Vernacular AI drives 30–40% higher engagement: Report

A new analysis from LS Digital indicates that Indian consumers show unusually high trust in AI-driven advertising, even as most are still learning the basics of how digital ads work. The findings are part of the company’s latest study, The Rise of AI-Native Advertising in India: Hyper-Personalisation Meets Vernacular Scale, which examines the intersection of consumer behaviour, AI adoption and the country’s expanding digital economy.

The report is based on LS Digital’s proprietary “Quilt” methodology, which uses machine learning to map conversations and search patterns across the open web.

One of the study’s central observations is what LS Digital describes as India’s “AI paradox.” According to the analysis, 99% of consumer search behaviour around native advertising revolves around basic definitions, with only 1% mentioning specific platforms. Despite this limited understanding, 82% of users say they are comfortable with AI-led recommendations, and 48% express trust in AI-generated content, a figure that the firm notes is significantly higher than global levels.

The report argues that this combination of low literacy and high trust is accelerating the development of AI-native ad models in India.

Hyper-personalisation dominates

Hyper-personalised advertising has emerged as the most prominent industry theme, accounting for 47% of all professional discourse captured by the Quilt model. LS Digital attributes this to rising consumer expectations for customised content and the increasing use of AI-powered programmatic tools that enable granular targeting.

Vernacular AI gains ground

The report highlights the rapid rise of Vernacular AI as a strategic priority. LS Digital found that regional-language content is driving 30–40% higher engagement compared to English-only messaging. Vernacular AI-related themes now make up 11% of the overall industry conversation, led largely by multilingual creative adaptation (70%), followed by regional voice interfaces and dialect-level targeting.

The analysis suggests that the articulation of India’s “next billion users” will depend heavily on scaling language-led personalisation.

AI as a leveler for small businesses

With India’s social commerce market projected to reach USD 70 billion by 2030, LS Digital notes an emerging focus on “Democratising Bharat.” Half of the discussions in this segment centre on self-serve AI tools designed for SMEs, allowing smaller enterprises access to precision targeting typically used by larger brands. Additional emphasis areas include Tier 2 and Tier 3 market expansion (13%) and rural inclusion through voice-led, low-cost systems (13%).

Marketers favour human–AI hybrid models

Despite widespread adoption of automation tools, the report finds that 73% of marketers prefer AI to augment, rather than replace, human creativity. Conversations around “creative balance” reveal that most teams use AI for rapid asset production, while relying on human oversight for cultural context and editorial judgment.

Commenting on the findings, Prasad Shejale, Founder & CEO of LS Digital, said India’s digital ecosystem is undergoing a distinct shift. He noted that while consumers are “still learning the basics,” they display high confidence in AI-led personalisation. “Brands that prioritise multilingual creative, which delivers 30–40% more engagement, while building responsible, privacy-preserving AI models, will be the ones to dominate the $70 billion social commerce wave by 2030,” he said.

Regulation and responsibility

The report situates these changes against India’s evolving regulatory backdrop, noting that the Digital Personal Data Protection Act (DPDPA) will require organisations to move toward consent-led data practices and privacy-first AI deployment. It warns that India’s transition to AI-native advertising will depend on balancing hyper-personalisation with user rights, transparency and compliance obligations.

LS Digital concludes that Indian advertising is shifting from event-based messaging to continuous, real-time, context-driven micro-moment engagement, a transition that mirrors global AI adoption trends while reflecting the country’s unique linguistic and cultural landscape.