01 / UNDERSTAND
了解工作如何变化。
Translate changes in AI, jobs and the labour market into practical guidance about tasks, roles, careers and capability requirements.
GLOBAL SHAPERS CHENGDU HUBPRESENTS
Stay in
the Loop.
Build the capability — and agency — to navigate an AI-shaped world of work.
A Global Shapers Chengdu Hub initiative helping young people and early-career workers understand change, diagnose their capabilities, build what matters and apply it in the real world.
Real people. Shared learning. Practical change.
IMPACT AT A GLANCE
120K+Cumulative reachBroader reach through assessments, learning, events and project activities.
Broader reach through assessments, learning, events and project activities.
进一步探索5K+Direct participationsDirect participation across programme activities.
Direct participation across programme activities.
进一步探索200Facilitators trainedFacilitators prepared to support learning and capability building.
Facilitators prepared to support learning and capability building.
进一步探索30Sessions deliveredLearning and programme sessions delivered across the initiative.
Learning and programme sessions delivered across the initiative.
进一步探索800+Assessment startsAssessments started, rather than completed.
Assessments started, rather than completed.
进一步探索Reach, participation and outcomes measure different things.
How we measure03 / THE MODEL
从变化走向机会的路径。
The loop keeps capability building connected to the world people are trying to navigate.
02 / DIAGNOSE
了解自己的位置。
Identify strengths, gaps and development priorities across eight capabilities and six developmental AI Work Profiles.
03 / RESKILL
建立真正重要的能力。
Develop practical AI fluency, human-AI collaboration, judgment and role-based capabilities through online and offline learning.
04 / APPLY
将能力转化为证据。
Use challenges, projects and real-world problems to move beyond learning and demonstrate how AI can be applied to practical work.
05 / LEARN
Reflect, improve and repeat.
Carry learning from real-world application back into the next cycle of understanding, diagnosis and capability building.
Learn from real work. Bring it back into the Loop.
The AI transition should expand opportunity — not widen the gap.
AI is changing tasks, roles and career pathways faster than traditional learning and workforce systems can adapt.
But the ability to respond is uneven. Some people have access to new tools, guidance, professional networks and learning opportunities. Many others do not.
Stay in the Loop exists to make the AI transition more navigable and more inclusive — so people can understand what is changing, build the capabilities that matter, and turn those capabilities into real opportunity.
我们的愿景
Our vision is a future where AI expands human opportunity rather than deepening the divide between those who can adapt early and those who cannot.
简明的变化理论
- 更好的信息
- 更清晰的能力差距
- 有针对性的学习
- 真实世界的应用
- 更强的职业与劳动力成果
The goal is not more AI training. It is better adaptation to an AI-shaped world of work.
04 / 循环实践
Different contexts. A shared way forward.
The model connects research, diagnosis, learning and real-world application — and is already being tested across different contexts.
FDE OPEN NIGHT / SHANGHAI
120 in the room. 2,000+ online.
One question: how does AI actually get delivered?
FDE OPEN NIGHT
From AI demos to real-world delivery
前线工程与交付落地交流会
From enterprise agents and AI security to productization and frontline engineering, FDE Open Night brought developers, enterprise practitioners and AI builders together to explore what it takes to move AI from proof-of-concept into real delivery.
Co-organized by Global Shapers Chengdu Hub
FDE capability developmentEnterprise Agent deploymentAI safety and securityProductization after proof-of-conceptFrom Demo to real delivery
200+Registrations
~120Onsite participants
2,000+Livestream audience
5演讲嘉宾
Registrations, onsite participation and livestream audience are separate measures; they are not added into a unique-person count.
Chengdu, China · Applied AI Challenge
Learning matters when it can be used.
An applied AI challenge environment where participants move from ideas to problem framing, solution development and presentation.
WAIC Future Tech OPC Challenge · ~80 participants. Supported by Global Shapers Chengdu Hub.
Application makes capability visible, testable and useful beyond the learning room.
Bring a challenge into the loop
Original challenge poster
India
Foundational AI learning in India.
面向接触新兴技术和数字学习机会有限的儿童与社区，开展基础 AI 素养与未来准备度学习。
Foundational AI literacy · India classroom and remote learning
获得 AI 能力建设不应取决于地理位置或特权。
Earlier learning programmes
Foundational AI literacy · Learning delivery in China, India and Kenya
Earlier learning programmes across China, India and Kenya engaged 200+ educators and education leaders and reached 1,000+ learners. These are programme-specific figures, not additional initiative totals or India-only counts. They describe reach and participation, not unique people or learning outcomes.
Learning across distance
Shanghai · Xuhui, China
前沿部署工程与 AI 原生工作
以角色为基础的学习，重点是将 AI 系统与真实组织问题、工作流程和业务需求连接起来。
Nearly 100 practitioners and professionals. Supported through a collaboration involving OpenCSG, the Communist Youth League Xuhui District Committee and Global Shapers Chengdu Hub.
新兴 AI 角色同时需要技术素养与结合业务语境的判断力。
Read the source recap
05 / THE NETWORK
From Chengdu to communities around the world.
9Hubs in the network8Countries in our footprint
在多个社区中共同构建，而非局限于一间教室。
Connecting perspectives across Asia, Africa, Europe and North America.
Nine Global Shapers communities. Shared learning, with each hub contributing in its own way.
Hub networkHub network
Chengdu
China
Part of the Global Shapers community network supporting Stay in the Loop. Each hub takes part in its own way.
Map: Natural Earth · Public domain.
One model. Many local ways to use it.
The long-term goal is not to export one fixed curriculum. It is to build a model that local communities can adapt to their own workforce and learning context.
语言ExamplesDeliveryLearning contextLocal workforce needs
06 / TOOLS THAT POWER THE LOOP
Before telling people what to learn, help them understand where they stand.
LEVEL 1 · EXPLORE
AI Era Player / AIEP
6–7 minutes · 7 primary Player Types + the additional Mission Integrator identity · Exploratory · Shareable result
Quickly reflect on your current way of working with AI.
从 AI 时代玩家开始LEVEL 2 · DEEPEN
AI 素养与职业成长评估
17–22 min · 8 capability dimensions · Development report
Understand capabilities, strengths, blind spots and development priorities.
参加深入评估Learn about the AI fluency assessmentAI fluency isn’t one skill.
The quality of AI-supported work depends on more than knowing how to prompt. Our assessment looks at eight capabilities that shape how people frame problems, collaborate with AI, verify information, exercise judgment, take ownership, learn and create original value.
阅读 AI 素养框架Eight AI fluency capability dimensions
- Problem Framing & Task Selection
- AI Collaboration & Orchestration
- Verification & Information Literacy
- Explainable Ownership & Accountability
- Domain & Contextual Judgment
- Learning & Capability Transfer
- Synthesis & Original Contribution
- Human Complementarity & Implementation
Six developmental AI Work Profiles
The assessment does not reduce people to a single score. It identifies developmental patterns that help people understand how they currently work with AI — and what to build next.
- Strategic AI Collaborator
- Capable but AI-Dependent User
- Efficient but Fragile Operator
- Creative AI Synthesizer
- Responsible but Underutilized User
- Developing AI Professional
Explore the product experience
07 / LISTEN → MEASURE → ADAPT
We listen before we design.
We continuously gather perspectives from young professionals, business leaders, educators and workforce practitioners to understand how AI is changing real work before deciding what people should be assessed or trained on.
40+ FIELD CONVERSATIONS
从实地证据走向全球对话。
我们关于 AI、Z 世代与劳动力转型的工作洞察，为我们与商业领袖及国际受众围绕 AI 如何重塑早期职业工作、能力发展和未来工作展开的对话提供了依据。
Cross-hub dialogue, future-of-work conversations, research and public dialogue.
Listening across roles helps us understand what people need to learn, use and repeat.
Generation Z — The Great ExpectationDoes AI Change the Future of Work?
These conversations inform our work; they do not imply endorsement.
我们围绕证据设计，而不是围绕固定课程。
As work changes, the capabilities people need will change too. Research, field conversations and public dialogue continuously feed back into the program.
World Economic Forum
What China’s enterprise leaders reveal about the next phase of AI at work
探索证据World Economic Forum
What AI in education needs next: Lessons from youth leaders across five countries
探索证据AIGW Policy Observatory
The Missing First Rung
Emerging Signals on Gen Z, AI and Early-Career Development
探索证据AIGW Policy Observatory
From AI Adoption to Workforce Architecture
Building the Next Phase of Human-Centered Workforce Transformation
探索证据观看对话
公共对话让本地证据在不同社区与语境之间持续交流。
Featured conversation
Learning to think in the age of AI
Watch on YouTubeCross-hub dialogue
Learning across contexts
Watch on YouTubePublic dialogue
What capability building looks like in practice
Watch on YouTubePublic dialogue
Building the next loop
Watch on YouTube
Continue the conversation.
Explore the updated AIGW Policy Observatory event poster and watch the full conversations.
View all conversationsFROM REACH TO IMPACT
我们不把参与本身视为影响。
Reach matters. But the next question is whether capability, behaviour and opportunity actually change.
Reach
Who encountered the initiative
Participation
Who directly took part
能力
What people learned or developed
Application
What was applied in real situations
Outcome
What changed over time
The Impact Ledger
What the numbers mean.
120K+Cumulative reach
Cumulative exposure across assessments, learning, interviews and events — not a count of unique people or demonstrated outcomes.
5K+Direct participations
Participation across programme activities. A person may take part more than once, so this is not a count of unique people.
200Facilitators trained
Facilitators trained to support learning and capability building. Training facilitators is distinct from measuring what participants learn.
30Sessions delivered
Sessions delivered across the initiative. A session count describes activity, not learning or career outcomes.
800+Assessment starts
Assessments started, not completed assessments or unique participants. Starting an assessment does not demonstrate capability improvement.
What we are now testing
We are studying whether learning changes capability, practice and opportunity. These are questions we are exploring, not outcomes we have already demonstrated.
Capability Development
Stronger evidence of effective AI-supported work.
Real-World Application
New skills and workflows applied in study, work or projects.
Career Clarity
Better-informed learning and career decisions.
Learning Transfer
Capability carried into classrooms, organizations and communities.
Institutional Adoption
Tools and learning models reused by hubs, schools and organizations.
The people learn. The program learns.
人员UnderstandDiagnose技能再培训ApplyRepeat
ProgramListenTestMeasureAdaptRepeat
我们学到的内容会反馈到下一步的评估、教学与测试中。
08 / BUILD THE NEXT LOOP WITH US
JOIN THE LOOP.
Capability building gets stronger when more people can add a perspective, a problem, a place or a practical next step.
For individuals
Understand your AI capabilities.
参加评估For educators & communities
Bring practical AI capability building to your learners.
- Run an AI literacy activity
- Use the assessment
- Host a workshop
- Build a learning cohort
For organizations
Connect workforce needs with diagnosis, learning and real-world application.
- Run a capability cohort
- Pilot the diagnostic
- Bring a real-world challenge
- Contribute workforce evidence
For Global Shapers
Adapt the model in your community.
- Run the assessment
- Host a dialogue
- Deliver a learning activity
- Localize the model
- Share field evidence