AI takes over india’s ad spend—but quality still reigns

By mid-2026, India's digital advertising budgets are undergoing a profound structural shift toward AI-driven environments that emphasize measurable outcomes, first-party data, and commerce integration. This transformation is fueled by emerging platforms such as Connected TV (CTV), OTT, and recommendation-driven digital video, which offer richer consumer data and new engagement opportunities. Industry leaders like Google, Meta, Amazon, and Walmart Connect exemplify this trend, integrating AI not only for campaign optimization but also to influence consumer discovery, product recommendations, and entirely new advertising inventory formats.

Forecasts for FY27 suggest that 70-80% of digital media spend by large Indian advertisers will be meaningfully optimized by AI, a sharp acceleration from current levels where only 10-15% of budgets are directly allocated to AI tools. However, AI’s influence extends far beyond direct spend, embedded within existing platforms to optimize bids, audience targeting, creative generation, and budget allocation. As Rajiv Dingra notes, this shift is transforming media buying roles, moving agency focus from manual execution toward strategic AI orchestration, data analytics, and creative intelligence, which could disrupt traditional agency revenue models.

Rather than creating new marketing budgets, AI-driven advertising largely reallocates existing spend, with 65-75% of AI investment redirected from manual campaign operations, agency fees, and conventional production. Currently, AI influences between 35% and 60% of digital ad expenditure among digitally mature Indian brands, with Ajay Varma highlighting that 35-40% of spend is AI-linked today, up from 10-20% a year ago. The largest portion of this AI-driven spend focuses on media buying and programmatic bidding—which accounted for 42% of India’s digital media spend in 2025 and is projected to rise—followed by audience targeting, creative generation, personalization, and measurement.

Generative AI is expanding the scope of AI’s role in advertising from media placement to creative optimization, enabling faster, more cost-effective production of personalized ad variations. According to Salesforce’s 2026 India State of Marketing report, 81% of Indian marketers have adopted AI, with 83% seeking more personalized content and 81% turning to AI to bridge this gap. This evolution underscores AI’s growing centrality not just in media spend allocation but also in delivering tailored creative experiences that drive engagement and conversion.

By mid-2026, the role of agencies in India's digital advertising landscape has fundamentally shifted from manual campaign execution to strategic orchestration of AI-driven processes. Industry leaders like Mathur emphasize that while AI algorithms handle thousands of operational decisions such as bidding and targeting, agencies retain control over defining business objectives, audience strategies, and measurement frameworks. This evolution favors agencies with deep expertise in business understanding, data strategy, platform architecture, and measurement capabilities, as they become indispensable partners guiding AI’s application rather than mere operators of advertising platforms.

As AI increasingly automates repetitive media operations, the economic value of traditional media buying is declining, but agency revenues are not disappearing; instead, they are migrating towards areas like data analytics, technology integration, creative intelligence, and AI orchestration. Experts such as Dingra and Varma highlight that up to 80% of large brands’ digital media spend could be AI-optimized by FY27, with 45% of AI-enabled spend focused on media buying, followed by audience targeting and creative generation. This transition is reshaping agency remuneration and production economics, as AI takes over execution-heavy tasks like automated bidding and creative versioning, prompting agencies to pivot towards strategic and experimental roles.

AI’s integration into digital advertising budgets is seamless rather than additive, with no separate AI spend but rather a transformation within existing media and marketing budgets. Leaders like Ajay Varma and Pankaj Srivastava note that AI operates beneath current campaigns, influencing bids, audience selection, creative personalization, and optimization, effectively embedding itself into the fabric of media buying. This nuanced integration challenges agencies to balance algorithmic automation with human oversight, especially as advertisers grapple with measuring AI-driven customer journeys and optimizing content for AI discovery, underscoring the ongoing need for strategic human input alongside AI tools.

The advent of AI-powered tools such as Google’s Meridian MMM chatbot exemplifies the evolving agency role toward strategic AI orchestration and sophisticated measurement. By enabling marketers to build, audit, and optimize marketing mix models with AI assistance, and incorporating advanced features like GeoX geotesting for geographic segmentation and upper-funnel signal integration, agencies can now blend algorithmic automation with nuanced human strategy. This development reflects a broader trend toward data-driven, multi-dimensional campaign measurement that enhances attribution accuracy across channels like TV and DOOH, reinforcing the critical partnership between AI capabilities and human expertise in media buying.

By early 2026, Indian consumers have embraced AI-driven advertising with enthusiasm, recognizing its potential to enhance their online experiences, as evidenced by 82% expressing positive views. However, this acceptance hinges heavily on the quality and transparency of AI-generated ads; 65% favor polished AI content, while nearly a third warn that low-quality AI ads can damage brand perception. Despite this consumer openness, marketers remain cautious—61% express concerns about brand safety linked to low-quality AI content, and over half are wary of advertising within AI platforms due to relevance and quality issues, underscoring a tension between consumer receptivity and marketer apprehension.

Indian consumers demonstrate a strong preference for fewer but highly relevant advertisements, with 84% willing to share their browsing history to achieve personalized ad experiences, according to a Criteo report. Yet, a significant gap persists in effective personalization, as 71% still encounter repetitive messaging, reflecting challenges in delivering truly tailored content. This disconnect is compounded by consumers’ fragmented, multi-channel shopping journeys—over half research products outside retail platforms—making seamless personalization more complex and highlighting the need for improved data integration and attribution methods.

While AI adoption is growing in backend retail operations across India, its use for dynamic, real-time ad personalization remains limited, revealing a substantial opportunity for brands to develop more connected and responsive AI-driven advertising strategies. This lag in leveraging AI’s full potential for personalized ad delivery contributes to the fragmented consumer experience and challenges advertisers face in measurement and data standardization, suggesting that bridging this gap could significantly enhance ad relevance and consumer satisfaction.

By early 2026, augmented reality (AR) had firmly established itself as a pivotal marketing tool in India, especially among Gen Z consumers who increasingly rely on immersive formats to inform their purchase decisions. A Snap Inc. and Kantar study revealed that 92% of Indian consumers view AR as integral to their shopping experience, with three-in-five Gen Z users engaging longer with AR content and two-thirds crediting it for better product understanding. Meanwhile, gaming and extended reality (XR) platforms have quietly amassed massive, highly engaged audiences—mobile gaming alone boasts over half a billion users—yet brands have been slow to tap into these channels, allocating only a small fraction of their ad budgets despite the clear potential to reach attentive, participatory consumers.

The participatory nature of gaming audiences presents a unique engagement paradigm where viewers are not passive but active participants in live, unscripted narratives, often interacting in real time and spending money on in-game items. This dynamic offers brands a rare opportunity to connect with consumers in a highly attentive state, yet the lack of standardized measurement frameworks and concerns over brand safety have made agencies hesitant to commit significant resources. Without consensus on how to quantify impressions across live streams, Discord communities, or branded assets, brands struggle to justify investments despite the clear engagement advantages these platforms offer.

Extended reality is undergoing a quiet renaissance after the early metaverse hype and subsequent disillusionment, emerging in more practical and accessible forms such as smart glasses, mixed-reality headsets, and AR-native social filters. However, this evolution has yet to translate into proportional brand investment, as many advertisers remain cautious, still navigating the lessons from past overenthusiasm. Snap's head of Ad Revenue underscores this shift, noting that India's AR market is moving beyond mere experimentation to deliver tangible business outcomes, signaling a maturation of immersive experiences from upper-funnel awareness to actionable consumer engagement.

By early 2026, AI capabilities had become a dominant factor shaping smartphone purchases in India, with 89% of buyers prioritizing seamless AI integration alongside performance and affordability, according to the Counterpoint Research and Flipkart report. This shift marks a move away from purely spec-driven decisions toward valuing long-term utility across diverse daily activities such as work, entertainment, and content creation. Concurrently, consumers are adopting more deliberate and extended upgrade cycles, reflecting rising baseline expectations for camera quality, battery life, and overall design, while still emphasizing value for money and personal expression.

AI’s influence on consumer behavior in India is nuanced across demographic lines, revealing varied adoption patterns that underscore its widespread integration. Gen Z users predominantly leverage AI features for creative content generation, millennials harness AI to boost productivity, and women increasingly rely on AI for lifestyle assistance, illustrating how AI is tailoring smartphone experiences to meet distinct needs and preferences across the population.

By early September 2026, Indian advertisers grapple with significant challenges in measurement, attribution, and data standardization, which severely constrain the effectiveness of dynamic AI-driven ad personalization. According to a Criteo report, 84% of Indian consumers prefer fewer but more relevant ads, even if it means sharing their browsing history, underscoring the critical need for precise targeting. However, despite AI's growing role in backend retail operations, its deployment for real-time, dynamic ad personalization remains limited, revealing a substantial opportunity for brands to develop more connected, AI-powered full-funnel advertising strategies that can deliver seamless and personalized consumer experiences.