Deep Analysis Report on Zhaogang Group (0056.HK) AI Agent Strategy

Based on collected materials and market data, I have prepared this

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On January 16, 2026, the first “AI+Traditional Industries” Practical Application and Development Forum themed “Empowering Hundreds of Industries · Integrating into Thousands of Sectors” was grandly held in Shanghai, co-hosted by the Artificial Intelligence Professional Committee of the China Electronics Chamber of Commerce and Zhaogang Group [1][2]. The forum brought together diverse participants from AI technology enterprises, traditional industry platforms, investment institutions, and academia to discuss how artificial intelligence can evolve from technical capability to industrial system application capability.

pointed out in his speech the core view: When artificial intelligence enters the deep waters of industry, there is no shortage of concepts and technologies; what is truly scarce is “an application path that can work sustainably” [1][2]. This judgment reveals the key bottleneck in the current development of AI+traditional industries—the gap from technical verification to large-scale implementation.

As an industrial internet platform rooted in the highly complex traditional steel industry, Zhaogang Group has been building a productive service system around the entire transaction process since its establishment in 2012.

[1][2]:

Core Scenario	AI Agent Applications	Strategic Value
Transaction Scenario	Intelligent quotation, demand matching, transaction decision support	Improve transaction efficiency and conversion rate
Logistics Scenario	Intelligent scheduling, route optimization, supply chain visualization	Reduce logistics costs by 15-20%
Finance Scenario	Intelligent risk control, credit assessment, supply chain finance	Solve financing difficulties for small and medium-sized enterprises
Management Scenario	Intelligent operation, data analysis, process automation	Improve organizational operational efficiency

Zhang Xiaokun, Managing Partner and Vice President of Zhaogang Group, stated at the forum that the company has achieved

[1][2], marking Zhaogang Group’s strategic upgrade from a “digital platform” to an “AI-native industrial internet platform”.

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After more than a decade of development, China’s steel e-commerce industry has formed a pattern of

. Key participants include:

Platform	Background	Competitive Advantage	Strategic Positioning
Zhaogang Group	Independent third-party	Data assets + AI capabilities	AI-native industrial internet platform
Ouyeel Cloud Commerce	Subsidiary of Baowu Group	Industrial chain integration capability	Steel ecological service platform
Steel E-commerce (Gangyin)	Subsidiary of Shanghai Steel Union	Information + transaction collaboration	Steel information-driven platform
China Steel Net	State-owned background	Resource integration capability	Government resource-based platform

According to industry analysis, Zhaogang Group holds

in the steel e-commerce sector, ranking among the top in the industry [3]. Compared with competitors, Zhaogang Group’s core differentiation lies in: , rather than just traffic or price advantages.

Dimension	Traditional E-commerce Competition	Competition in the AI Agent Era
Core Competitiveness	Traffic scale, price advantage	Data assets, AI capabilities
Customer Value	Information matching, transaction convenience	Intelligent decision-making, full-process optimization
Competitive Barrier	Number of users, transaction scale	Scenario understanding, algorithm accumulation
Profit Model	Transaction commissions, service fees	Intelligent value-added services, data services

Through its AI Agent strategy, Zhaogang Group is elevating the competitive dimension from “transaction matching” to “intelligent decision support”, which constitutes a

against traditional steel e-commerce platforms. As pointed out by Yang Runxin, a guest investor from Xianfeng Changqing: [2].

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Zhaogang Group’s statement at the forum is of great strategic significance: Zhang Xiaokun clearly stated, “As the company has achieved full-process penetration of AI in the pre-sales, in-sales, and after-sales links of steel circulation, it indicates that AI has the capability for cross-industry replication” [1][2].

Zhaogang Group AI Agent Cross-Industry Replication Model
├── Technical Layer: Large Model + Agent Framework (Universal Foundation)
├── Data Layer: Industrial Data Assets (Core Barrier)  
├── Scenario Layer: Business Process Digitalization (Implementation Foundation)
└── Capability Layer: Industry Know-How Accumulation (Key Differentiator)

1. Industrial Data Assets
   : Over a decade of accumulated steel circulation data, including full-dimensional data such as prices, demand, logistics, and suppliers
2. Standardized Business Processes
   : The entire steel transaction process is highly standardized, providing a foundation for digital transformation
3. In-Depth Scenario Understanding
   : Profound understanding of industry pain points (information asymmetry, low transaction efficiency, high logistics costs, difficulty in financial services)

During the forum, the Artificial Intelligence Professional Committee of the China Electronics Chamber of Commerce officially released the 2025 White Paper on Artificial Intelligence Industry Development, which systematically sorts out the global AI industry pattern, technological evolution path, and key application directions [1][2]. The core viewpoints of the white paper are of important reference value for understanding AI transformation in traditional industries:

• Standardization Construction
  : Promote the establishment of group standards for data governance, model application, and service quality
• Ecosystem Collaboration
  : Building a “common language” and “foundation of trust” is the key to large-scale implementation
• Scenario Focus
  : Start from real application scenarios, rather than simply pursuing technological advancement

Challenge Type	Specific Performance	Response Strategy
Data Standardization	Large differences in data format and quality across industries	Promote the construction of industry data standards
Scenario Adaptation	Significant differences in business processes across industries	Promote in phases and modularly
Organizational Transformation	AI transformation requires upgrading organizational capabilities	Talent cultivation and cultural construction
Return on Investment Cycle	AI implementation takes time to show results	Set reasonable expectations and milestones

According to the consensus of guests in the forum’s roundtable discussion, AI empowerment of traditional industries should follow a three-stage path of

[2]:

1. Phase 1 (Tool Application)
   : AI serves as an efficiency tool to assist manual decision-making
2. Phase 2 (Process Embedding)
   : AI is embedded into core business processes to achieve automation
3. Phase 3 (Model Restructuring)
   : AI reshapes the business model to create new value

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Evaluation Dimension	Rating (1-5)	Core Logic
Market Space	★★★★★	Trillion-level steel market + cross-industry replication potential
Competitive Barrier	★★★★★	Dual barriers formed by industrial data assets + AI capabilities
Policy Support	★★★★★	“AI+traditional industries” receives strong policy support
Business Model	★★★★☆	Verified in the steel circulation link
Technological Maturity	★★★★☆	Large model + Agent technology is becoming mature
Team Capability	★★★★☆	Founding team has profound industrial background

1. Track Logic
   : Intersection of industrial internet and AI Agent dual tracks, a scarce target
2. Growth Logic
   : Increasing AI penetration drives ARPU growth, and cross-industry replication opens up a second growth curve
3. Valuation Logic
   : The value of data assets is not yet fully reflected in traditional valuation systems

Risk Type	Specific Risk	Risk Level
Technological Risk	AI technology iterates rapidly, may be caught up	Medium
Competitive Risk	Leading platforms accelerate AI layout, industry competition intensifies	Medium
Implementation Risk	Uncertainty in large-scale commercialization of AI Agents	Medium
Macro Risk	Cyclical fluctuations in the steel industry affect platform transaction volume	Medium
Valuation Risk	High valuation volatility for early-stage growth enterprises	High

Investment Theme	Target Type	Representative Opportunities
Industrial Internet Platforms	Vertical industry leaders	Zhaogang Group, Ouyeel Cloud Commerce, etc.
AI Solution Providers	General AI technology enterprises	Zhipu, Yunhan Xincheng, etc.
Digital Transformation of Traditional Industries	Transforming traditional enterprises	Baoshan Iron & Steel, Sinosteel International, etc.
Infrastructure Layer	Data & computing power enterprises	Cloud computing, data service enterprises

According to recent changes in investment logic,

[4]. This transformation makes “AI+traditional industries” a core investment direction for 2026 and beyond.

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1. Strategic Significance
   : Zhaogang Group’s AI Agent strategy represents a typical path for industrial internet platforms to upgrade from “digitalization” to “intelligentization”, with industry demonstration effects
2. Competitive Impact
   : AI Agents are reshaping the competitive landscape of the steel e-commerce industry, shifting from “traffic competition” to “intelligent capability competition”, and Zhaogang Group has established a first-mover advantage
3. Replicability
   : Zhaogang Group’s model has a foundation for cross-industry replication, but key challenges such as data standardization and scenario adaptation need to be addressed
4. Investment Value
   : As a representative target of “AI+traditional industries”, Zhaogang Group has long-term investment value, but attention should be paid to technological iteration and commercialization progress

Investment Strategy	Specific Recommendation
Long-term Layout	Focus on the industrial internet + AI Agent track, and deploy leading targets on dips
Thematic Investment	“AI+traditional industries” has become a key policy-supported area, which can be allocated as a thematic investment
Risk Warning	Need to pay attention to the progress of technology implementation and changes in industry competition pattern

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[1] First “AI+Traditional Industries” Practical Application and Development Forum Held to Explore the Industrialization Path of Artificial Intelligence - Eastmoney.com

[2] First “AI+Traditional Industries” Practical Application and Development Forum Held to Explore the Industrialization Path of Artificial Intelligence - Sina Finance

[3] Zheshang Zhongtuo Investor Interaction - Zheshang Zhongtuo Official Website

[4] AI Investment Logic Shift Releases Three Positive Signals - China Economic Net