AI Media Buying Is Deepening The Super-App Advantage

Tencent reported on August 12 that second-quarter marketing-services revenue rose 22% year on year to RMB43.6 billion, supported by AI-driven ad recommendations, its automated AIM+ buying system and closed-loop marketing across Weixin. The result gives marketers fresh evidence that AI is improving platform advertising economics, but it also shows where more campaign control is moving.

Tencent's advantage is not only a better recommendation model. It can connect the ad impression, campaign automation, Mini Games, Mini Shops and other Weixin activity inside an ecosystem used by 1.44 billion monthly users. For CMOs, that makes the platform more effective and harder to audit from outside.

What Tencent Changed

Tencent said most major industry categories increased spending on its platforms during the quarter. Marketing-services revenue accelerated from 20% growth in the first quarter to 22% in the second, while total company revenue grew 11% to RMB204.8 billion.

The company linked the advertising performance to three changes: an upgraded AI model that chooses which ad appears for each impression, improvements to AIM+, and tighter links between advertising and transactions inside Weixin. AIM+ was also expanded with end-to-end execution for Mini Shop and mini-drama advertisers.

Chairman and CEO Ma Huateng said Tencent was seeing "sustained marketing services revenue growth" while building AI capabilities at the model, application and infrastructure levels. The advertising result matters because it is already helping fund that wider buildout. Tencent's capital expenditure rose 176% to RMB52.8 billion, and the company reported negative free cash flow of RMB13.8 billion after infrastructure spending and AI-related prepayments.

Why Closed-Loop Automation Matters

The common reading is that better ad ranking produces better returns. The more consequential change is that targeting, buying, conversion and measurement can now happen within the same platform. Each additional step gives Tencent more feedback for its models and gives advertisers fewer reasons to move activity elsewhere.

That can shorten campaign setup and improve relevance. It can also make platform-reported performance increasingly difficult to separate from the platform's own optimization choices. A model that selects audiences, manages bids and observes purchases is both operator and scorekeeper.

For regional marketing leaders, the issue is not whether to use the automation. It is which evidence should remain portable. Conversion definitions, incrementality tests and campaign-level data exports become more important as the platform absorbs more execution.

Competitors Are Automating The Same Work

Kuaishou reported in May that first-quarter online marketing revenue grew 9.3% to RMB19.6 billion, also crediting wider AI use. Its generative recommendation and intelligent-bidding models contributed an estimated three to four percentage points of domestic marketing-services growth, while its automated placement product handled creative generation, campaign setup and bid management.

Kuaishou CEO Cheng Yixiao said the company had expanded AI across "content creation, online marketing, e-commerce operations and organizational management." The company also said AI-generated short-video materials accounted for 10% of short-video ad spending on its platform in March.

The comparison suggests the competitive race is moving beyond who has the largest audience. Platforms are trying to prove that integrated AI can produce, place and optimize advertising against commerce outcomes with less manual work. Independent adtech and agencies may still offer broader cross-platform judgment, but they are competing with systems that own both the workflow and the transaction signal.

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What CMOs Should Decide

Tencent's quarter gives CMOs a practical governance test. Before expanding automated buying, leaders should specify which objectives the platform may optimize, which budget or creative changes require human approval, and which outcome data must be reconciled against an independent source.

Agency leaders also need to show where their value sits when campaign operation becomes automated. Cross-platform allocation, experimentation design, brand safeguards and independent measurement are more defensible than manual trafficking or routine bid changes.

The 22% revenue increase does not prove that every advertiser received a better business outcome. It does show that AI-led buying and closed-loop commerce are strengthening one another. For APAC marketing leaders, the next platform review should examine not only efficiency, but also how much decision authority and measurement independence the brand is prepared to give up.