SHANGHAI, July 17 — As the 2026 World Artificial Intelligence Conference (WAIC) opened in Shanghai on Thursday under the theme “Intelligent Partners, Co-create the Future,” attention has increasingly shifted from breakthroughs in foundation models to a more practical question facing the artificial intelligence industry: how AI generates sustainable corporate earnings. The conference brings together more than 1,100 companies, over 3,000 AI exhibits and more than 140 forums, reflecting growing emphasis on industrial adoption, ecosystem collaboration and enterprise deployment.
That transition is becoming increasingly visible in corporate earnings.
Just days before WAIC opened, Hong Kong-listed Marketingforce Management Ltd. (HKEX: 2556) issued a positive profit alert, forecasting a substantial increase in first-half net profit compared with a year earlier, supported by growth in its AI application business and continued improvements in operating efficiency.
While individual earnings announcements rarely define an industry trend, Marketingforce’s results provide an early example of how enterprise AI companies are beginning to translate application adoption into profitability.
From AI Infrastructure to Enterprise Execution
Over the past two years, investor attention has largely focused on semiconductor suppliers, cloud infrastructure providers and developers of large language models.
However, as model capabilities converge and inference costs continue to decline, industry participants increasingly expect competitive differentiation to shift toward enterprise implementation rather than model performance alone.
This year’s WAIC reflects that evolution.
Conference sessions have expanded beyond foundation models to include AI agents, enterprise applications, intelligent manufacturing, open platforms and industrial collaboration, signalling that commercialization has become a central theme of China’s AI ecosystem.
For enterprise software companies, the challenge is no longer demonstrating that AI works, but proving that AI can improve productivity, reduce operating costs and generate measurable returns for customers.
Commercial Value Becomes the New Benchmark
Marketingforce has positioned its strategy around what it describes as “Scenario Tokens,” integrating AI into customer acquisition, marketing automation, customer service and business analytics.
Rather than charging primarily for software licences or API consumption, the company increasingly links AI deployment to enterprise workflows and business outcomes.
That reflects a broader trend emerging across global enterprise software.
Companies are increasingly evaluating AI investments based on operational impact—including customer conversion, employee productivity and decision-making efficiency—rather than on model sophistication alone.
For investors, such models potentially offer greater pricing flexibility and stronger recurring revenue characteristics than traditional project-based software implementation.
Internal AI Adoption Supports Margins
Another feature of Marketingforce’s earnings outlook is the role of internal AI deployment.
The company said it has expanded internally developed AI employees across sales, marketing, customer service and employee training, contributing to improvements in operating efficiency while maintaining relatively stable headcount.
Software companies globally have increasingly adopted their own AI technologies internally before expanding commercial deployment, viewing internal adoption both as product validation and as a way to improve operating leverage.
Should this pattern continue, profitability within enterprise AI may become increasingly dependent not only on revenue growth but also on how effectively companies deploy AI inside their own organisations.
The Next Phase of China’s AI Industry
WAIC has historically served as a showcase for advances in China’s AI capabilities.
This year’s event suggests that the industry’s priorities are evolving.
As AI moves deeper into enterprise operations, questions surrounding workflow integration, proprietary enterprise knowledge, platform scalability and sustainable monetisation are expected to become increasingly important.
Against that backdrop, companies capable of combining AI infrastructure, enterprise software and industry-specific applications may attract greater attention from investors seeking evidence that artificial intelligence can generate durable earnings rather than simply technological progress.
Marketingforce’s earnings forecast does not, by itself, establish a broader industry trend.
But together with the themes emerging at WAIC 2026, it illustrates how China’s AI sector is gradually entering a new phase—one in which commercial execution may matter as much as technological innovation.