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Alibaba shares fall after Jefferies cuts target on AI spending, non-core losses

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Alibaba shares fall after Jefferies cuts target on AI spending, non-core losses

Jefferies cut Alibaba's target price to $185 from $212 (retained Buy); shares fell 2.9% to HK$122.70 and the Hang Seng slipped 0.6%. The downgrade reflects higher AI-promotion spending (Alibaba earmarked 3 billion yuan for Lunar New Year promotions to push its Qwen AI app) and larger expected losses in the non-core 'All Others' segment; Jefferies expects quick-commerce losses to improve in the March quarter and fiscal 2027 losses to halve year-over-year.

Analysis

Alibaba’s pivot to aggressive AI customer acquisition is a classic short-term margin vs long-term share trade: heavy promotional spend will compress near-term EBITDA while increasing user funnels and data capture that are core to an AI monetization roadmap. Second-order beneficiaries include cloud/GPU infrastructure providers, AI model partners, and digital marketing platforms that will capture the incremental spend; logistics and quick-commerce partners shoulder asymmetric subsidy risk as unit economics are pressured. Competitive dynamics shift subtly: rivals that remain focused on low-cost commerce (JD, PDD) can exploit any execution slippage or weakened merchant economics, while pure-play AI/AI-search franchises (BIDU, certain cloud suppliers) can monetize model usage faster if they avoid burn. The durability of any user gains depends on CAC/LTV dynamics — if incremental users driven by promotions convert at materially lower ARPU, the headline “user growth” will be value-destructive. Catalysts to watch across time horizons are clear: near-term (days-weeks) — quarterly metrics and management commentary on non-core losses and promotional cadence; medium-term (3-12 months) — retention and paying-conversion of AI app users and quick-commerce unit economics; long-term (12-36 months) — gross margin trajectory of AI services and ability to cross-sell higher-margin cloud/ads offerings. Tail risks include regulatory tightening on platform monetization and a slower-than-expected ARPU uplift that forces persistent elevated subsidies. Contrarian case: the market may be over-discounting the company’s ability to reprice AI features once engagement is established — if conversion lifts or gross margins on AI services approach cloud norms within 12–24 months, current weakness could present a multi-bagger optionality play. Key inflection datapoints to prove the contrarian view are steady sequential uplift in paying users per cohort and a measurable decline in subsidy per order.