WAIC 2026: Tech Dividends Peak, Compliance Is the New Moat
Axel Björn Lundqvist
2026-07-19 16:00
The 2026 World Artificial Intelligence Conference and High-Level Meeting on Global Governance of Artificial Intelligence were held in Shanghai from July 17th to 20th. This year’s conference set new records in terms of scale and prestige, with an exhibition area exceeding 100,000 square meters, bringing together over 1,100 domestic and international companies and showcasing over 3,000 cutting-edge AI products, including over 300 global debuts. President Xi Jinping attended the opening ceremony and delivered a keynote speech. Representatives from over 100 countries and international organizations participated, and nine Turing Award and Nobel Prize laureates were present. The addition of the top-tier international AI academic conference WAICA further solidified its position as a leading industry exchange platform.
As a barometer for observing the development trends of the AI industry, the most significant milestone of this conference was not within the exhibition halls. On the eve of the conference’s opening, representatives from 29 countries signed an agreement in Shanghai to establish the world’s first intergovernmental international organization for artificial intelligence—the World Artificial Intelligence Cooperation Organization (WAIC), with its headquarters permanently located in Shanghai. In his keynote speech at the opening ceremony, President Xi Jinping stated that this is a significant milestone in the history of artificial intelligence development.
When 29 countries sat down together to establish unified rules for AI, the signal itself indicated that the technological dividend is reaching its peak, and the industry is no longer simply competing on models and computing power. Compliance, standards, and global governance rules are surpassing technical parameters to become new core barriers, directly changing the competitive logic of technology service providers and AI entrepreneurs.
For the past few years, the AI industry has been in a period of technological dividends. Whether it’s large model manufacturers or technology service providers, the core task is to refine technical capabilities, optimize model performance, and reduce computing costs. As long as the technology is strong enough, even if the processes are not standardized or the system is incomplete, the market will still buy it.
However, the 2026 World Artificial Intelligence Conference has set a new bottom line for development. The conference chairman’s statement emphasized the need to “pay attention to the security risks brought by artificial intelligence,” and to promote the construction of a “legal and regulatory, technology monitoring, risk warning, and emergency response system,” specifically mentioning “exploring classified and graded management, strengthening the security bottom line, and ensuring that artificial intelligence always remains under human control.” For leading AI companies, the statement requires them to “advance R&D with a cautious attitude and install necessary safeguards for large-scale AI models.”
Simply put: No matter how good an AI product’s performance is, if it’s non-compliant, uncontrollable, and cannot be audited throughout the entire process, it will be difficult to gain entry into government, enterprise, and multinational projects.
In the past, large enterprises focused on accuracy and speed when purchasing AI services, and pre-sales teams emphasized accuracy. Now, whether data is controllable, processes are traceable, risks are predictable, and applications meet tiered requirements have become the most important concerns for clients. Technological advantages have become a basic threshold; compliance and governance capabilities are the key to success.
“Categorized and tiered management” is particularly noteworthy. Compliance requirements differ for AI applications in different scenarios and with varying data sensitivities. Large companies may not have the resources to provide refined adaptations for every vertical industry, but service providers with deep expertise in specific fields can turn it into a high-barrier, customized business—whoever thoroughly understands the compliance standards of a particular industry first will have an extra layer of protection.
In his speech, President Xi Jinping also stated that we should “oppose the practice of generalizing the concept of national security in the field of artificial intelligence and placing national security above the security of other countries.” The industrial implications of this statement are direct: the competitive model relying on blockades and monopolies is outdated; future core competitiveness comes from building a compliance system and standardized governance.
In the AI industry system, data is a core production resource and a core scenario for implementing compliance governance. The rule changes at this conference have also led to a restructuring of the business models of data service providers.
In the past, most domestic data service providers competed on price and volume, focusing their business on simple processing steps such as data labeling and basic cleaning. With low entry barriers and severe homogenization, they could only maintain business through low-price competition, resulting in continuously shrinking overall profit margins and a very passive business model.
This conference has opened up new growth opportunities for the data industry. The conference chairman’s statement pointed out that “we should grasp the characteristics of high data mobility and high enabling power, deepen the development and utilization of data resources, effectively safeguard data security, jointly strengthen personal information protection, accelerate the construction of basic systems such as data property rights, ensure that data is manageable, controllable, and traceable, and promote the safe and orderly flow and efficient development and utilization of data.” The accompanying “Action Plan for Cooperation and Development in Artificial Intelligence” further establishes a complete data compliance governance framework from multiple dimensions, including high-quality data supply, cross-border data governance, and secure collaboration.
The implementation of these rules has driven the industry away from extensive development. Low-end processing businesses are gradually becoming saturated, while data compliance governance services adapted to AI model training and government and enterprise project implementation have become a market necessity. High-value services such as data anonymization, training data traceability, data flow auditing, and AI data risk management are replacing traditional low-end processing services and becoming the core profit growth points for data service providers.
Compliance governance determines market access qualifications. The official establishment of the World Artificial Intelligence Cooperation Organization marks a complete departure from the fragmented and independently managed development pattern of the global AI industry, and a unified governance standard and collaboration system is rapidly taking shape.
This has transformed the internationalization strategy of domestic technology service providers from a “bonus” to a “must-have.” Previously, Chinese companies could seize market share overseas by leveraging cost-effectiveness and flexible adaptability. However, under the new global governance system, all multinational AI projects must adapt to unified international rules, making compliance and governance capabilities a mandatory qualification for successful overseas deployment.
This conference also announced several specific measures for international AI development: providing 5,000 AI-focused training opportunities for developing countries over the next five years; establishing international AI application cooperation centers in multiple regions, including ASEAN, the Arab League, and the African Union; and promoting the application of the “Mazu” intelligent weather early warning solution in 30 countries. These actions signify a shift in AI internationalization from sporadic, single-point deployments to systematic, standardized, and routine global collaborative cooperation.
In the future, the threshold for undertaking AI projects will not only include technical capabilities but also standards adaptation capabilities, international collaboration qualifications, and compliant delivery capabilities. Service providers that proactively establish compliant governance systems will gain priority access to government and enterprise projects and international collaborations.
The 2026 World Artificial Intelligence Conference is a watershed moment: on one hand, the focus has shifted from past competition on parameters and computing power to future competition on compliance and standards. AI entrepreneurs and technology service providers can proactively plan in several areas.
First, make compliance capabilities a core weapon in pre-sales. Stop focusing solely on model benchmarks; highlight end-to-end compliance governance, tiered adaptation, risk warning, and full traceability capabilities to precisely match clients’ core needs.
In the practical implementation of compliance governance, a stable network environment is crucial. 1024proxy provides clean residential IP resources, supporting compliant network access for data collection and model training scenarios, helping technology service providers achieve stable business development.
Second, upgrade data business structure, moving beyond simply selling “volume.” Package data governance, anonymization compliance, and model adaptation into a one-stop service, moving beyond low-end homogenized processing, focusing on high-value sectors, and increasing average order value and profit margins.
Simultaneously, proactively plan for international cooperation. Pay attention to the progress of several internationalization initiatives mentioned at the conference and proactively connect with regional AI application standards and governance norms. Thorough preliminary work is essential to securing a competitive position when projects scale up.
Finally, the application of open-source technologies must be standardized. The conference emphasized “encouraging the responsible co-construction of the open-source ecosystem”—code tracing, intellectual property management, and risk auditing are all indispensable. Small and medium-sized teams can leverage the open-source ecosystem to operate with a lighter burden, but they must adhere to ethical standards.
The 2026 World Artificial Intelligence Conference has drawn a new starting line for the AI industry.
In the past, the competition was about who could run the fastest. From now on, the competition is not only about speed, but also about who understands the rules better, who is more compliant, and who can complete standardized delivery within multilateral frameworks. For technology service providers, adapting to governance trends and deepening compliance capabilities is a more worthwhile investment than continuing to pile on computing power.
Running fast is just the foundation. Running steadily and sustainably is the key.
