As AI moves deeper into the marketing stack, India’s growth leaders are clear on one thing: technology may accelerate execution, but it cannot replace human judgment. At the first episode of MartechAI Webinar Series 3.0, leaders from Zepto, Navi, STAN, Awshad and 10on10 Foods discussed how AI is reshaping creative production, customer support, campaign analytics, personalization and creator-led growth. But the conversation also revealed a sharper reality for marketers in 2026: AI can make brands faster and more efficient, but trust, cultural nuance and original thinking still need people at the centre.
Artificial intelligence has moved from being a marketing experiment to becoming part of the daily operating system for growth teams. From creative production and campaign reporting to customer support, personalization, data analysis and creator enablement, AI is no longer sitting at the edge of marketing innovation. It is beginning to influence how brands plan, execute and optimize growth.
That was the central theme of the first episode of MartechAI Webinar Series 3.0, hosted by e4m, titled “The New Marketing Engine: How AI is Rewiring Growth in 2026.” The session brought together Pawrush Elavia, VP Growth, Zepto; Richa Jaggi, Co-founder and Chief Marketing Officer, Awshad; Nauman Mulla, Co-founder, STAN; Dr. Ashish Bajaj, Co-founder, 10on10 Foods; and Abhijeet Sinha, Senior Manager, Growth Marketing, AI, Navi. The session was moderated by Brij Pahwa, Editorial Lead, e4m and MartechAI.com. Vikas Nair was listed on the webinar creative but was not present in the discussion.
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The discussion opened against the backdrop of India’s fast-growing advertising and digital economy. As brands chase higher efficiency, deeper personalization and faster campaign execution, the real question is no longer whether AI will affect marketing. It is how brands can use it without losing originality, cultural nuance and human judgment.
Richa Jaggi said AI is already rewiring marketing, but the shift did not happen overnight. According to her, the foundations were laid when marketing began moving to a digital-first model and teams started expecting faster turnaround, sharper targeting and more measurable outcomes. For Awshad, AI is helping most in areas such as automation, data crunching, optimization and intent-based targeting. Tasks that were earlier manual and time-consuming are now easier to manage, although she cautioned that her team is still not allowing AI to operate without human oversight.
Pawrush Elavia said Zepto has taken a significant plunge into AI-led creative production. For a platform with thousands of product categories, it is not practical to manually create every possible creative variation. AI has helped the team compress timelines significantly. What earlier took three to seven days can now often be completed in one or two days. He said AI is helping even before campaigns go live by reducing production time, while also supporting campaign reporting and analysis later.
Zepto is also using AI tools to understand which creatives, cities, stores and cohorts are performing better. Earlier, this kind of work would require analysts to write queries and manually pull insights. Now, AI tools are helping growth teams summarize performance faster and free up time for higher-value work. Elavia said the shift also requires marketers to trust AI enough to let it make their work easier, while still knowing where human direction is needed.
Dr. Ashish Bajaj brought in a different perspective, comparing his earlier role as a group CMO with his current entrepreneurial role. He said that as a CMO, AI was largely seen as a productivity and efficiency tool. As a founder, he now also sees it as a cost-saving tool. However, he warned that overdependence on AI can reduce creative thinking. He recalled instances where people using AI for routine work were no longer thinking deeply and were simply modifying older prompts. He also shared that two freelancers from different cities sent him nearly identical project plans for a website, suggesting that AI-generated sameness is already becoming visible.
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Jaggi agreed with that concern, especially from the lens of a founder running a lean marketing team. She said junior team members often default to AI for hooks and ideas instead of contributing original thinking. For her, the challenge is not whether AI should be used, but how to ensure teams do not lose the habit of thinking creatively. She said she sometimes pushes her team away from screens and back into real-world settings to restore human creativity in content and campaign thinking.
Nauman Mulla said STAN’s use case is different because the platform’s growth has been heavily influencer-led rather than dependent on Google and Meta spends. He said STAN has scaled to millions of users through gaming creators and community-led growth. For the company, AI has been more useful in retention than acquisition. STAN uses AI to coach creators before and after live streams. Before going live, creators can warm up with AI, share topics and receive suggestions. After the stream, they can get analysis on performance. According to Mulla, better-trained creators improve engagement, which in turn helps user retention.
He added that AI has also helped STAN in discovery, safety and language support. The platform has built systems that support multiple Indian languages, allowing regional creators to scale. For gaming audiences, he said, standard ads do not work in the same way because gamers are quick to skip them. That makes community, creator-led formats and deeper integrations more important than conventional ad delivery.
Abhijeet Sinha said Navi is using AI across several parts of the growth engine. In customer support, AI is helping automate interactions. In sales-led use cases such as motor insurance, bots are being tested to speak with customers in ways that can match human-like assistance. From a growth marketing standpoint, AI is helping simplify analytics, affiliate operations, data sharing and campaign monitoring.
Sinha said AI is freeing teams from process-heavy work and allowing them to focus more on customer understanding. Navi has tested AI-led systems that monitor campaign performance, detect what is working, identify patterns and suggest improvements. He said this has made feedback loops shorter and helped the team become sharper. However, he also pointed out that AI-generated creatives can feel emotionally flat. Navi has experimented with a creative-maker bot and a checker bot, where the second system checks for emotional flatness and other errors. Even then, he said human quality control remains important.
The most intense part of the discussion centered on whether AI improves creativity or makes brands look and sound the same. Jaggi argued that AI can replace repetitive marketing tasks, but not actual marketers. For Awshad, trust is built through real people, reviews, authentic stories and human-led messaging, especially because the brand operates in a category where customer education is more important than acquisition. AI helps with research, blogs, medical information and SEO, but cannot build trust on its own.
Elavia offered a counterpoint from Zepto’s experience. He said that during a brand campaign featuring well-known celebrities, the team later layered the campaign with AI-based creatives, including unusual and experimental formats. Some of those AI-assisted creatives performed better. His point was that AI output depends heavily on the quality and originality of human inputs. If creative teams use AI boldly and differently, it can improve campaign performance rather than flatten it.
The panel broadly agreed that the future of AI-led marketing will not be about replacing people entirely. Instead, marketers will need to become better at prompting, contextualizing, testing and supervising AI systems. The creative edge may come from the human ability to ask unexpected questions, understand culture and identify what will resonate in a specific moment.
The conversation then moved to data and personalization. Dr. Bajaj said AI makes it easier to compartmentalize complex consumer data by tier, age, demographics, usage and psychographics. For a country as diverse as India, where consumer behavior changes dramatically across cities, regions and categories, he said AI can help marketers make sense of different data stacks and create more relevant outputs. Earlier, one marketer had to understand multiple audiences and build campaigns across festivals, geographies and demographics. AI can now help compress that complexity.
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Sinha, however, cautioned that personalization only works when it is genuinely relevant. He said brands often claim to personalize communication, but if the underlying hypothesis is shallow, personalization can become confusing or even irritating. He gave the example of pushing a product to a customer based only on limited demographic assumptions, instead of deeper behavior and intent data. According to him, the ideal scenario is to send the right message to the right customer at the right time on the right channel, but that requires strong guardrails.
Elavia added that personalization existed even before AI, but AI enhances the marketer’s ability to do it at scale. The danger lies in losing control of it. Dr. Bajaj illustrated the risk through healthcare marketing, saying that if a person with a cardiovascular concern receives an oncology-led message, the personalization fails completely. For him, the marketer’s intention should be to stay relevant from the consumer’s point of view, not simply from the brand’s product-selling point of view.
The panel also discussed the future of AI agents and emotional AI. On timelines, the speakers differed. Sinha said full agentic and emotionally intelligent marketing is not likely in the immediate future and may not happen within the next year. Dr. Bajaj was more aggressive, suggesting that major progress could happen within six to eight months. Elavia said it may take a couple of years, though he also noted that use-case-specific agents are already emerging, including voice-led ordering experiences in quick commerce.
What stood out across the session was that AI is already transforming the mechanics of marketing. It is reducing production timelines, automating reporting, enabling micro-personalization, supporting creator coaching, improving customer support and helping teams act faster. But the panel was equally clear that AI alone is not the advantage.
The real advantage lies in how brands combine AI with human judgment, cultural understanding, emotional intelligence and category context. In 2026, the winners may not be the brands that use the most AI, but the ones that know where to automate, where to supervise and where to let humans lead.
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