The Global AI Workforce
How AI is transforming work across every continent — and the path to truly planetary labour
The Planetary Vision
Our manifesto speaks of "networked intelligence that powers work everywhere, across every language, every industry, every continent." This isn't merely aspirational — it's the recognition that AI's transformative potential is inherently global. The question isn't whether AI will reshape work worldwide, but whether its benefits will be distributed equitably or concentrated in wealthy nations.
Today, roughly one in six people globally (16.3%) are actively using AI tools — 378 million people representing the largest year-on-year adoption jump ever recorded. Yet this adoption varies dramatically by geography, creating both urgent challenges and unprecedented opportunities.
The Leapfrog Opportunity
Just as mobile phones enabled developing nations to skip landlines — with M-Pesa revolutionizing banking in Kenya without traditional branch infrastructure — AI could enable emerging economies to leapfrog stages of industrial development. Countries can potentially go directly to AI-augmented productivity without the legacy infrastructure costs that burdened developed nations. The World Bank's 2025 Digital Progress Report highlights how "small AI" applications — designed to run on everyday devices without major infrastructure — are already delivering real impact in developing economies.
Global AI Adoption at a Glance
AI adoption rates vary dramatically across the globe. According to Microsoft's 2025 Global AI Adoption Report, the leading nations in working-age population adoption present a diverse picture:
| Rank | Country | AI Adoption Rate | Notable Trend |
|---|---|---|---|
| 1 | UAE | 64.0% | Up from 59.4% in H1 2025 |
| 2 | Singapore | 60.9% | Building national model on Qwen |
| 3 | Norway | 46.4% | Nordic digital leadership |
| 4 | Ireland | 44.6% | Tech hub advantage |
| 5 | France | 44.0% | Strong enterprise adoption |
| 18 | South Korea | ~30% | Jumped 7 positions in 3 months |
| 24 | United States | 28.3% | Leads in infrastructure, not usage |
| — | Japan | 19.1% | Strong robotics integration |
| — | China | 16.3% | 38% of global AI investment |
| — | India | 15.7% | Fastest-growing talent pool |
North America: The Infrastructure Powerhouse
While the U.S. ranks only 24th in individual AI usage rates, it dominates the infrastructure that powers global AI. According to Crunchbase, American companies captured 79% of all global AI funding in 2025 — $159 billion of the $202 billion invested worldwide.
United States
- $159B in AI funding (2025) — 79% of global total
- 73% of global AI compute capacity
- 61% of foundational AI models developed
- San Francisco alone: $122B raised
Sources: Crunchbase, Microsoft
Canada
- Home to AI pioneers: Geoffrey Hinton, Yoshua Bengio
- Strong AI research hubs in Toronto and Montreal
- Part of $280B North American startup ecosystem (2025)
Source: Crunchbase
The Concentration Concern
The U.S. dominance raises important questions about global AI equity. High-income countries account for 87% of notable AI models, 86% of AI startups, and 91% of venture capital funding — despite representing just 17% of the global population. This concentration creates both dependencies and opportunities for the rest of the world.
Europe: Regulation and Responsibility
Europe has taken a distinctive approach to AI — leading on regulation while investing heavily in "trustworthy AI." The EU AI Act, which entered into force in August 2024, represents the world's first comprehensive AI legal framework.
EU AI Act Implementation Timeline
AI Continent Plan
April 2025 strategy to make Europe a global AI leader while safeguarding democratic values, with focus on healthcare, education, and sustainability.
Nordic Leadership
Norway (46.4%), Ireland (44.6%), and France (44.0%) lead European adoption, driven by strong digital government services.
Apply AI Strategy
October 2025 initiative targeting AI adoption in SMEs and public sectors to unlock societal benefits.
Asia: The New Frontier
Asia presents the most diverse AI landscape globally — from China's state-backed AI push to India's services transformation to Southeast Asia's mobile-first adoption. The region that will shape AI's future is also where adoption patterns vary most dramatically.
China: The Strategic Competitor
Investment Scale
- •$125 billion invested in AI in 2025 (38% of global)
- •$8.2B National AI Industry Investment Fund (Jan 2025)
- •Alibaba: $53B capex plan for AI infrastructure
Open Source Leadership
- •Chinese models now ~30% of global AI usage
- •Alibaba's Qwen overtook Meta's Llama as #1 on Hugging Face
- •DeepSeek built for ~$5.6M (10% of Llama's cost)
Sources: Second Talent, Stanford HAI
India: The Talent Powerhouse
Market & Workforce
- •AI market: $6B → $20B by 2028 (26% CAGR)
- •AI talent demand: 600K → 1.25M by 2027
- •19.9% of global GitHub AI projects
Enterprise Transformation
- •47% of enterprises run multiple GenAI use cases
- •93% of leaders plan to use AI agents in 12-18 months
- •₹10,000+ crore IndiaAI Mission budget
Sources: AI Spectrum India, Microsoft Work Trend Index
Japan: Robotics Integration
- •44,500 industrial robots installed in 2024
- •450,500 operational robot stock
- •15,000+ eldercare robots deployed
- •World's 2nd largest robot market
South Korea: Rapid Adoption
- •1,012 robots per 10K workers (highest globally)
- •AI market: $7.17B → $53.87B by 2032
- •$71.5B five-year AI investment plan
- •Supplies 37% of global AI chips
Source: Fortune Business Insights
Southeast Asia: Mobile-First AI
The region is rapidly adopting AI through mobile platforms and fintech. Singapore leads with 60.9% adoption rate, building its national AI model on Alibaba's Qwen. Countries like Thailand, Malaysia, and Indonesia are developing monolingual models (OpenThaiGPT, MaLLaM) tailored to local languages and contexts. The AI Singapore initiative developed SEA-LION, supporting 11 Southeast Asian languages.
Emerging Markets: The Leapfrog Opportunity
For emerging markets, AI presents a historic opportunity — the chance to leapfrog traditional development stages, just as mobile phones enabled financial inclusion without traditional banking infrastructure.
Africa: The M-Pesa Model for AI
Africa's AI market is projected to grow from $4.5B in 2025 to $16.5B — a 27.42% annual increase. Kenya has emerged as the world leader in ChatGPT usage at 42.1% among internet users, driven by 92% smartphone penetration and grassroots adoption by small businesses.
- • Kenya, Nigeria, South Africa, Egypt: 83% of continental AI startup funding
- • 75% of young Africans use AI tools weekly
- • 230M digital jobs expected by 2030
African Language AI
InkubaLM — Africa's first multilingual small language model — supports Swahili, Yoruba, IsiXhosa, Hausa, and IsiZulu. The African Natural Voices initiative, funded by a $2.2M Gates Foundation grant, has recorded 9,000 hours of speech across 18 languages.
Sources: Mastercard AI in Africa, DigitalDefynd
Latin America: Fintech-Driven AI
The region's AI market is scaling from $11.82B in 2025 to $47.88B by 2031 (26.25% CAGR). Brazil and Mexico account for ~95% of regional AI patents. Mexico has become a "real regional hub" driven by nearshoring, with Mexico City producing 50% more tech graduates than Brazil's top market.
- • Fintech sector expanded 300% from 2017-2023
- • Mercado Livre: $9.2B regional investment (2025)
- • Embedded finance market: $39B in 2025
Regional Leaders
Chile, Brazil, and Uruguay lead the ILIA 2025 AI index with scores above 60. Early-stage investment surged 112% YoY in Q4 2025, with $690M flowing into startups.
Sources: GlobeNewswire, Crunchbase
Middle East: Petrodollar-Powered AI
The Gulf states have pledged $2 trillion in AI deals, representing one of the largest regional commitments globally. The UAE leads adoption at 64% (highest in the world), while Saudi Arabia has announced 2,200 megawatts of future data center capacity — four times the UAE's planned 500 MW.
- • Saudi $40B AI fund + $10B Google Cloud deal
- • UAE: 5-gigawatt Stargate data center project
- • G42: $10B for Arabic language models
Economic Diversification
AI is central to both nations' post-oil strategies. The UAE's National AI Strategy 2031 targets healthcare, logistics, and energy. Annual AI contribution growth is expected at 20-34% across the region.
Sources: Rest of World, Introl
Barriers to Global AI Access
For AI to be truly planetary, we must address the structural barriers preventing equitable global access. The World Bank's 2025 report identifies four foundational challenges: connectivity, compute, context (data), and competency (skills).
Infrastructure Gap
High-income countries host 77% of global data center capacity. Africa has 18% of the world's population but less than 1% of data center capacity. India generates one-fifth of global data but holds only ~3% of data center infrastructure.
Source: World Bank DPTR 2025
Talent Drain
Since 2022, the talent gap in Latin America has widened due to accelerated brain drain. India faces a ~50% talent shortfall (420K professionals vs 600K needed). Less than 5% of people in low-income countries have basic digital skills, compared to 66% in high-income nations.
Source: Deloitte-NASSCOM
Language Bias
Most AI models are optimized for English. ChatGPT recognizes only 10–20% of sentences in Hausa — a language spoken by 94 million people. Africa has 2,000+ languages, the vast majority underrepresented in AI training data.
Source: Nature
Capital Concentration
High-income countries capture 91% of AI venture funding despite representing 17% of global population. The U.S. alone received 79% of all AI funding in 2025. Smaller economies cite skill shortages and ambiguous ROI as key adoption hurdles.
Source: Crunchbase
The Path to Equitable Access
Despite these barriers, several developments are actively democratizing AI access globally. Open source models, multilingual initiatives, and infrastructure investments are creating pathways for broader participation.
Open Source AI Revolution
DeepSeek's January 2025 breakthrough demonstrated that frontier AI can be built for ~$5.6M — just 10% of comparable closed models. Marc Andreessen called it "a profound gift to the world." Chinese open-source models now account for ~30% of global AI usage, with Alibaba's Qwen overtaking Meta's Llama as the most downloaded model family on Hugging Face.
DeepSeek has seen surging popularity across Africa, where usage is estimated at 2-4x higher than other regions.
Multilingual AI Development
Cohere's Aya initiative involved 3,000+ researchers across 119 countries to develop models supporting 101 languages. India's Bhashini infrastructure has produced 350+ AI-powered language models across 22 official languages. The UAE's Falcon Arabic serves Modern Standard Arabic and regional dialects.
Local Talent Development
Kenya's KAISA (Kenya AI Skilling Alliance) coordinates national AI skills development. India's NITI Aayog programs have enrolled 865,000 candidates in emerging tech courses, including 320,000 in AI-specific training. Nigeria's Three Million Technical Talent program supports its 400+ AI companies and startups.
Infrastructure Investment
The Tony Blair Institute proposes a joint public-private GPU debt fund to catalyze compute infrastructure in developing nations. Middle-income countries now generate 40%+ of ChatGPT traffic — led by Brazil, India, Indonesia, and Vietnam — demonstrating demand that infrastructure investment could unlock.
Global Job Transformation
AI's impact on employment varies dramatically by region and economy type. The IMF estimates that almost 40% of global employment is exposed to AI — but the nature of that exposure differs significantly.
AI Job Exposure by Economy Type
~Half may benefit from AI integration; half face potential displacement
Less immediate impact but fewer resources for transition
Lower exposure but risk of missing productivity benefits
Net Positive Job Creation
The World Economic Forum's 2025 Future of Jobs Report projects AI will create 170 million new roles while displacing 92 million by 2030 — a net gain of 78 million jobs globally. The challenge is the transition: 63% of employers cite skills gaps as their main barrier, and 39% of core skills are expected to change by 2030.
Truly Planetary Labour
Our ambition is planetary: "the networked intelligence that powers work everywhere, across every language, every industry, every continent." We're building for global access from day one — because the benefits of AI labour should be distributed, accessible, and global.
The data shows both the challenge and the opportunity. While adoption gaps persist, the rapid spread of open-source models, mobile-first applications, and local language AI demonstrates that planetary reach is achievable. The question is whether we build systems that amplify existing inequalities — or create new pathways to shared prosperity.
Read the Manifesto →Sources & Further Reading
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