Why AI could redefine media, measurement and vernacular marketing by 2028

India’s AI moment is steadily rewriting how brands discover audiences, create communication, optimise media, and measure performance, often collapsing traditional silos between technology, media, and strategy. 

At the recent India AI Impact Summit, startups demonstrated solutions that extended far beyond generic chatbots or automation scripts. From AI-led education platforms that adapt to behavioural inputs, to smart surveillance systems capable of real-time anomaly detection, to predictive railway safety models built on pattern recognition and live data feeds, the event underscored how applied intelligence is moving into mission-critical environments. 

Among the technologies on display were SATHEE, an AI-led personalised coaching platform developed with IIT Kanpur that offers study planning, doubt resolution, and analytics for eight major competitive exams in multiple Indian languages. IIRIS, a smart security solution that turns traditional surveillance systems into intelligent risk assessment frameworks by transforming cameras into AI-powered filters that prioritise actionable alerts. RaiLabs’ Arista autonomous inspection system, which uses ultrasonic sensors and predictive diagnostics to detect internal cracks and wheel wear on railway tracks well before human inspections could, promising 200% greater efficiency in preventing derailments.

While these innovations were showcased in sectors like education, public safety, and transport, their core architecture i.e., real-time analytics, continuous learning loops, predictive modelling, and automated decision support, mirrors the exact capabilities marketing ecosystems increasingly demand. Marketing and advertising, in that sense, are emerging as some of the most immediate commercial beneficiaries of this shift.

For instance, CoRover AI has been pushing the boundaries of conversational intelligence with BharatGPT and its recently launched DeskAI appliance, an offline AI assistant designed to function in low-connectivity environments. By leveraging NVIDIA infrastructure to enable offline deployments, CoRover is positioning AI not merely as a cloud-based enterprise layer, but as distributed intelligence capable of powering customer support, lead generation, vernacular engagement, and real-time decisioning across Bharat. “The innovative initiative leveraged voice-based interactions to engage consumers without internet or smartphones. The idea is to go where the customer is, and interact in their language, real-time. AI platforms can process vast amounts of data to deliver context-aware, hyper-personalised experiences at scale,” Ankush Sabharwal, Founder & CEO, CoRover told e4m.

On the agency front, Tonic Worldwide recently launched Groth, a full-funnel marketing intelligence platform built to unify fragmented dashboards into a single decision-making ecosystem. Rather than adding another analytics layer, Groth integrates market intelligence, AI visibility, creative performance auditing, and unified attribution into a connected framework, attempting to solve what growth marketers often describe as having “too much data and too few answers.”

These developments set the stage for a deeper structural shift underway in India’s marketing and advertising landscape. 

According to Chetan Asher, Founder and CEO of Tonic Worldwide, over the next two to three years, media optimisation and attribution are likely to move fastest toward AI-led decisioning, while discovery and creative functions will remain hybrid. He points to the fact that marketing and sales already rank among the highest AI adoption functions globally, particularly in segmentation and optimisation. With signal loss and privacy shifts complicating traditional measurement models, attribution is moving toward probabilistic, model-driven systems. Platforms like Groth, he suggested sit at this inflection point, combining predictive analytics with human validation to compress optimisation cycles without eliminating strategic oversight. In other words, AI may increasingly determine what to optimise and when, while humans define why.

Adding to this, Sabharwal said, AI will automate tasks like ad targeting, content creation, and campaign optimisation, allowing marketers to focus on strategy and creativity. “For instance, AI-powered tools can analyze user data to predict ad performance and adjust bids in real-time, increasing ROI. We expect AI to redefine areas like customer segmentation, personalization, and measurement, enabling more precise and effective marketing.”

The question of whether AI startups will partner with agencies or compete with them for budgets is also beginning to crystallise. 

Asher believes AI companies are more likely to act as strategic partners in the near term, especially as operational readiness across enterprises remains uneven. This capability gap creates room for agencies to integrate AI deeply into planning and execution rather than be displaced by it. Groth, he frames, is not a self-serve tool layered on top of existing systems, but an intelligence framework built to translate AI outputs into business-aligned marketing action. The implication is clear: agencies that embed AI into their core processes could strengthen their strategic relevance rather than lose it.

Chandrakant Agrawal, Co-Founder and CEO of AppSquadz, argues that automation across audience segmentation, media planning, and bid optimisation is no longer optional for brands that want to remain competitive.

According to Agrawal audience segmentation, media planning, and bid optimisation is no longer optional for brands that want to remain competitive. He added that traditional customer journey mapping is giving way to dynamic, AI-driven personalisation, where systems continuously adjust messaging, targeting, and budget allocation based on live behavioural signals. Reporting, too, is shifting from static dashboards to real-time insight engines that generate actionable recommendations rather than retrospective summaries. The transformation, he suggests, lies not just in automation but in intelligence, systems that learn and optimise without human lag.

He added that in the immediate term, AI startups will enhance agency capabilities through analytics and automation, while agencies retain ownership of brand strategy and storytelling. Over time, however, AI-native firms could begin competing for performance-driven mandates, particularly where measurable ROI becomes the primary decision criterion. Agencies that fail to embed AI deeply into their workflows, he cautions, may see portions of their budgets migrate to technology-first platforms.

Adding perspective to this, Maaz Ansari, Co-founder & CRO, Oriserve, said, “I believe we’ll see more partnerships between AI startups and marketing agencies in the future. When you think about it, successful marketing has two key components, creative vision and painstaking execution. Agencies understand brands. They hold relationships, strategic context and creative judgment. What they’ve historically struggled with is execution at scale and personalisation at depth. That’s exactly where AI plays.

“The smarter agencies are already figuring this out. The real competition isn’t between AI startups and agencies, it’s between agencies that adopt AI infrastructure and those that don’t.”

Oriserve’s speech-to-text and text-to-speech platform Tarang is built to handle what Ansari describes as the “Indian noise”, mixed languages, accents, and background disruptions common in Tier-2 and Tier-3 environments. By reducing latency to around 100 milliseconds, AI conversations begin to feel human. Traditional marketing tools, he noted, are broadcast mechanisms; AI-driven engagement platforms enable a million one-on-one conversations simultaneously. That shift could structurally expand who brands are able to reach.

Ramesh Ravishankar, Co-Founder & Chief GTM Officer, Highperformr.ai, added, “AI won’t improve marketing as we know it; it will replace it. Teams will get smaller and sharper, SDRs will evolve into AI-powered full-stack GTM operators, and brands will need to optimize for AI engines, not just Google. The winners won’t be thin wrapper; they’ll have real data moats and deep workflow integration. India has a clean slate. This is our window to build the next generation of marketing infrastructure.”

As per experts, budget allocation patterns also reflect an inflection point. 

Currently, most brands treat AI as embedded within digital or martech budgets, often in experimental phases focused on content automation or performance optimisation. However, the trajectory is shifting. 

Sabharwal points to industry data showing that 47% of Indian enterprises already have multiple AI use cases live in production, signalling that AI adoption is moving beyond pilots. 

By 2028, experts expect AI budgets to grow significantly, particularly in areas like hyper-personalisation and predictive analytics.