Artificial intelligence is reshaping how advertising budgets flow across China's internet sector, yet until at least 2030, its impact more closely resembles a redistribution of existing market share rather than igniting a fresh cycle of ad spending growth.
According to a September deep-dive report on China's internet industry from Morgan Stanley's Asia team, among advertisers who have already adopted or plan to adopt AI, 72% report no change to their overall ad budgets, while 74% note that cross-platform ad spending is becoming increasingly consolidated. With limited growth in total budgets, AI's primary effect right now is altering how those budgets are allocated.
This trend is already visible in real-world advertiser behavior. In 2025, 74% of surveyed advertisers use AI for content generation and 62% for campaign management, whereas adoption of product feed and catalog optimization and generative engine optimization stands at just 9% and 5%, respectively. At present, AI's main contribution to the advertising industry is boosting efficiency rather than creating new advertising entry points.
As AI evolves from content creation and bid optimization toward autonomous agents, competition among ad platforms will gradually extend into user decision-making and transaction stages. For internet platforms, the key question is not how much new budget AI generates on its own, but who can leverage AI to capture a larger share of existing budgets and unlock monetization opportunities beyond advertising.
AI Reshapes Budget Flows First, While Ad Increment Remains Elusive
Morgan Stanley's conclusions, drawn from the sixth edition of its AlphaWise China Advertiser Survey, are quite definitive: AI is transforming ad budget distribution without yet significantly expanding the overall ad market size.
The survey shows that 50% of advertisers believe AI has already delivered ROI improvements, and 46% report better handling of customer inquiries along with pre-sales and after-sales support. However, on the budget front, 72% of advertisers say total ad spending has not changed, with most adjustments occurring within existing budget allocations.
Meanwhile, 74% of advertisers perceive that cross-platform ad spending is becoming more concentrated. As advertisers place greater emphasis on efficiency and measurable outcomes, budgets are shifting toward platforms that offer higher conversion performance and more complete data feedback loops. Therefore, what AI delivers initially is a shift in market share, not an expansion of the overall market.
Another hallmark of this phase is that AI applications remain largely confined to ad production and management. Content generation and campaign management have emerged as mature use cases, while product feed optimization and generative engine optimization, which are closer to AI-native advertising models, still show low penetration rates. Only when AI becomes further involved in user discovery, product decisions, and transaction execution can genuinely new commercial revenue streams begin to materialize.
Budget Migration by 2030, Incremental Growth Only by 2040
Morgan Stanley projects that by 2030, the total identifiable AI monetization scale will reach approximately RMB 291 billion, with candidate-set advertising contributing about RMB 10 billion and AI-attributed transaction commissions around RMB 281 billion.
Importantly, this forecast does not include revenue growth derived from predictive AI enhancing the monetization efficiency of existing ad inventory. In other words, if AI improves click-through rates, conversion rates, or delivery efficiency, that upside will still be recorded as traditional advertising revenue rather than as new, standalone AI revenue.
The real incremental opportunity comes from agents penetrating deeper into the transaction chain. By 2040, as AI participates in discovery, decision-making, and transaction execution, AI-facilitated advertising revenue is expected to hit RMB 319 billion, while AI-attributed transaction commissions could reach RMB 1.24 trillion. However, after accounting for the displacement of traditional business, incentive expenditures, and partner revenue sharing, the final net market expansion will be smaller than these headline figures.
These two phases thus correspond to different business logics: before 2030, the story is primarily budget migration; only around 2040 does AI more fully reflect its restructuring of business models and market space. The 2040 projections are better treated as long-term scenario anchors rather than precise timelines.
Beyond Models, Commercial Closed Loops Determine Value Capture
When AI evolves from an ad delivery tool into an agent capable of understanding needs and executing tasks, the core of platform competition shifts toward controlling the commercial chain. Morgan Stanley distills this into four critical nodes: who initiates the demand, who defines the candidate set, who completes the transaction, and who holds the resulting data and write-back rights. From advertising and sponsored rankings to transaction commissions, payments, and merchant services, each segment corresponds to distinct value-capture mechanisms.
This also highlights the key difference between standalone AI and embedded AI. Standalone AI can aggregate user intent across domains, but AI embedded within business ecosystems sits closer to products, merchants, payments, and transactions, making it easier to convert user needs into measurable commercial outcomes. The survey reveals that 47% of advertisers believe AI-created value will be shared among all participants, while 37% think platforms will emerge as the largest single beneficiary.
From this perspective, AI may not fundamentally overturn the competitive landscape of the internet industry; instead, it is likely to amplify existing differences among platforms in user demand, supply, transactions, and data. For the advertising market, the near-term focus is on budgets consolidating toward high-efficiency platforms, while the medium-to-long-term outcome depends on whether platforms can integrate AI into a complete commercial chain. As agents move from auxiliary delivery to a full loop of reading demand, making decisions, executing, and writing back data, transaction commissions and merchant service revenue beyond advertising are poised to become the next phase's more significant growth drivers.
Comments