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Enterprises in India are quietly shifting how they build brands, and the movement is not starting in media plans or campaign storyboards. It is happening inside backend systems, in the customer data layers, content pipelines, and decisioning models being infused with generative AI. These investments, once small experiments, have become strategic priorities.
India’s enterprise generative AI market was valued at USD 183 million in 2024 and is projected to grow at more than 38% annually to USD 1.2billion by 2030. The broader AI market is expected to surpass USD 8billion in 2025 and is projected to more than triple to USD 17 billion by 2027, according to industry forecasts.
This dynamism is fuelled by companies like Ergo, which has committed €130million to building GenAI capabilities using India as a strategic center for engineering talent, as well as infrastructure investments from AWS, which plans to deploy USD 12.7billion in India by 2030, and Microsoft, which has pledged USD 3 billion over the next two years to accelerate AI and cloud development.
It is within this context that Venugopal Ganganna, co-founder and CIO at LS Digital, sees brand-building being fundamentally rewired. “Traditional top-of-funnel advertising isn’t going away, but it’s now being deeply informed by backend intelligence—customer modeling, predictive behavior, and dynamic personalization. With large-scale GenAI deployments, especially at the enterprise level, brand-building is no longer a one-way narrative.”
The shift he describes is not hypothetical. Major banks are now running GenAI models that simulate campaign scenarios before they spend a rupee on media, while consumer goods companies are dynamically adapting creatives across geographies based on predictive segment behaviour.
Ganganna’s point is that awareness, consideration, and loyalty are no longer sequential stages; they operate as a continuous optimisation loop in which AI stitches insights and actions together in real time.
This shift changes the very definition of brand presence. Jacob Joseph, VP Data Science at CleverTap, argues that AI is expanding brand-building into spaces that were never considered marketing before. “GenAI isn’t replacing top-of-funnel marketing, it’s turning the entire customer journey into a brand-building opportunity,” he says.
That means a personalised onboarding flow for a telecom customer can carry as much brand weight as a prime-time TV spot, and an e-commerce recommendation engine tuned to a user’s past behaviour can do more for loyalty than a generic discount campaign.
The logic is backed by enterprise activity: Indian IT majors like TCS and Wipro are integrating AI-led personalisation into global client platforms, embedding marketing functions deep inside product and service layers. Joseph’s emphasis is that the loud opening act of a campaign still matters, but it now plays alongside hundreds of quiet touchpoints that cumulatively shape how a brand is understood and trusted.
For the marketing supply chain, this evolution is forcing a rethink of where value lies. Rajiv Dingra, founder and CEO of ReBid, says enterprise investments in GenAI are compressing the funnel. “Demand can be generated and captured faster because AI is constantly optimizing messaging, channels, and offers in near real time.” That compression has tangible effects. Global fashion retailers operating in India are running AI models that adjust ad placements and creative sequencing hour by hour, while fintech companies are using predictive models to shift spend instantly between acquisition and retention channels based on customer behaviour signals.
The outcome is that fewer resources are being devoted to broad, expensive awareness pushes, and more are going into systems that can capture and convert demand the moment it surfaces. Dingra notes that this also redefines agency relationships: execution-heavy retainers are giving way to partnerships where the agency’s currency is its fluency in data, AI architecture, and cultural context.
Execution itself is changing too. Siddharth Jhawar, country manager at Moloco India, highlights how AI is becoming a co-pilot for both creative and media decisions. Marketers are generating multiple ad concepts with AI, running them through rapid tests to identify winners, and only then investing in high-quality production. On the media side, advanced machine learning systems trained on the behaviours of high-value customers are making programmatic buying far more precise, bidding only on the individuals most likely to generate meaningful revenue.
This is already in play with Indian gaming platforms and app-first consumer brands, which are using AI decisioning to avoid wasting impressions on low-value audiences, directly improving return on ad spend. The result is not just efficiency but a reallocation of budget from indiscriminate reach to targeted impact.
According to Hitarth Dadia, CEO and partner, NOFILTR, "If brands can use AI to plan, test, and optimise creative/targeting internally, media buying and agency partnerships will need to either: plug directly into these AI-driven systems, or bring something AI can’t yet replicate, taste, cultural intuition, storytelling that isn’t just data-backed but culturally sound.
"The danger for agencies is being stuck in execution while not moving towards strategic infrastructure in-house. The opportunity is to become the human layer on top of the machine, where brand soul, not just brand efficiency, lives."
India’s advertising spend is projected to grow 7.8% in 2025 to ?1.37 trillion, with digital commanding the largest share at around ?72,800 crore (51% of total spend). While digital’s share is rising, so is the pressure on CMOs to prove measurable ROI and leverage data-driven insights.
The lure of AI investment lies in its compounding effect: once a model is trained and integrated into systems, it works continuously across campaigns, owned platforms, and customer service, influencing outcomes long after a media buy has ended. For a brand, the choice is increasingly between renting attention through media or owning an intelligent infrastructure that drives value over time.
The implications are significant. For brands, it means thinking of marketing not just as an external broadcast but as an internal capability woven through the business. For agencies, it demands moving upstream to design and manage AI-enabled growth systems that integrate paid, owned, and earned channels. For adtech vendors, it challenges the dominance of external platforms by shifting more decision-making inside the enterprise’s own systems, pushing them to become interoperable partners rather than gatekeepers.
Enterprise AI is not arriving with a sudden, disruptive event. It is seeping into marketing practice through predictive audience modelling, adaptive creative, and precise bidding. Each of these steps may seem incremental, but together they are restructuring how brands in India allocate budgets and build equity.
The companies that treat AI as a bolt-on to existing processes may see some gains, but the ones that let it redefine how they orchestrate growth could find themselves controlling not just their message, but the architecture of their future market share. In a country where digital advertising and enterprise AI are both set to grow sharply in the next five years, that may be the most important brand investment they can make.
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