This article was originally published in 2024 and was last updated June 12, 2025.
- Tension: We treat AI personalization as a performance upgrade, not a relationship-builder.
- Noise: Industry hype and one-size-fits-all algorithms mask how AI reshapes shopper trust and identity.
- Direct Message: Lasting personalization isn’t about precision—it’s about contextual empathy—AI must first learn people, not just patterns.
Read more about our approach → The Direct Message Methodology
In November 2024, Lazada unveiled a suite of GenAI-powered features—personal assistants, smart catalogs, AI-written descriptions—promising shoppers a hyper-personalized experience.
Fast forward to June 2025, and the platform continues to expand its AI footprint across Southeast Asia.
From smarter translation engines to predictive user experiences, Lazada now integrates over a dozen AI “work streams” that impact discovery, content, logistics, seller automation, and targeted marketing.
But beyond speed and scale, what truly matters is how AI helps shoppers—and sellers—feel recognized.
What It Is: GenAI, the Tailored Concierge
GenAI refers to AI tools that generate custom content—from images to personalized chat assistance—using large language models and multimodal systems.
Lazada’s in-app assistant, “Lazzie,” offers product suggestions, answers queries, and even formats listings for sellers.
Powered by Alibaba’s Marco MT, it provides seamless multi‑language support across SEA markets.
These tools aim to improve efficiency: auto-tagging product attributes saves sellers thousands of hours, while predictive models drive double-digit increases in traffic and conversions.
The Deeper Tension: Connection vs. Convenience
At its core, this isn’t really about algorithmic wizardry—it’s about human connection.
Shoppers today crave experiences that signal someone understands them, not just what their clickstream suggests.
Sellers yearn to reach audiences in an authentic voice, not as faceless sellers in a sea of commodities.
The tension? We’re caught in a cycle of performance metrics—clicks, CTR, add-to-cart—without asking if AI is fostering loyalty or identity.
If Lazzie only targets transactions, it risks amplifying the transactional gap between consumer and brand, making personalization feel hollow.
What Gets in the Way: Hype, Noise, and Illusion
AI press releases tout “nine-in-10 trust rates” for recommended content , but such metrics often gloss over the real risk: AI defaulting to safe sameness.
Generic recommendations inflate engagement while deepening filter bubbles.
When trusted voices in the marketing world speak of “hyper-targeting” as the ultimate goal, they reinforce a reductive view—that data equals relationship.
Noise also includes the narrative of “AI as an instant boost,” which hides how these systems require care, curation, and empathy.
The real asset is not the model, but its alignment with user context—culture, mood, stage of life.
The Direct Message
True personalization isn’t a function of data—it’s a function of empathy; AI should reveal the person, not just predict them.
Integrating This Insight
First, reframe AI projects not as feature rollouts, but empathy experiments.
Before adding any GenAI tool, ask: “What does this help a real person feel, think, or do?”
Lazada could tailor Lazzie’s responses based on cultural moments—celebrations, pain points, aspirations—instead of triggering generic promotions.
Second, build feedback loops that center on qualitative sentiment, not just KPIs. Beyond click engagement, measure trust, clarity, satisfaction.
A seller survey could ask: “Did AI help you express your brand’s narrative?” A shopper test could assess: “Did this feel like it was tailored to me specifically?”
Third, adopt “context frames” in AI output. For example, when translating listings, use localized idioms, climate relevance, even customary merger of language and visuals.
As Lazzie translates “holiday dress,” it might suggest festive-themed stylings in the Philippines or Ramadan-inspired modest wear in Malaysia.
With Marco MT in the loop, this kind of nuanced translation isn’t pipe-dream—it’s technically viable.
Finally, invest in narrative AI—not just targeting AI. That means scaffolding the AI flow with storytelling arcs.
Lazzie’s product suggestion could start with a question (“Looking for something comfortable for rainy-season commutes?”), then build to a recommendation.
This narrative pulley builds identity, not just conversion.
Why This Matters Now
As Lazada and other platforms double-down on GenAI, the real walled garden will be psychological, not technical.
Platforms that enable human-scale personalization will command trust and loyalty. Those that chase metrics alone risk training audiences not to feel understood—and thus to disengage.
By orienting GenAI tools around empathy, storytelling, and cultural coherence, platforms can evolve beyond personalized dashboards into personalized relationships—where each recommendation says: we see you.
And in a crowded e‑commerce market, that depth may be the ultimate competitive moat.
