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Picture this: a customer in Mumbai opens ChatGPT, types "find me the best ergonomic office chair under ₹15,000 with fast delivery," and within seconds receives three specific product recommendations — complete with prices, delivery timelines, and a summary of customer reviews. They don't visit your website. They don't search on Google. An AI agent found, evaluated, and presented your product — or your competitor's — based entirely on how well your product data was structured.
This is not a prediction for 2030. It is happening right now, in June 2026. And most Indian D2C brands are not ready for it.
The word "agentic" comes from "agent" — a system that acts on behalf of someone to achieve a goal. Agentic AI is artificial intelligence that doesn't just answer questions; it takes actions, makes decisions, and executes multi-step tasks independently.
Here is how it differs from what came before it:
A traditional chatbot follows a decision tree. You ask a specific question and it returns a pre-programmed answer. It cannot adapt, explore, or take initiative.
A regular AI assistant like early ChatGPT answers questions based on its training data. It can reason and generate responses, but it cannot browse the web, interact with other software, or complete transactions on your behalf.
An agentic AI system can do all of this. It can interpret your goal ("find me a chair"), search multiple sources, compare options, check stock availability, read reviews, identify the best match, and in some implementations, actually complete the purchase — all without you clicking through a single web page.
The shift is already well underway. A 2026 global commerce study found that 73% of consumers are already using AI in some part of their shopping journey. Gartner reports that more than 30% of all digital commerce interactions now involve AI agents at some stage of the process. Morgan Stanley predicts that by 2030, nearly half of online shoppers will use AI shopping agents, accounting for roughly 25% of total e-commerce spend.
Closer to home, platforms that Indian consumers use daily — ChatGPT, Google AI Mode, Perplexity — have all evolved into active shopping research tools in 2026. A customer doesn't search "best running shoes India" on Google and click through ten blue links anymore. They ask an AI system and get a curated answer. The AI decides who gets recommended.
This is the most important thing to understand: AI agents do not shop the way humans do.
A human customer is influenced by beautiful product photography, a persuasive brand story, and social proof. An AI agent is influenced by none of that. It evaluates your product based on the quality and structure of your data — product specifications, dimensions, materials, price history, availability, return policy, and customer review scores.
If your product listing is rich with accurate, structured information, AI systems can confidently recommend it. If your description is thin, inconsistent, or missing key attributes, the AI either ignores your product or ranks it lower in its recommendation set.
This means the most expensive product page design in the world is worth nothing if your underlying data is not AI-readable.
Discovery is shifting from search to conversation. Consumers increasingly start their product research by asking an AI assistant rather than typing keywords into Google. ChatGPT Search, Perplexity, and Google's AI Mode are handling a growing share of product discovery queries.
Comparison happens inside the AI. Instead of visiting five tabs and comparing products manually, consumers ask the AI to compare. The AI does this analysis and surfaces a shortlist. Brands that are not in this shortlist simply do not exist for that customer.
Purchasing is becoming delegated. Google's "Buy for me" functionality — live in the US as of early 2026 — allows AI agents to complete purchases directly on merchant sites. This is coming to India. When it does, brands that have optimised for AI discovery will see automated purchase traffic; those that haven't will not.
You do not need to overhaul your entire tech stack to prepare for agentic commerce. Start with these three steps.
Audit and enrich your product data. Go through your product listings and ensure every item has complete, accurate specifications — materials, dimensions, compatibility, use cases, and a clear return policy. This is the single most impactful thing you can do.
Implement structured schema markup. Schema markup is code that tells AI systems and search engines exactly what your products are, what they cost, and who they are for. Product schema, Review schema, and BreadcrumbList schema are the minimum. If you're on Shopify, several apps handle this automatically.
Build a content presence on AI-indexed platforms. Perplexity, ChatGPT, and Google AI Mode pull from web pages, Reddit, Quora, and directory listings when building their recommendations. Being present and authoritative on these platforms increases your chance of being cited.
The brands that start preparing now will be the ones AI agents recommend when your potential customers come searching. The ones that wait will find themselves invisible in the channel that is fast becoming the primary way people discover products.
At Howl Media Labs, we help Indian D2C brands build AI-ready digital infrastructure — from structured data and schema to AI-powered automation and GEO strategies. If you want to understand where your brand stands, book a 15-minute call with our team.
Related reading: AI Agents & Automation Services | Website Development for D2C Brands

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