01
UNDERSTAND
See how work is changing.
Translate changes in AI, jobs and the labour market into practical guidance about tasks, roles, careers and capability requirements.
A Global Shapers Chengdu Hub Initiative
Stay in the Loop.
AI is changing work. Everyone deserves a way to keep up — and move forward.
Stay in the Loop helps people understand how AI is reshaping work, diagnose the capabilities they need, build what matters, and apply it in the real world.
A public project and evidence page for an international AI capability-building initiative.
Stayin the loopLearn · use · repeat
UNDERSTAND01
DIAGNOSE02
RESKILL03
APPLY04
UnderstandDiagnoseReskillApply
01 / WHY THIS EXISTS
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.
Our vision
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.
02 / HOW CHANGE HAPPENS
A pathway from change to opportunity.
The loop keeps capability building connected to the world people are trying to navigate.
Understand → Diagnose → Reskill → Apply → Learn → Repeat
02
DIAGNOSE
Know where you stand.
Identify strengths, gaps and development priorities across eight capabilities and six developmental AI Work Profiles.
03
RESKILL
Build what matters.
Develop practical AI fluency, human-AI collaboration, judgment and role-based capabilities through online and offline learning.
04
APPLY
Turn capability into evidence.
Use challenges, projects and real-world problems to move beyond learning and demonstrate how AI can be applied to practical work.
Stayin the loopLearn · use · repeat
UNDERSTAND01
DIAGNOSE02
RESKILL03
APPLY04
A light theory of change
Better information→Clearer capability gaps→Targeted learning→Real-world application→Stronger career and workforce outcomes
The goal is not more AI training. It is better adaptation to an AI-shaped world of work.
03 / PROGRESS
Progress at a glance.
10K+People reached through the AI capability assessment
12Countries reached
200+Educators and education leaders engaged
1,000+Learners reached through participating communities
7Global Shapers communities connected or represented
40+Field conversations
3Countries with active learning delivery
10K+ means reach — not completed assessments.
04 / THE LOOP IN ACTION
The Loop in Action
The model connects research, diagnosis, learning and real-world application — and is already being tested across different contexts.
UNDERSTAND
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
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.
DIAGNOSE
Before telling people what to learn, help them understand where they stand.
AI Fluency & Career Growth Assessment
AI 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.
01Problem Framing & Task Selection02AI Collaboration & Orchestration03Verification & Information Literacy04Explainable Ownership & Accountability05Domain & Contextual Judgment06Learning & Capability Transfer07Synthesis & Original Contribution08Human 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 CollaboratorCapable but AI-Dependent UserEfficient but Fragile OperatorCreative AI SynthesizerResponsible but Underutilized UserDeveloping AI Professional
Reached 10K+ people across 12 countries.
ai-fluency-career-growth / report
ai-fluency-career-growth / report
RESKILL
Turn capability gaps into learning pathways.
Shanghai, China · Nearly 100 practitioners and professionals
Forward Deployed Engineering & AI-Native Work
Role-based learning focused on connecting AI systems with real organizational problems, workflows and business needs.
Supported through a collaboration involving OpenCSG, the Communist Youth League Xuhui District Committee and Global Shapers Chengdu Hub.
Why it matters: Emerging AI roles require both technical fluency and business-context judgment.
Read the source recap
India & Kenya · Foundational AI literacy
Learning that starts with possibility.
Foundational AI literacy and future-readiness learning for children and communities with limited access to emerging technology and digital learning opportunities.
200+ educators and education leaders engaged1,000+ learners reached through participating communitiesChina · India · Kenya active learning delivery
Why it matters: Access to AI capability building should not depend on geography or privilege.
India learning images are supplied program documentation. Public deployment should confirm school/partner permission for identifiable minors; this page prioritizes wide, activity-focused views.
APPLY
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 — Chengdu · ~80 participants
Global Shapers Chengdu Hub supported the challenge as a supporting organization shown on the public poster.
Why it matters: Application makes capability visible, testable and useful beyond the learning room.
Bring a challenge into the loop
05 / ACROSS THE LOOP
Built across communities, not in one classroom.
Connecting perspectives across Asia, Africa, Europe and North America.
7 Global Shapers communities connected or represented4 world regions3 countries with active learning delivery
01Chengdu02Beijing03Chicago04Dubai05Nairobi06Lucerne07Kolhapur
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.
ChengduBeijingChicagoDubaiNairobiLucerneKolhapur
06 / FROM FIELD EVIDENCE TO GLOBAL DIALOGUE
From field evidence to global dialogue.
Insights from our work on AI, Gen Z and workforce transformation have informed conversations with business leaders and international audiences on how AI is reshaping early-career work, capability development and the future of work.
Generation Z — The Great ExpectationDoes AI Change the Future of Work?
Field intelligence, not endorsement.
Read the World Economic Forum article
07 / EVIDENCE BEHIND THE WORK
We design around evidence — not a fixed curriculum.
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
Read the field intelligenceWorld Economic Forum
What AI in education needs next: Lessons from youth leaders across five countries
Read the field intelligenceAIGW Policy Observatory
The Missing First Rung
Emerging Signals on Gen Z, AI and Early-Career Development
Explore the evidenceAIGW Policy Observatory
From AI Adoption to Workforce Architecture
Building the Next Phase of Human-Centered Workforce Transformation
Explore the evidenceWATCH THE CONVERSATIONS
Watch the conversations
Public dialogue keeps local evidence in conversation across communities and contexts.
Featured conversation
AI & Education Policy Dialogue
Cross-hub dialogue
Learning across contexts
Public dialogue
What capability building looks like in practice
Public dialogue
Building the next loop
PEOPLE
UnderstandDiagnoseReskillApply
PROGRAM
ListenTestMeasureAdapt
What we learn feeds back into what we assess, teach and test next.
09 / FROM REACH TO IMPACT
From reach to impact.
Reach matters. But the next question is whether capability, behaviour and opportunity actually change.
WHAT WE CAN PROVE TODAY
10K+People reached through the AI capability assessment
12Countries reached
200+Educators and education leaders engaged
1,000+Learners reached through participating communities
7Global Shapers communities connected or represented
3Countries with active learning delivery
OUTPUT→OUTCOMEReach becomes meaningful when it changes capability, behaviour or opportunity.
WHAT WE ARE NOW TESTING
The next evidence layer — not a claim that these outcomes have already been achieved.
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.
METHODWe do not treat participation as impact.
10 / JOIN THE LOOP
Stay in 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.
Take the AssessmentFor educators & communities
Bring practical AI capability building to your learners.
Ways to participateRun an AI literacy activityUse the assessmentHost a workshopBuild a learning cohort
Bring It to Your Community For organizations
Connect workforce needs with diagnosis, learning and real-world application.
Ways to participateRun a capability cohortPilot the diagnosticBring a real-world challengeContribute workforce evidence
Explore a Pilot For Global Shapers
Adapt the model in your community.
Ways to participateRun the assessmentHost a dialogueDeliver a learning activityLocalize the modelShare field evidence
Bring It to Your Hub Led by Global Shapers Chengdu HubKnowledge and research collaborator: Global AI Governance & Workforce Transformation Policy Observatory (AIGW Policy Observatory)