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Liu Yun
Qihoo 360
Design Director
Design Director of the 360 User Experience Center, Chair of the 360 Design Committee, Product Lead for 360 CV Model Applications, and Head of the 360 Design System. He have 10 years of internet product management experience. Responsible for multiple AI large model innovation product projects spanning domains including enterprise collaboration, design, R&D, and industrial AI transformation. Specializes in B2B AI innovation, design team development for AI design implementation, and emphasizes user experience and data-driven decision-making in products.
Design philosophy: Goal-oriented design thinking. Design must be goal-driven, structured, valuable, and measurable.
AI-Driven Enterprise Knowledge Value Leap
Amid the digital wave, enterprises face unprecedented data deluge and knowledge management challenges. As information explodes and business scenarios grow increasingly complex, the core difficulty in leveraging enterprise knowledge lies in information acquisition. Internal information is scattered across disparate systems, making it exceptionally challenging to identify useful versus outdated content. Understanding the relationships among employees, knowledge assets, and their interdependencies is crucial for successful internal search or Q&A services.
The rise of large models and generative AI has unlocked new dimensions for transforming enterprise knowledge value—through intelligent knowledge extraction, automated analysis, and real-time decision support, AI is reshaping how enterprises acquire, integrate, and create knowledge assets.
Against this backdrop, our workshop "AI-Driven Enterprise Knowledge Value Leap" explores how AI-powered systems can dismantle knowledge flow barriers, converting fragmented expertise, data, and scenarios into reusable strategic resources. This empowers enterprises to build sustainable competitive advantages in volatile markets.
Key Topics Include:
1. Case Study: Smart Policing Platform for Public Security
1.1 Analysis of Industry Pain Points
1.2 Building AI Knowledge Platform Scenarios
1.3 Police Incident Detection & Handling Platform Workflow: Resolving Resource Waste and Automating Transcript Generation
2. Chongqing Rail Transit Monorail Knowledge Large Model Project
2.1 Project Background: Significance of China’s First Monorail
2.2 Industry-Leading Monorail Knowledge Features
2.3 Product Introduction: Monorail Knowledge Large Model
3. Aircraft Maintenance Knowledge & Agent-Enabled Smart Work Platform for a Major Airline
3.1 Application Scenarios in Aircraft Maintenance
3.2 Traceability Differences Across Multi-Source Maintenance Records
3.3 Multi-Agent Autonomous Planning Platform for Airline Knowledge Base
4. Design-Driven Commercial Success: Overseas AI Image Product for Consumers
4.1 Global Consumer AI Market Status & Growth Trends
4.2 Technical Architecture, Design Goals & Value Strategy for Consumer AI Products
4.3 Gimme Art: Commercial Value Analysis of AI Image Product
5. Innovative Experience Design Methodology for Enterprise AI Projects
5.1 Workshop Frameworks: "Five Perspectives, Three Determinations" Strategy House
5.2 Agile MVP Essentials: Scenario-Driven, Value Loop, Quantifiable Metrics, Resource Integration, Talent Enablement
5.3 Holistic Analysis: Market Scale, Business Models, Experience Value & Strategy
1、Networking Session: Introduction of the Speaker & Team & Suitable Audience & Key Takeaways
2、Content & Case Study: "XX Public Security Command and Alarm Platform" - Enterprise Knowledge Base Implementation Challenges & Solutions
3、Interactive Workshop: Exploring Knowledge Application Opportunities Based on Enterprise Processes and Scenarios
4、Q&A & Free Discussion
1、Mid/Senior Product Managers
2、Managerial Roles in Enterprise AI Transformation
3、Mid/Senior Interaction Designers
4、Mid/Senior User Researchers
5、AI Industry Practitioners, AI Entrepreneurs
1、Master the Implementation Scenarios for AI Enterprise Knowledge
2、Master the Methodology for Enterprise Knowledge Application
