AI user acquisition: adoption is now the competitive bottleneck

China’s $431M AI play: turning chatbot access into habit

Alibaba just committed $431 million roughly twice what Tencent and Baidu are spending combined to flood its Qwen AI chatbot with users this Lunar New Year. 

While much of the global AI conversation remains fixated on model capability, China’s largest platforms are focusing on something more difficult to scale: habit formation. By early 2026, the hard problem is no longer building capable AI. It’s getting people to use it, repeatedly, in daily life.

Between February 15 and 23, Alibaba, Tencent, and Baidu will deploy over $640 million in incentives tied directly to AI chatbot usage(Reuters, 2026). Cash rewards, digital red envelopes, and discounts are offered only after users download, upgrade, and interact with AI features.

The focus of the competition has changed from building the most advanced model to influencing how and when users engage with AI.

Why Lunar New Year matters more than the models

Alibaba could have run this campaign at any time. It chose Lunar New Year deliberately.

The holiday disrupts routine. People travel, spend time with family, and step away from work habits. In that break from normal patterns, trying something new feels easier. The psychological cost of experimentation drops.

This is when adoption accelerates.

Teams that treat AI rollout like a standard product launch often miss this dynamic. People don’t avoid new tools because they lack access. They avoid them because change feels costly. Adoption happens when users are already adjusting their routines and trying something new feels safe, not disruptive.

Why first use is being engineered, not encouraged

These campaigns are built around action, not awareness. Simply knowing the AI exists isn’t enough. Users are required to upgrade their apps and actively engage with AI features before they receive any rewards.

That requirement turns incentives into a guided first experience. Instead of leaving adoption to chance, it pushes users into trying the product. The decision disappears, and movement takes its place.

Once people interact with the tool, familiarity builds quickly. Familiarity reduces uncertainty. With repeated use, the AI starts to feel normal rather than new.

Organizations that depend on announcements, training sessions, or optional access often find that AI stays at the edges of work. In contrast, teams that intentionally design the first interaction and make it happen early are far more likely to see lasting behavior change.

What the spending really tells us

The scale of Alibaba’s spending says less about belief in Qwen’s technical strength and more about belief in how people behave. Once habits form, they tend to stick.

By early 2026, access to capable AI is no longer rare. What’s hard to secure is regular, repeated use. In markets where models can be copied and improved quickly, familiarity and routine become the real sources of advantage.

This reflects a subtle change in how AI competition is decided. Strong technology still matters, but leadership increasingly belongs to the companies that succeed in shaping everyday behavior, not just building impressive systems..

What this means for teams deploying AI

For organizations introducing AI into products or workflows, matching China’s level of spending is unrealistic for most. What matters more is that simply providing access does not guarantee that people will start using the technology.

True usage depends on timing, incentives, and guided early interaction. It requires understanding when people are ready to change and designing systems that lead them to use the AI effectively.

Teams that treat adoption as secondary often struggle to show real value from AI. Teams that make behavior a central focus are more likely to see AI move from experiments into everyday work.

Alibaba’s $431 million investment highlights a key reality: in AI markets, technology can be duplicated, but user habits are far more durable and difficult to replicate.

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