AI-Driven Service Experience and Growth

Artificial intelligence is reshaping all industries with unstoppable momentum. From financial payment and knowledge work to creative production and globalized services, AI keeps pushing the boundaries of efficiency and possibility. Nevertheless, as technical capabilities become homogeneous and APIs accessible to all, the purely utilitarian logic of technology has hit its ceiling. Users now yearn to be understood, respected and cared for, while enterprises urgently need to translate technological potential into steady revenue growth. A fundamental question arises: How can intelligent systems evolve from cold functional tools into warm, empathetic partners?

The national policy Opinions on Expanding Capacity and Improving Quality of the Service Industry issued by the State Council clearly calls for "accelerating the innovative development of software and information services" and "advancing the digital and intelligent transformation of the service sector". Centered on the core theme "Human-AI Symbiosis, Experience First", this summit gathers leading AI design figures and industry practitioners from world-renowned tech companies including Microsoft, Google, Kuaishou, Didi, China Merchants Bank and Qihoo 360, to conduct in-depth discussions on "AI-driven transformation of service experience".

We will address the core contradictions encountered in real-world AI implementation: the versatility of technology versus the precision required by businesses, the probabilistic nature of generative outputs versus the reliability demanded by product delivery, and the mechanical rigidity of tools versus users’ desire for emotional resonance. Covering strategic mindset, design methodologies, real-world use cases spanning finance, commercialization and globalization, as well as internal closed-loop R&D efficiency systems, the summit will systematically demonstrate how human-AI collaboration reshapes a new service ecosystem, delivering full-spectrum guidance for the intelligent upgrade of service industries — from conceptual frameworks to actionable practices.

• Speech 1：When AI Is Everywhere, Why UX Designers Matter More Than Ever — UX as the True Moat of AI Products
  Speaker：Javy Wang （ Microsoft (US),Senior Lead Product Designer）

  As AI model capabilities grow homogeneous, APIs become universally accessible, and AI code generation is available to all, competition among AI products is shifting from "who boasts a more powerful model" to "who delivers a more valuable user experience". While technical barriers are collapsing, new product moats are being rebuilt — with UX taking on an unprecedentedly central role.
  
  Over the past two years, numerous technically advanced AI products with flawed user experiences have illustrated a clear truth: a tool packed with powerful functions may end up unused; it can deliver accurate answers yet confuse users; it may possess outstanding capabilities but fail to earn user trust. Meanwhile, many products without top-tier underlying models have pulled ahead by gaining deep insight into user scenarios, conversational rhythm, trust building and workflow integration. This is no coincidence, but a structural shift: the decisive competitive edge of AI products is moving from the model layer to the experience layer.
  
  This talk systematically dissects this industry transformation. Drawing on frontline design practices of Microsoft Azure enterprise AI products and user feedback from independently built AI products, it puts forward a complete conceptual framework: What core elements make up the UX moat? How can designers evolve from mere "feature polishers" to core product definers? This is not generic commentary on the importance of AI, but an in-depth reflection on where genuine competitive barriers lie when every stakeholder fixates on foundational models.
  

  Work Case

  • Javy Wang - AI transformation
  • Javy Wang - work chart
  • Javy Wang - AI Product development lifecycle
  • Javy Wang - UX evolution
• Speech 2：Financial Design Transformation: AI Reshaping the New Ecosystem of Banking Services
  Speaker：Chen Ming （ China Merchants Bank,Experience Design Team Manager）

  In the digital age, AI is restructuring every link of financial services at the fundamental logical level. As a practitioner of this transformation, the speaker will draw on China Merchants Bank’s exploration of intelligent design systems. From three dimensions — technology empowerment, mindset reconstruction and capability reshaping — the speech will elaborate on how MUI (Multimodal Interaction) and iSEA (Intent-Sensing Interaction Architecture) build financial design capabilities adapted to the AI era.
  
  1.Technology Empowerment: Shifting from Humans Adapting to Machines to Machines Understanding Humans
  MUI delivers multi-dimensional upgrades to human-computer interaction, forming a full value chain covering demand analysis through outcome evaluation.
  
  2.Mindset Reconstruction: From Function-Oriented Design to Intent & Emotion Recognition
  The iSEA paradigm unlocks designers’ creative potential and redefines the core value of design.
  
  3.Capability Reshaping: Designers as Curators and Gatekeepers of Intelligent Design Systems
  Designers equipped with data and systematic thinking participate in decision-making at a higher strategic level.
  While pursuing technological innovation, we remain anchored to the essence of design: innovation rooted in human-centric value.
  

  Work Case

  • Chen Ming - Intelligent design systems cover the full design value chain end-to-end
  • Chen Ming - Human & Agent Co-creation: Generative UI
  • Chen Ming - MUI Design Production Paradigm
  • Chen Ming - iSEA Human-Agent Interaction Paradigm
• Speech 3：AI Reconstructs Ad Creation: Fuel Kuaishou’s Commercial Growth
  Speaker：Liu Xin （ Kuaishou,Senior AI Product Designer）

  1. Topic Background:​
  AI is reshaping every aspect of digital advertising, with ad creative production undergoing the most fundamental transformation. The traditional linear process of “scripting → filming → post-production” is being by AI-driven end-to-end generation, compressing production cycles from days to minutes. However, in commercial scenarios, a technically impressive video ≠ a deployable ad creative. The latter must be tightly integrated with performance data, user profiles, compliance review, and brand safety—constituting a vast systemic project. This presentation will directly confront the core contradictions in commercializing AI, revealing how experience design can turn uncertain technological potential into certain revenue growth.
  
  2.Presentation Content:​
  This talk will use Kwai’s “Cili Kaichuang” platform as a case study to systematically deconstruct how we drive growth for commercial AI through experience design. The content follows a three-tier progressive logic:
  Identifying Contradictions: Analyzing Three Fundamental Conflicts in Commercializing AI​
  The volatility​ of technology vs. the stability​ required for experience
  The generality​ of models vs. the precision​ of business demands
  The probabilistic​ nature of generation vs. the usability​ required for delivery
  These conflicts define the core design challenge: finding a dynamic “optimal experience balance point” on the shifting riverbed of technology.
  Core Solutions: Sharing Three Key Design Approaches of “Cili Kaichuang”​
  
  2.1 Redefining What Constitutes Effective Commercial AI Creatives​
  Using “driving growth” as the benchmark, we deconstruct the creative production formula, build a creative asset system, and automate generation pipelines to redefine deployable creative standards—systematically transforming technological potential into revenue.
  
  2.2 Designing Evolvable Human-AI Collaboration Relationships​
  We share how the platform systematically designs three modes—“Collaboration → Supervision → Delegation”—evolving with AI capabilities, smoothly transitioning users from “operators” to “decision-makers,” continuously lowering barriers to entry and scaling adoption.
  
  2.3 Designing Structured Commercial Dialogue Mechanisms​
  Addressing the conflict between “vague natural language” and “precise business requirements,” we share how to turn “sentence-building” into “fill-in-the-blanks” through structured intent clarification, acting as a “business intent translator” to significantly enhance the usability and commercial value of AI output.
  
  3.Conclusion and Outlook: Extracting Reusable Design Thinking and Future Directions​
  We will conclude that in the AI era, the essence of experience innovation shifts from “designing interfaces” to “designing production relationships.” The eternal mission of design is to leverage all technological means to enable users to clearly express intent, understand process states, and obtain effective outcomes—ultimately transforming design from a “support function” into a “growth engine.”
  

  Work Case

  • agent design
  • agent design
  • Dialogue Design
  • The scene entry design of the agent family
  • agent ecosystem image design
  • AIGC Commercial Product Interaction Framework Definition
• Speech 4：Mechanical Uniformity to Organic Growth: Evolving Global Design for Human-AI Symbiosis
  Speaker：Dai Quan （ Didi Chuxing,Senior Design Research Specialist）

  Throughout the development of international products, design has long centered on "unification". Design standards were leveraged to boost efficiency, deliver consistent user experiences, strengthen brand recognition and support large-scale business expansion. However, with the integration of AI capabilities and increasingly diversified user demands, this paradigm built around rigid mechanical uniformity has revealed clear limitations. Products are no longer mere collections of functions; they interact with users with distinct personality, real-time feedback and unique brand temperament. This poses new challenges to internationalized design: designers now design far beyond interfaces and workflows — they shape how products build genuine connections with users across diverse cultural contexts.
  Drawing on Didi’s international design practices and first-hand insights from global regional markets, this talk explores how cross-border design evolves from mechanical uniformity to organic growth. It illustrates the shift from static design language to dynamic design systems that evolve continuously to adapt to varied local environments. Covering design systems, user insights and cross-cultural collaboration, the session addresses a core question: Faced with complex cultural differences and AI-powered intelligent products, how can we build global user experiences that balance operational efficiency and human warmth?
  
  Key takeaways include:
  1.A review of design’s shifting role in globalization and emerging challenges brought by the AI era
  2.How to craft user experiences that resonate and win preference across cultures, rather than merely meeting basic acceptance standards
  3.Strategies to build design systems that preserve unified operational efficiency while supporting dynamic iteration, enabling deeper human-AI connections
  

  Work Case

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• Speech 5：AI Coding Beyond Conversations — Scale LLMs for Enterprise Team Development
  Speaker：Wang Chuanhai （ Qihoo 360,Technical Director）

  The speed of AI code generation is self-evident and no longer needs further proof. Yet in real enterprise R&D scenarios, the real challenge has never been whether AI can write code. Instead, the critical questions lie elsewhere: Can AI grasp full project context? Can it comply with team coding standards? Can it integrate with existing development toolchains? Can it form a trustworthy closed loop covering files, terminals, Git, browsers, permission approvals, code rollbacks and quality gates? Without these capabilities, AI Coding remains nothing more than an extension of chat interactions and can hardly be fully integrated into enterprise development pipelines.
  
  This talk draws on real-world practices of the WisCode product to break down how we evolved a simple chat-and-code-generation AI assistant into a team-wide R&D workbench. The core goal is to make Agent execution visible, controllable, rollbackable and reusable — covering the full workflow from task initiation, context parsing and tool invocation, to permission verification, code diff display, failure recovery, Git collaboration and continuous delivery. The sharing centers around three core topics:
  
  1.Why AI Coding products cannot stop at basic chat and code generation. We unpack the fundamental differences between personal efficiency tools and enterprise-grade team R&D platforms.
  
  2.How to design collaborative experiences for AI Agents. This includes task triggering, context loading, tool calling, permission confirmation, code change visualization, error recovery, Git teamwork and continuous delivery.
  
  3.How teams scale AI’s value from individual developers to the entire organization. We cover the precipitation of reusable Skills, Harnesses, engineering specifications and data metrics, enabling AI to participate not only in code writing, but also cross-team collaboration, engineering governance and continuous delivery.
  
  If you are building AI development tools or exploring ways to embed AI deeply into R&D workflows, this session will deliver actionable methodologies: how to design an AI Coding workbench trusted by engineering teams, and how to translate large model capabilities into reusable, measurable and scalable enterprise R&D productivity.
  

  Work Case

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1.Strategic decision-makers including enterprise CEOs, CTOs and CDOs
2.Product Directors and AI Product Managers
3.UX specialists and Design Directors
4.Practitioners in technology services, software & information services, and supply chain finance
5.Officials and researchers from government institutions focusing on the digital-intelligent transformation of the service industry

1.Upgraded Strategic Cognition
Understand the evolutionary logic of AI shifting from a "tool" to a "collaborative partner"; master the three-layer competition framework of "Model - Experience - Trust"; and grasp the underlying rules that determine product success or failure in the AI era.

2.Practical Implementation Methodologies
Gain first-hand design strategies and real-world implementation cases from flagship products including China Merchants Bank’s MUI & iSEA, Google NotebookLM, Kuaishou Magical Creator, and Didi’s international design system.

3.Reusable Measurement Tools
Learn a six-dimensional experience indicator system tailored for the Agent era, which converts subjective concepts such as empathy and trust into quantifiable, manageable business metrics.

4.Cost Reduction, Efficiency Boost & Growth Roadmap
Explore how AI design systems cut R&D costs and streamline service workflows via human-AI collaboration; master commercial design practices that directly translate AI technology into revenue growth.

5.Organizational & Talent Transformation Framework
Clarify the capability upgrade path for designers and product managers in the AI era (e.g., shifting from "executors" to "curators"), and obtain a clear blueprint for building AI-ready teams within enterprises.