IDC中国副总裁韩国华：出海AI营销要从单点提效走向全链路增长闭环

This article is a transcription of a speech by Han Guohua, Vice President of IDC China, delivered at the 2026 Global New Brands AI Competitiveness Conference. It shares the current development status and practical implementation insights of AI marketing for Chinese cross-border enterprises. Key takeaways are as follows:

1. Industry status quo: A survey of 200 cross-border Chinese enterprises conducted by IDC found that nearly 80% of respondents already widely use AI in marketing scenarios, but the overall maturity remains at an early stage. Most companies are at Level 1 (AI-assisted human decision-making) and Level 2 (basic automation), with only a small number of scenarios approaching Level 3, and Level 5 remains a long-term vision. Localized content creation and media placement optimization are currently the two most widely adopted and most mature AI application scenarios.

2. Practical implementation guidance: Enterprises should not blindly pursue cutting-edge high-level AI technologies, and should start with mature scenarios that fit their own business. They should conduct risk classification in advance, retain manual review for sensitive information, and keep full process records. Companies are advised to roll out AI marketing incrementally starting from mature scenarios, while establishing supporting organizational mechanisms, assigning clear ownership, and coordinating internal and external resources to drive implementation.

This article provides industry survey data and practical guidance for cross-border brands looking to adopt AI marketing and drive global growth. Key insights are as follows:

1. Industry status and changing consumer markets: Chinese cross-border brands are currently growing strongly, with some leading players holding over 30% global market share, but most regional markets are still at an early stage of development. The industry broadly faces headwinds of stricter regulation and persistently high customer acquisition and localization costs. AI has become a core tool for brands to cut costs and improve efficiency, with nearly 80% of cross-border brands already adopting AI in marketing scenarios.

2. Future direction of brand marketing: AI marketing needs to evolve from isolated efficiency improvements to a full-funnel growth closed loop. By connecting creative development, placement, risk control, and user operations across the entire user journey of reach, retention, and repurchase, brands can achieve measurable improvements in ROI.

3. Implementation guidance: Do not blindly pursue high-level automation; choose solutions that match your current development stage. Conduct compliance risk classification in advance for different overseas markets. When selecting service providers, prioritize end-to-end service capabilities over single-tool functionality, and establish internal organizational mechanisms to support implementation.

This article clarifies growth opportunities, implementation paths, and risk warnings for cross-border sellers in AI marketing. Key insights are as follows:

1. Market opportunities: AI has already become a core solution for cutting costs and improving efficiency in cross-border marketing, with nearly 80% of cross-border sellers already adopting AI. More than 80% of marketing decision-makers believe that effective AI adoption can drive 10-30% revenue growth, helping address the widespread pain points of high customer acquisition costs, high localization costs, and low placement efficiency faced by sellers.

2. Development direction: Sellers should not stop at isolated AI-powered cost reduction and efficiency improvement. The next step is to build a full-funnel growth closed loop that connects creative development, placement, risk control, and user operations to achieve integrated growth.

3. Risks and implementation guidance: Do not blindly pursue high-level automation; start with mature scenarios such as localized content creation and media placement optimization. Conduct compliance risk classification in advance for different overseas markets, and retain manual review for sensitive content to avoid regulatory risks. Do not invest heavily in building standalone AI systems in-house; partner with professional service providers to control costs.

This article provides insights for export-oriented factories to capture industry opportunities and advance digital transformation. Key takeaways are as follows:

1. Overall cross-border industry opportunities: China's cross-border industry is currently growing strongly, with operations spanning the globe. Some leading players already hold over 30% global market share, but most regional markets (outside parts of Southeast Asia and Western Europe) remain at an early development stage, leaving substantial room for overall growth.

2. New opportunities from industrial upgrading: Cross-border enterprises broadly face the pain point of persistently high customer acquisition and localization costs, and are accelerating AI marketing upgrades, creating strong demand for supporting AI marketing-related products and services. Factories active in related fields can capture this business opportunity brought by industrial upgrading.

3. Insights for factories' digital transformation: When advancing digital and e-commerce transformation, factories should not blindly pursue cutting-edge technology, but start with mature scenarios that fit their business to address core pain points first. They should implement risk control alongside rollout, establish supporting organizational mechanisms, and advance incrementally to eventually achieve full-funnel digital growth and upgrading.

Based on industry survey data, this article clarifies customer pain points and industry trends in the cross-border AI marketing sector, and outlines a clear development direction for service providers. Key insights are as follows:

1. Core current customer pain points: Nearly 80% of cross-border enterprises already use AI in marketing scenarios, but overall adoption remains at an early stage. Enterprises are dissatisfied with currently fragmented, single-point AI tools, and are unwilling to invest significant in-house resources to build and manage multiple independent AI agents. They urgently need service providers that understand the full brand marketing funnel to help connect fragmented AI applications and drive tangible business growth.

2. Industry development trend: The core future direction of AI marketing is shifting from isolated efficiency improvements to an integrated full-funnel growth closed loop. Enterprises no longer need single-function tools, but integrated services that help improve full-funnel ROI.

3. Development guidance for service providers: Different types of current service providers each have their own strengths. Execution-focused, media agency, and MarTech tool providers should leverage their respective advantages, deepen collaboration, and jointly deliver full-funnel AI marketing services to brand enterprises to meet their demand for an integrated growth closed loop.

This article surveys cross-border enterprises' demand for AI marketing, and outlines optimization directions for platform operators offering cross-border marketing services. Key insights are as follows:

1. Core current customer demand for platforms: Cross-border enterprises now widely use AI marketing tools, and many platforms already have built-in AI tools, but customers are not satisfied with fragmented single-point AI applications. They urgently need platforms to provide integrated AI services that support the entire marketing funnel, helping connect all stages from creative development and placement to user operations, and build a full-funnel growth closed loop covering reach, retention, and repurchase.

2. Optimization direction for platform ecosystem operations: Platforms can align with customers' full-funnel growth demand, integrate capabilities of different types of service providers in their ecosystem, help customers connect fragmented AI applications, and address the pain points of high cost and poor performance associated with building in-house systems. This will also help attract more merchants to join the platform.

3. Risk mitigation guidance: Platforms should guide customers to establish a compliance risk classification framework, put in place supporting rules such as manual review and process audit trails aligned with regulatory requirements of different overseas markets to help customers avoid compliance risks. They should also improve collaboration mechanisms within the ecosystem, clarify responsibilities of all parties, and drive the healthy implementation of AI marketing.

This article shares IDC's latest research findings on AI marketing for cross-border enterprises, proposes new industry trends and an analytical framework, and provides first-hand research materials for industry researchers. Key content is as follows:

1. New industry trends: AI has already achieved first-mover adoption in cross-border marketing scenarios, with nearly 80% of cross-border enterprises already widely applying AI. Overall maturity remains at an early stage: most companies are at L1 (AI-assisted decision-making) and L2 (basic automation), with only a small number of scenarios approaching L3. The most widely adopted and most mature AI scenarios are localized content creation and media placement optimization. Maturity varies across sectors, with cross-border e-commerce placement and app user operation showing relatively higher maturity.

2. New industry challenges: Enterprises currently broadly face the problem that isolated AI applications cannot drive overall growth, most lack the capability to build a full-funnel AI system in-house, and cross-border enterprises also need to address compliance risks in different markets. These are new challenges the industry needs to resolve.

3. New analytical framework: IDC proposes an AI marketing maturity assessment model ranging from L0 to L5, and puts forward that AI marketing is a systems engineering project that requires alignment with business scenarios and parallel development of risk management and organizational mechanisms, providing a new analytical framework for future industry research.