India's digital advertising sector is navigating a fundamental shift as the gradual phase-out of third-party cookies converges with accelerating adoption of predictive artificial intelligence technologies. This transformation is reshaping targeting infrastructure across the country's Rs 49,251 crore digital advertising market, which closed 2024 with 21.1 percent growth and is projected to reach Rs 59,200 crore in 2025, according to the dentsu-e4m Digital Advertising Report 2025.
Google's approach to third-party cookies has evolved considerably since initial announcements in 2020. The company began restricting cookies for one percent of Chrome users in January 2024, affecting approximately 30 million people globally. However, in July 2024, Google reversed its complete deprecation plans, instead introducing a user choice model that allows Chrome users to control third-party cookie access through browser settings. This decision followed regulatory scrutiny from the UK's Competition and Markets Authority and divergent feedback from industry stakeholders.
Despite this reversal, the trajectory toward reduced cookie dependence remains clear. Safari and Firefox blocked third-party cookies years earlier, creating a fragmented ecosystem where significant portions of web traffic already operate without cookie-based tracking. Indian marketing organizations face substantial readiness challenges. A survey conducted by Kiaos Marketing in December 2023 found that over 92 percent of Indian marketers rated their readiness for the cookieless era below six on a scale of ten.
Vishal Chinchankar, formerly CEO of Madison Digital and Madison Media Alpha, estimated in January 2024 that "only 10 percent to 12 percent of advertisers would have invested in their tech maturity curve to be future-ready." The readiness gap indicates substantial infrastructure challenges ahead, particularly for small and medium enterprises that lack resources to rebuild marketing technology stacks.
Predictive AI technologies are emerging as the primary alternative for maintaining precision without cross-site tracking. The technology analyzes first-party data, behavioral patterns, and contextual signals to forecast customer intent and purchasing probability. Global AI marketing revenue is projected to exceed $107.5 billion by 2028, with 69.1 percent of marketers already integrating AI into their operations. Nearly a quarter of businesses now spend more than 10 percent of marketing budgets on AI initiatives, according to industry research.
Indian martech platforms have accelerated development of predictive capabilities to address market needs. Companies including Netcore Cloud, WebEngage, and CleverTap have integrated AI prediction engines into their customer engagement platforms. Early adopters in India's e-commerce and financial services sectors report conversion rate increases of 20 to 35 percent when deploying predictive AI models compared to traditional cookie-based targeting.
The shift toward predictive AI demands substantial infrastructure investments. Building effective prediction models requires clean, structured first-party data. Research from the Data Security Council of India indicates that while 73 percent of large enterprises have initiated first-party data strategies, only 31 percent of small and medium businesses have begun similar preparations.
Harsha Razdan, CEO of dentsu South Asia, stated during the launch of the dentsu Digital Advertising Report 2025 in February: "The future isn't a distant concept. It's built in real-time, in the decisions we make today. The brands that will lead tomorrow are the ones that see through the noise, connect the dots, and act before the world catches up."
The implementation challenge extends beyond technology to organizational readiness. Many Indian companies operate with data silos, inconsistent customer records, and legacy systems not architected for unified customer data platforms. The talent shortage compounds implementation barriers. Industry estimates suggest demand for AI-specialized marketing talent has grown 150 percent year over year, while supply has increased only 60 percent, creating recruitment competition and salary inflation.
India's Digital Personal Data Protection Act, 2023, which became enforceable in 2025, is accelerating the move toward privacy-preserving marketing technologies. The legislation mandates explicit user consent for data processing and grants individuals data erasure rights. Anita Kotwani, Chief Client Officer for South Asia at dentsu, acknowledged the regulatory challenges in January 2025: "In 2025, the media industry will face several headwinds that will challenge its growth and operations. One significant hurdle will be the tightening of data privacy regulations, like the evolving data protection laws in India. As demand for personalized advertising increases, media agencies will be forced to navigate complex compliance requirements, which could lead to higher operational costs and adjustments in data collection practices."
Financial services companies are implementing prediction models that analyze transaction patterns and life events to forecast when customers will need specific products. Banks are deploying AI systems that identify customers likely to require personal loans, investment services, or insurance products based on behavioral signals and financial milestones. HDFC Bank, State Bank of India, and ICICI Bank have implemented machine learning models for personalized product recommendations, with reported improvements in customer engagement rates of 25 to 40 percent, according to banking sector reports.
E-commerce platforms use predictive algorithms to anticipate purchase intent and optimize inventory allocation. Indian e-commerce companies including Flipkart leverage AI algorithms to provide personalized product recommendations to customers. Fashion retailers employ AI to forecast trending styles weeks in advance, allowing more targeted campaign planning. Research indicates that AI-driven recommendations account for up to 35 percent of online sales, with companies excelling at AI-driven personalization generating 40 percent more revenue than those that don't.
The education technology sector applies predictive AI to identify professionals most likely to complete specific courses based on learning patterns and career progression data. Healthcare and wellness brands use predictive models to identify patients who may benefit from preventive health screenings or wellness programs, working from anonymized aggregated data. Food delivery platforms employ predictive systems to forecast ordering patterns based on weather conditions, local events, and first-party customer data.
Programmatic advertising, which accounts for 42 percent of India's digital media spending (approximately Rs 20,686 crore in 2024), is adapting to cookieless environments. The segment is expected to grow to 44 percent of digital spend by 2026, according to projections, but the underlying mechanisms are shifting from cookie-based audience targeting to contextual signals and first-party data activation.
Narayan Devanathan, President and Chief Strategy Officer for South Asia at dentsu, emphasized the strategic importance of martech in March 2025: "As the dots between media, creative, and customer experience connect more intimately, Martech has become the spine that unites these disciplines, enabling powerful, data-driven connections that drive meaningful outcomes. India's Martech landscape is evolving rapidly, redefining how brands engage with consumers."
Retail media is emerging as a significant advertising channel, with ad spends on e-retail platforms growing at 23.43 percent annually. By integrating first-party shopping data, brands can target high-intent consumers with precision, creating closed-loop measurement systems that don't depend on third-party cookies. The evolution toward privacy-preserving programmatic infrastructure is accelerating investments in data clean rooms, identity resolution frameworks, and contextual targeting technologies.
Despite accelerating AI adoption, most Indian marketing organizations implement hybrid approaches that combine multiple targeting methodologies. This pragmatism reflects technical realities in India's digital ecosystem. While Google Chrome holds approximately 65 percent browser market share, significant traffic occurs through browsers and applications where third-party cookies continue operating normally.
Connected TV advertising and mobile in-app advertising, both growing rapidly in India, operate on different technical frameworks than web-based cookies, requiring distinct targeting approaches. Marketing teams are building flexible infrastructure that doesn't depend entirely on any single methodology, recognizing that complete cookie deprecation may take longer than initially anticipated while alternative solutions mature.
Companies that began testing predictive approaches 18 months ago are now operationalizing systems that deliver measurable advantages in customer acquisition efficiency. For Indian marketing organizations, success depends on strategic implementation that addresses data infrastructure, talent development, and organizational change management. The next phase of this evolution will likely separate organizations that can effectively integrate predictive capabilities from those that struggle with implementation complexity.
