the point. The brands actually using AI well don’t need to tell you. The ones shouting about it probably should stop.
The future of AI in Indian marketing isn’t about more AI. It’s about honest AI. And until the industry can tell the difference, the tech-wash cycle will keep spinning.
Agree? Disagree? Think we missed a brand that’s genuinely using AI well? Drop your take in the comments. We read every single one. And if you want more no-BS marketing analysis, subscribe for weekly breakdowns that cut through the noise.
Sources and References:
1. NASSCOM “State of AI Adoption in Indian Enterprises” Survey, 2025, reporting 87% AI claim rate vs. 12% genuine ML deployment.
2. Tracxn “India AI Startup Valuation Premium” Analysis, Q3 2025, documenting the 2.3x valuation multiplier for AI-labelled startups.
3. Redseer Consulting “Consumer Response to AI Marketing Claims in Indian D2C,” November 2025.
4. Myntra FY2025 Investor Presentation, personalisation conversion metrics.
5. Flipkart “Big Billion Days 2025” Post-Event Analytics Report, GMV attribution data.
