Leaders from Zivame, Urban Ladder, Yoga Bars, DrinkPrime, and Trustsignal gathered at the ETRetail E-Commerce and Digital Natives Summit 2026 to debate the role of artificial intelligence in direct-to-consumer (D2C) growth. The panel, titled “Can You Trust AI to Run Your Growth Engine?”, featured Kiruba Devi, COO of Zivame; Vivek Mehta, CEO of Urban Ladder; Aditya Anand, Co-Founder & CMO of Yoga Bars; Manas Ranjan Hota, Co-Founder of DrinkPrime; and Mohammad Imran Shaikh, CEO & Co-Founder of Trustsignal, moderated by Sunitha Vishwanathan, Partner at Kae Capital. The discussion centered on how AI is reshaping growth engines while human judgment remains indispensable.
AI in Performance Marketing
Panelists highlighted that AI has already begun transforming performance marketing workflows by enabling faster feedback loops, better targeting insights, and improved campaign optimisation, according to the source. Manas Ranjan Hota of DrinkPrime said AI-driven analytics has helped reduce customer acquisition costs by enabling real-time interpretation of lead quality and campaign performance. However, he emphasised that while AI improves efficiency in performance marketing, it is currently more effective in analysing outcomes than fully automating execution. He noted that human sales interactions still play a critical role in understanding customer intent, pricing sensitivity, and trust barriers, which are then fed back into marketing systems for optimisation.
Retention vs. Acquisition: Where AI Excels and Fails
Mohammad Imran Shaikh of Trustsignal said AI is more effective in retention-led communication than in acquisition, particularly because it requires behavioural learning over time. He noted that AI systems need sustained behavioural data to personalise engagement meaningfully, adding that current applications are largely limited to automation rather than deep behavioural prediction. In contrast, Vivek Mehta of Urban Ladder offered a differing view, stating that AI has already matured significantly in acquisition, especially through platforms like Google and Meta, which now largely run automated optimisation systems. He noted that retention, however, still requires emotional connection, brand trust, and product experience—areas where human involvement remains critical. He added that while AI can optimise operational marketing tasks, it is not yet capable of defining brand positioning or category strategy independently.
AI Accelerates Content Production
Panelists highlighted how AI has significantly accelerated content production cycles, particularly in performance marketing. According to the source, AI tools have reduced dependency on physical shoots, creators, and production timelines, enabling brands to test multiple creative variations at scale. However, they added that the effectiveness of content still depends on human judgment in selecting narratives, brand positioning, and emotional resonance.
Where AI Falls Short
A key part of the discussion focused on the limitations of AI. Panelists said chatbot systems and automated customer service flows often struggle with emotional nuance and escalation handling, leading to customer dissatisfaction in complex queries. They noted that while AI can efficiently handle structured responses, it often fails in scenarios requiring empathy, judgment, or personalised escalation. Manas Ranjan Hota added that fully automated customer interactions without human fallback can negatively impact Net Promoter Score (NPS) and trust if not carefully designed. Vivek Mehta pointed out that AI tends to optimise for what is measured, which can sometimes conflict with broader business goals. He noted that while AI is effective at improving metrics like return on ad spend (ROAS), it may over-index on existing customers rather than expanding new customer segments. He added that strategic decisions such as brand positioning and category strategy remain beyond AI's current capabilities.
Panelist Perspectives at a Glance
The following table summarises the key positions of panelists on the role of AI in D2C growth:
| Panelist | Company | Key View on AI in Growth |
|---|---|---|
| Manas Ranjan Hota | DrinkPrime | AI reduces customer acquisition costs through real-time analytics but works better for analysis than full automation; human sales interactions remain critical for understanding customer intent. |
| Mohammad Imran Shaikh | Trustsignal | AI is more effective in retention-led communication, but requires sustained behavioural data; current applications limited to automation, not deep prediction. |
| Vivek Mehta | Urban Ladder | AI has matured in acquisition via Google/Meta automated optimisation; retention requires human emotional connection and brand trust. AI cannot define brand positioning or category strategy. |
| Kiruba Devi | Zivame | (No specific quote in source, but part of panel.) |
| Aditya Anand | Yoga Bars | (No specific quote in source, but part of panel.) |
Implications for B2B and Cross-Border E-Commerce Operators
For cross-border e-commerce sellers, marketplace operators, and B2B platform managers, the panel's insights underscore that while AI can drive efficiency in performance marketing and content production, human judgment is irreplaceable for brand trust, positioning, and complex customer interactions. Vivek Mehta's warning that AI may over-optimise for existing customers rather than new segments is particularly relevant for sellers expanding into new geographies. Manas Ranjan Hota's emphasis on maintaining human fallback in customer service aligns with compliance requirements in many cross-border markets where personalised support is expected. The reliance on AI for acquisition via automated platforms (Google, Meta) means sellers must still invest in human oversight to ensure brand positioning aligns with local market nuances.
What sellers need to do: According to the panel, sellers should leverage AI for performance marketing analytics and content testing at scale, but maintain human-led sales and customer service teams to handle complex queries and trust-building. They should also monitor AI-driven metrics to avoid over-indexing on retention at the expense of new customer acquisition. As Mohammad Imran Shaikh noted, AI requires sustained behavioural data to be effective in retention—meaning sellers must invest in data collection infrastructure while ensuring human judgment guides strategic brand decisions.
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