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India’s Gen Z turns to AI for product research but prioritises quality, trust and price
Our read
In India, Gen Z will make AI the front door to retail discovery, but transparent product data and human-backed service—not AI novelty—will determine who converts the sale.
For operators
Make AI search and recommendation tools explainable and price-aware, while reinforcing quality proof, transparent policies and human support at checkout.
Watch
Growth in AI-referred traffic and conversion rates from search, chat assistants and in-app recommendation tools.
The report,
YouGov and Rukam Capital’s India Gen Z study finds quality, price, transparency and customer experience drive purchase decisions. Consumers increasingly use AI for research rather than autonomous buying, while quick commerce, festive spending and trusted established brands remain important retail signals.
- Expect brand honesty and transparency82%
- Say good customer experience builds trust74%
- Cite quality as top purchase driver51%
- Cite price as a top purchase driver49%
Channel facts
From the report. Source details below
- 82% expect brand honesty and transparency
- 51% cite quality as top purchase driver
- 49% cite price as a top purchase driver
- Nearly 60% use AI for product research
- 70% are comfortable with AI recommendations
- 49% would allow AI to decide without approval
- 60% spend more during festive season
- 74% say good customer experience builds trust
Other figures
- 4,002 Gen Z respondents
- 18 states in India
- 28% use quick commerce
What it means for online and offline
Prioritize partnerships or acquisitions in product-information management, AI shopping assistants and trust-building CX tools that improve conversion without reducing consumer control.
Signals to track
- Consumer complaints or regulatory action involving undisclosed sponsored AI results, hallucinated product claims or synthetic reviews.
- Widening performance gap between brands with rich, verified product data and brands with incomplete catalog information.
- Rising demand for live support, store pickup, video consultation or WhatsApp confirmation after AI-led product research.
- Increases in returns or customer-service contacts from AI-recommended purchases, indicating weak recommendation quality.
- Adoption of standardized product provenance, review verification and price-transparency signals by major Indian marketplaces.
Likely next moves
Our read of what comes next — analysis, not reported by the source.
- Make product feeds AI-readable: structured specifications, availability, price history, compatibility details, comparison tables and policy information.
- Treat transparency as conversion infrastructure: disclose sponsored placements, verify reviews, show total delivered price and make returns, warranties and seller identity prominent.
- Deploy AI assistants primarily for discovery, education and narrowing choices; preserve explicit consumer control and easy escalation to human support.
- Unify online, app, social, WhatsApp and store inventory and pricing to prevent trust-damaging channel inconsistencies.
- Measure AI-assisted commerce separately: AI-originated discovery, assisted conversion, return rate, service escalation, repeat purchase and trust/NPS outcomes.
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- Prioritise quality proof over promotional copy through demos, certifications, user-generated evidence, durability information and post-purchase support.
The counter-case
The case against this reading — not reported by the source.
Using AI for product research does not prove that AI changes purchase outcomes: Gen Z may use it for ideas, comparisons or summaries, then default to marketplaces, peers, search and established brands at checkout. Quality, price and trust are near-universal stated preferences, so the findings may be more attitudinally unsurprising than commercially actionable. Retailers could overinvest in AI discovery features without evidence of incremental conversion, basket size or loyalty.
The source
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