Indian marketing is going through one of its most consequential shifts in decades. The convergence of digital consumption, a stricter data protection regime, and the arrival of scalable AI is forcing brands to rethink not only how they reach customers but also how they manage internal operations, measure impact, and ensure compliance. MarTech and AI have moved from being pilot projects to becoming core parts of brand strategy. The story of Indian brands today is as much about plumbing and governance as it is about creativity.

Take Hindustan Unilever, the country’s largest consumer goods company. It has built a digital spine that integrates first-party data across brands, and its Shikhar B2B app now connects more than 1.3 million stores. Precision media campaigns have reportedly delivered click-through rate lifts of up to 10 times, while the company’s direct-to-consumer experiments serve thousands of pin codes. This is not marketing as an isolated function but marketing embedded into distribution, sales, and operations. Journalist’s note: the real shift here is that consumer goods companies are no longer treating digital as a layer on top of television and print but as a system that runs parallel to their physical supply chain.

Banking has taken another path, but with equally profound results. HDFC Bank, India’s largest private sector lender, has seen 95 percent of its transactions move to digital channels. Its Group Head and CMO Ravi Santhanam has explained that more than 70 percent of servicing is digital, and that personalisation at scale cannot be attempted without guardrails. The bank has created a governance framework with a data officer, council, and strict oversight on AI-powered targeting. In categories where trust is fragile, one incorrect message can cause long-term damage. Journalist’s note: financial services are showing the industry what “responsible AI” actually looks like in practice, not just in principle.

In e-commerce, AI has become the unseen engine powering everything from search and recommendations to fraud detection and customer support. Flipkart’s Chief Data Scientist, Mayur Datar, has said that AI touches “every aspect” of the platform. That means more relevant search results, dynamic pricing, reduced returns, and stronger fraud checks. Myntra has gone further by deploying generative AI. Its “Dream Room Inspirations” feature allows a user to describe a desired home look in text, and instantly see mood-board images that map to products on its platform. This kind of creative AI is quietly altering the way catalogues, merchandising, and inspiration-driven shopping work.

The most cited Indian case study, though, remains Cadbury’s “Not Just a Cadbury Ad.” During Diwali, Mondelez India deployed AI to create thousands of personalised ads that featured Shah Rukh Khan promoting local stores alongside Cadbury. The system connected to over 1,800 retailers across multiple cities and more than 270 pin codes, delivering measurable uplift in sales. As Anil Viswanathan, who led the initiative, explained, the idea was not just to advertise Cadbury but to support small businesses in the process. Later iterations used synthetic media to allow local shops to generate their own versions of the ad. Journalist’s note: the deeper point here is not the novelty of using AI to clone a celebrity’s voice and likeness, but the operational discipline required to roll out thousands of compliant, localised variants in a market as fragmented as India.

ITC provides another lens. Its Chief Digital Marketing Officer, Shuvadip Banerjee, has repeatedly emphasised that MarTech adoption must start with business objectives and brand needs before tools are chosen. The company has been building owned brand assets and scaling first-party data initiatives to ensure deeper consumer engagement. The emphasis is not on shiny new tools but on how those tools are embedded into decision-making, investment allocation, and analytics at scale. Journalist’s note: this is a corrective lesson for many marketing teams, which often chase new platforms before solving basic problems like clean data pipelines and clear objectives.

Travel and food delivery offer yet another perspective on how AI is reshaping consumer-facing industries. MakeMyTrip launched a conversational AI assistant to help users plan and book trips, allowing them to describe preferences and receive curated options across flights, hotels, and experiences. For a sector overloaded with choices and constraints, AI simplifies discovery in a way search filters never could. Zomato, meanwhile, rolled out “Zomato AI,” which CEO Deepinder Goyal described as a move from generic restaurant reviews to a personalised match score based on a user’s past interactions and preferences. The ambition is to make search results less about averages and more about fit.

Automotive brands are also experimenting aggressively. At Goafest 2025, Tata Motors CMO Shubhranshu Singh made a striking comment: “With the arrival of AI and the multiple tools which are producing content and outcomes at warp speed, why will I buy time, I will buy end outcomes.” For marketers, this signals a shift from traditional media buying to performance contracts directly tied to results. Within Tata’s electric vehicle business, marketing head Pooja Asar has spoken about the role of data and digital storytelling in expanding adoption, particularly in smaller cities. EV marketing is not only about aspiration but also about providing reassurance, information, and community, which is where AI-driven content and CRM become essential.

Behind these brand stories is the reality of a changing regulatory environment. India’s Digital Personal Data Protection Act, 2023, now in effect, requires clear consent for the processing of personal data and allows restrictions on cross-border transfers. Draft rules released in early 2025 expand these obligations further. Marketers must implement robust consent management, preference centers, and clear governance frameworks. At the same time, the Advertising Standards Council of India has tightened rules for influencer marketing, mandating explicit disclosures across platforms. Journalist’s note: for brand and influencer teams, this means AI tools for campaign management must now include compliance as a core feature, not an afterthought.

The broader media economy is also shifting. Retail media has exploded, accounting for nearly a quarter of India’s digital advertising spend by late 2024. This is changing how brands allocate budgets, with e-commerce platforms becoming both retailers and advertising giants. Retail media’s promise of closed-loop measurement appeals to marketers under pressure to prove ROI. Journalist’s note: retail media is both a MarTech and an AI story, because the ability to connect ad spend to SKU-level sales depends on real-time data integration and algorithmic optimisation.

Reliance Jio adds another twist. Its investments in AI platforms such as JioBrain are not only about network operations but also about creating the infrastructure for AI services across industries. As Jio consolidates its telecom, OTT, sports, and commerce arms, marketers are watching closely. The possibility of a single platform that ties together connectivity, content, and commerce is one of the most consequential shifts for India’s media landscape.

Strip away the hype and six areas stand out where Indian marketers are actually deploying AI: audience planning with propensity models, search and discovery improvements, dynamic creative generation, CRM and next-best-action systems, retail media optimisation, and fraud detection. Journalist’s note: most of these are not futuristic applications but deeply operational ones. The glamour is often in the demos, but the real value lies in routing, compliance, and optimisation.

Challenges remain. Data quality is still patchy, and many companies are learning that AI does not fix broken systems but instead magnifies flaws. Measurement continues to be a battleground, with retail media promising precision but cross-platform incrementality still elusive. Governance is resource-intensive, yet unavoidable, especially as consumer trust and regulatory scrutiny increase. And while AI can produce endless creative variants, it cannot originate ideas, which is why human direction continues to matter.

Looking forward, agentic AI systems that draft briefs, generate compliant content variants, and recommend budget reallocations are already creeping into workflows. Search is fragmenting into conversational, social, and voice-led channels, forcing brands to diversify creative assets. Consent-based identity will be the critical enabler, and companies like ITC, HUL, and BFSI players are already moving aggressively in this direction. Retail media will likely remain the fastest-growing channel, with AI creative ops becoming necessary to deliver high-quality assets at scale.

The conclusion is clear: Indian brands are not waiting for perfect models or futuristic breakthroughs. They are embedding AI into the practical, high-leverage parts of the funnel, from customer acquisition and recommendation to fraud detection and compliance. The best examples—HUL’s precision media, HDFC Bank’s governed personalisation, Flipkart’s AI-powered commerce, Cadbury’s hyper-localised campaigns—show that the future of marketing in India is already here, running quietly in the background. What remains is less about discovering new tools and more about mastering the discipline of data, governance, and measurement at scale.