HONG KONG, June 26, 2026 — CIC extends our warmest congratulations to Beijing Zhongke WengeAI Science and Technology Co., Ltd. (01956. HK) on its successful listing on the Main Board of the Hong Kong Stock Exchange today.
CIC's Collaborative Journey to the Listing
Throughout the listing process, CIC provided end-to-end support to the company and its sponsors:
Drafted and compiled the industry overview chapter of the prospectus, laying a solid research foundation for the formal listing application.
Assisted in responding to inquiries from regulatory authorities, ensuring comprehensive and accurate disclosure.
Refined listing application materials continuously to meet stringent market and regulatory requirements.
Zhongke WengeAI: A Leading Player in Enterprise-Grade AI-Powered Decision Intelligence
Zhongke WengeAI is an emerging enterprise AI technology and services vendor in China, specialized in complex technical analytics and AI-augmented decision-making. The company builds its core AI capabilities in-house and delivers a full-stack AI service portfolio spanning data governance, domain knowledge management, large language and multimodal model training, decision automation & evaluation, and low-code AI application development.
Its deeply integrated software architecture boosts the performance, reliability and security of enterprise-grade AI products. By unifying underlying infrastructure, resolving cross-system compatibility frictions and eliminating redundant work from stitching together fragmented systems, the platform reduces development costs and deployment cycles for enterprise AI solutions, and accelerates time-to-market for custom deployments.
As of 2025, Zhongke WengeAI has served more than 650 enterprise and government clients cumulatively. Ranked by 2025 revenue, it holds the number one position in China’s enterprise large model-driven decision intelligence market, with a 10.2% market share, according to CIC research.
China’s Enterprise AI Market: Robust Growth Ahead
China remains at the global frontier of AI innovation, home to a cohort of technology leaders with world-class large model capabilities. Strong corporate appetite for AI adoption and investment has also made China one of the world’s largest enterprise AI markets. According to CIC reports, China’s enterprise AI market reached RMB 391.8 billion in 2025, and is on track to hit RMB 950 billion by 2030, representing a compound annual growth rate (CAGR) of 19.5%.
The market is split into two segments: traditional enterprise AI, built for targeted use cases, and enterprise-grade large models, which mark a generational paradigm shift with broad generalization and cross-task capabilities. While large models still account for a small share of total enterprise AI deployments today, they are widely viewed as the definitive technology roadmap for the industry.
Revenue from enterprise large model solutions surged from RMB 3.6 billion in 2023 to RMB 18.1 billion in 2025. The segment is forecast to reach RMB 138.2 billion by 2030, posting a 50.2% CAGR between 2025 and 2030. Its share of the overall enterprise AI market is expected to rise from roughly 4.6% in 2025 to around 14.5% by 2030, as AI capabilities mature and enterprise adoption accelerates.
Notably, the large model-powered decision intelligence segment is growing faster than the broader market. It totalled RMB 3.9 billion in 2025, or 21.6% of China’s entire enterprise large model market. It is projected to grow to RMB 37.5 billion by 2030 — accounting for 27.1% of the total market — with a 57.2% CAGR from 2025 to 2030.
CIC identifies four key growth drivers underpinning the sector:
01 Continuous Accumulation of High-Quality Data
Advancements in large model-driven decision-making capabilities are fundamentally underpinned by the quality of training data. As data collection networks improve, data cleansing technologies advance, and open-source communities and public datasets expand, access to high-quality data has become increasingly accessible.
Comprehensive cross-domain data spanning diverse sectors, industries and departments can be integrated and analyzed to generate complementary insights. This enables large models to build holistic knowledge networks, delivering broader perspectives and richer knowledge reserves to address increasingly complex and dynamic decision-making scenarios.
The integration of multimodal data — encompassing text, images, audio, video and other data formats — allows large models to perceive information more comprehensively, enabling them to better identify core issues and underlying patterns during decision-making processes.
Highly accurate, consistently annotated data not only helps large models interpret data semantics more effectively, but also sharpens their ability to discern nuanced differences, leading to more precise identification of critical information and more reliable decision outputs. Meanwhile, low-noise data, which contains minimal irrelevant information, errors or random fluctuations, reduces interference, improves the extraction and utilization of valid information, and minimizes the risk of hallucinations and factual errors.
02 Technological Advancements
Continuous innovation is driving the evolution of large model technology. The "pre-training + post-training processing + fine-tuning" paradigm — in which models first learn general knowledge, are then optimized with domain-specific data, and finally fine-tuned on labeled task datasets — has emerged as the new standard for large model development.
When combined with technologies such as mixed-precision training, reinforcement learning, optimized attention mechanisms and mixture-of-experts (MoE) architectures, this paradigm strikes a balanced trade-off between training efficiency, accuracy, inference performance and cost.
Specifically, mixed-precision training accelerates training cycles and reduces costs by utilizing lower-precision data for non-critical steps. Reinforcement learning-based large models achieve real-time performance optimization by receiving feedback after each decision. Optimized attention mechanisms lower computational costs by enabling models to focus on relevant input data. MoE architectures boost inference efficiency by activating only a subset of sub-models during task execution.
These ongoing technological advances not only drive step-function improvements in the decision-making capabilities of large models, but also reshape the cost structure and application paradigm of the enterprise-grade AI industry, underpinning sustained growth in the enterprise large model sector.
03 Rising Customer Recognition of Decision Intelligence Value Across Industries
Enterprise-grade large model-driven decision intelligence has demonstrated proven commercial value across multiple sectors. As customer understanding deepens, their willingness to pay for such solutions has grown accordingly.
In the media sector, for example, large models empower the entire value chain — from content planning, editorial production and distribution to content management and communication performance evaluation — elevating overall communication effectiveness and operational efficiency for media organizations.
In the financial sector, large models strengthen risk management by enabling multi-dimensional data analysis, improved risk identification and more accurate decision-making.
In manufacturing, large models support precise forecasting, intelligent optimization and autonomous decision-making across production, scheduling, operation and management processes, improving operational efficiency, workplace safety and resource utilization.
04 Supportive Industry Policies
Sustained policy support from the government provides a solid foundation for the development of enterprise-grade large model-driven decision intelligence. The *2025 Government Work Report* explicitly stated its support for the wide application of large models, establishing top-level policy backing for the deployment of decision intelligence across industries.
Major cities across China have also rolled out targeted support policies for large models. For instance, Beijing’s *"AI+" Action Plan (2024–2025)* aims to seize the opportunities brought by large model technological innovation, significantly enhance indigenous innovation capabilities in large models, and fully leverage the enabling role of large model technology in industrial applications.
The plan also introduces "model vouchers" — a form of local fiscal subsidy designed to incentivize enterprise adoption of large models. Companies developing AI applications are eligible for partial financial support when using third-party model APIs or deploying large models on-premises. By lowering the financial barriers to accessing and deploying AI technologies, these subsidies encourage more enterprises, particularly small and medium-sized enterprises, to explore AI solutions, driving broader adoption of large models across industries.
Separately, Shanghai’s *Measures to Promote Innovative Development of AI Large Models (2023–2025)* focuses on three pillars: supporting innovation capacity building for large models, advancing innovative large model applications, and fostering the development of a sound large model ecosystem.
As a seasoned Industry Consultant, CIC offers services such as market sizing, competitive analysis, and enterprise value verification, etc., with global experience in advising "first-in-sector" IPOs in artificial intelligence and other sectors.
From IPO preparation to listing hearings, CIC unearths the true intrinsic value of enterprises and translates it into actionable insights for successful capital market landing. Prior to Zhongke WengeAI, CIC has supported leading enterprises in successful listings both domestically and overseas, including MiniMax, Baidu, Fourth Paradigm, etc.
CIC Reports are now available on Bloomberg and FactSet portals.
About CIC
CIC is a professional consulting firm offering tailored end-to-end support across the full investment and financing lifecycle. The firm boasts a world-leading track record in guiding landmark first-in-sector IPOs across global markets, alongside unrivaled reach and in-depth coverage capabilities across specialized niche market segments.
CIC helps enterprises refine scalable business models and craft compelling capital narratives to enable seamless access to global capital markets, while serving as a trusted due diligence partner to investment institutions. It delivers granular industry insights and direct access to subject matter experts, empowering clients to identify high-value opportunities and mitigate critical risks effectively.
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