Morgan Stanley analyzes "The Advertising Industry in the AI Era": From the Battle for Attention to the Closed Loop of Transactions

AI is reshaping the flow of budgets for internet advertising in China, but at least until 2030, it is more like a redistribution of the existing market than a new cycle of advertising growth.

A September in-depth study of China's internet industry released by Morgan Stanley's Asia team revealed that among advertisers who have already used or plan to adopt AI, 72% reported no change in their total advertising budget, while 74% believed that cross-platform advertising spending was becoming increasingly concentrated. With limited growth in total budgets, AI is primarily changing how advertising budgets are allocated.

This trend is already reflected in advertisers' actual applications. In 2025, 74% of surveyed advertisers used AI for content generation, and 62% used it for advertising campaign management, while the penetration rates for product feed/catalog optimization and generative engine optimization were only 9% and 5%, respectively. Currently, the main role of AI in the advertising industry is still to improve efficiency, rather than to create new advertising entry points.

As AI evolves from content generation and ad placement optimization to becoming an agent, competition among advertising platforms will gradually extend to user decision-making and transaction stages. For internet platforms, the real focus should not be on how much new budget AI brings, but rather on who can leverage AI to acquire more existing budget and further unlock commercial opportunities beyond advertising.

AI has already shifted budget allocations, but the growth potential for advertising has yet to be unlocked.

Morgan Stanley's conclusion, based on the sixth AlphaWise China advertiser survey, is quite clear: AI is changing the allocation of advertising budgets, but has not yet significantly expanded the overall advertising market.

Research shows that 50% of advertisers believe AI has improved ROI, and 46% believe customer inquiry handling and pre-sales and after-sales service have improved. However, in terms of budget, 72% of advertisers said their total advertising expenditure remained unchanged, with adjustments made primarily to their ad placement structure within their existing budgets.

Meanwhile, 74% of advertisers believe that cross-platform advertising spending is becoming more concentrated. As advertisers increasingly value campaign efficiency and measurable results, budgets are concentrating on platforms that offer higher conversion rates and more complete data feedback. Therefore, AI is currently primarily bringing about changes in market share, rather than overall market expansion.

Another characteristic of this stage is that AI applications are still mainly limited to advertising production and management. Content generation and advertising campaign management have become relatively mature use cases, while product feed optimization and generative engine optimization, which are closer to AI-native advertising models, still have low penetration rates. Only when AI further participates in user discovery, product decision-making, and transaction execution can new commercial revenue potential truly be unlocked.

Budgetary shifts will be observed in 2030, with incremental changes only becoming apparent in 2040.

Morgan Stanley predicts that by 2030, the total monetization of individually identifiable AI will be approximately RMB 291 billion, including approximately RMB 10 billion in candidate set advertising and approximately RMB 281 billion in AI attribution transaction commissions.

It's important to note that this forecast does not include revenue growth resulting from predictive AI improving the monetization efficiency of existing ad inventory. In other words, if AI improves ad click-through rates, conversion rates, or delivery efficiency, this incremental increase will still be reflected in traditional advertising revenue, rather than new, independent AI revenue.

The real growth potential comes from agents further integrating into the transaction chain. By 2040, with AI involved in discovery, decision-making, and transaction execution, AI-driven advertising revenue is projected to reach 319 billion yuan, while AI-attributed transaction commissions could reach 1.24 trillion yuan. However, after deducting the replacement of traditional businesses, incentive expenses, and partner revenue sharing, the final net market expansion will be lower than the aforementioned totals.

Therefore, the two phases correspond to different business logics: before 2030, the focus is mainly on budget migration, while around 2040, AI's restructuring of business models and market space will become more prominent. The 2040 prediction is more suitable as a long-term scenario anchor rather than a precise time point.

Beyond the model, the business closed loop determines value capture.

As AI evolves from an advertising delivery tool into an agent capable of understanding demand and executing tasks, the core of platform competition will shift to control over the business chain. Morgan Stanley summarizes this into four key nodes: who initiates the demand, who determines the candidate set, who completes the transaction, and who controls the outcome data and write-back permissions . From advertising and sponsorship ranking to transaction commissions, payments, and merchant services, different stages correspond to different value extraction methods.

This is also the main difference between standalone AI and embedded AI. Standalone AI can aggregate user intent across different domains, but AI embedded in a business system is closer to products, merchants, payments, and transactions, making it easier to transform user needs into quantifiable business results. Research shows that 47% of advertisers believe the value created by AI will be shared by all stakeholders, while 37% believe the platform will be the single biggest beneficiary.

Therefore, AI may not fundamentally change the competitive landscape of the internet; instead, it may amplify existing differences among platforms in user demand, supply, transactions, and data. For the advertising market, in the short term, budgets will concentrate on high-efficiency platforms, while in the medium to long term, it depends on whether platforms can integrate AI into the entire business chain. As agents move from assisting with ad placement to "reading demand—making decisions—executing—writing back," transaction commissions and merchant service revenue beyond advertising are expected to become more important sources of incremental growth in the next stage.

Risk warning and disclaimerInvesting involves risk; please exercise caution. This article does not constitute personal investment advice and does not take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article are suitable for their specific circumstances. Any investment decisions made based on this information are at your own risk.