SHENZHEN, China, Oct. 23, 2026 /PRNewswire/ — Wenge AI brought together more than 50 academics, industry experts and business leaders from the Greater Bay Area for the first session of its seminar series on putting decision AI into practice in enterprises. Participants explored how AI is being applied to management decisions, risk anticipation and business analysis.
Decision-making becomes a new frontier for AI
In his opening remarks, Professor Liu Min, a director at The Chinese University of Hong Kong (CUHK) Business School, said AI was rewriting the fundamental rules of business competition. Managers should test its effectiveness in real operating environments rather than simply observe its development, he said. He welcomed Wenge AI’s sustained investment in decision AI and expressed hope that Chinese AI companies would translate their technological capabilities into productivity gains for society.
Hang Tian, director of CUHK’s Asian Institute of Supply Chains & Logistics, outlined the institute’s latest AI research. He said the institute had long used AI to translate research into practical applications. A macro-event analysis system developed by his team is supporting the deployment of logistics agents for warehousing, transport capacity and compliance. He looked forward to working with Wenge AI to support Chinese companies expanding overseas and using AI to strengthen the real economy, turning research findings into workflows that businesses can put into operation.
Wenge AI chairman Wang Lei said general-purpose large language models still faced limitations in enterprise decisions involving multiple stakeholders, complex reasoning and rapidly changing conditions. Decision AI would move beyond answering questions to simulating future scenarios, he said. Wenge AI has built the Decitron Decision Engine, which is the world’s first general-purpose large decision model, alongside its Decision Intelligence Platform (DIP) to support decision-making in real business operations.
Enterprises move from AI exploration to implementation
Xu Huansheng, vice-president of Meinian Health Group, spoke on “AI-driven transformation in the healthcare industry: decision-making, operations and growth”. He said AI was now essential for businesses. Markets would value companies for their future capabilities rather than pay a premium for past achievements.
Meinian Health Group has pursued an AI transformation since 2021, Xu Huansheng said. The quality of AI-assisted decisions depends on the completeness and continuity of data. In healthcare, AI can deliver meaningful insights when imaging data, blood test results, genetic data and other information are connected and accumulated consistently over time. Meinian has been progressively embedding AI capabilities into its day-to-day operations.
Wenge AI vice-president Zhang Xina presented the case of a Fortune Global 500 new energy company that previously spent several days manually reconciling tens of thousands of purchase orders. After adopting Wenge AI’s DIP and large decision model, the company created a digital twin of its procurement workflow using data from its enterprise resource planning (ERP) system. Materials planners now use a single consolidated view to complete the work in about 10 minutes each day.
The system also identifies the causes of delivery problems. When the company’s on-time delivery rate fell by about 25 percentage points month on month, the AI identified incomplete shipments after dispatch, rather than slow dispatch, as the root cause. One supplier was delivering an average of 83 days late.
Frank, a veteran chief information officer, shared an enterprise perspective in his presentation on “Best practices for enterprise AI agents”. His team initially invested in integrated AI appliances and an internal AI platform to improve efficiency, but employees sometimes found that using them created additional work. His company has now embedded an AI ontology into the sales, planning and materials modules of its ERP system. The system directly handles demand forecasting, anomaly detection and order processing, with audit trails to ensure traceability. He said AI’s value should be demonstrated through the redesign of real business workflows.
Embedding AI into enterprise decision-making requires effective data governance, process redesign and validation in real business operations. Wenge AI develops general-purpose large decision models and enterprise platforms to help businesses turn AI capabilities into tangible value.