AI Middle Way Coalition

The Economic Case for
Global South AI Governance

How sovereign AI frameworks can unlock a new consumer market of 3.1 billion people, generate $14–18 trillion in GDP, and transform the lower middle class into the engine of 21st-century growth — by 2035.

3.1B
People Served
$14–18T
Coalition GDP by 2035
$10.1T
Swing vs. Fragmentation

The Problem: AI Without Governance Deepens Inequality

AI could add $19.9 trillion to the global economy by 2030.1 But without governance frameworks, only 3% of those benefits reach Latin America and 8% reach Africa, Oceania, and developing Asia combined.2

Today, seven technology companies are valued at over $21.5 trillion — roughly equal to the GDP of the entire Global South.3 The United States alone captured $109.1 billion in private AI investment in 2024, more than 8.7 times China, the second-highest country.4 Two-thirds of the world's data center capacity sits in the United States, China, or Europe.5 Africa holds less than 1% of global data center capacity despite being home to 18% of the world's population.6

This creates a stark disparity: the United States consumes over 540 kWh per capita in data center electricity, while Africa uses less than 1 kWh per capita — a 600-fold gap in AI access.7 Without intervention, the Global South risks becoming a permanent data-extraction zone while the benefits of AI concentrate in a handful of nations.

The Opportunity: Adding a New Tier to the Global Market

The AI Middle Way offers something no current framework does: a pathway to bring the lower middle class — 3.1 billion people earning $4–10 per day — into the formal economy as consumers, producers, and entrepreneurs.

This is not charity. It is market creation. AI dramatically reduces the per-unit cost of delivering education, financial services, and skills training to large dispersed populations. A platform that serves 100,000 lower-middle-class learners becomes smarter and cheaper for the next cohort. The marginal cost drops while the value increases — a virtuous cycle that markets can sustain without permanent subsidy.8

The Core Economic Logic

AI-enabled cooperative formalization brings 300–400 million informal workers into the formal economy, generating documented income, tax revenue, and creditworthiness. This creates a new consumer tier that neither superpower can ignore — a market comparable in scale to the European Union but growing at 4–5% annually instead of 1–2%.9

Three Mechanisms of Market Expansion

Mechanism People Reached Income Increase Annual Economic Impact
Cooperative Formalization 300–400 million +$1,000–3,000/year $300–400 billion
AI-Enabled Skills Upscaling 200–300 million +$2,000–4,000/year $200–400 billion
Data Ownership & Monetization 500–800 million +$500–1,000/year $500–800 billion
Total Annual Impact 1 billion+ +$4–21/day average $1.0–1.6 trillion

These projections assume 50% adoption rate by 2035 across all coalition nations, with phased implementation beginning 2026–2028.10

Two Futures: Fragmentation vs. the Middle Way

The difference between inaction and coordinated governance is not marginal. It is a $10.1 trillion swing by 2035.

Without AI Middle Way

−$6.35 Trillion

Cumulative GDP loss across six founding nations (2030–2035) from AI fragmentation, data colonialism, and unmanaged labor displacement.11

45 million jobs displaced without transition programs. 25–30% of the lower middle class falls back into poverty.12

$20 billion/year in data value extracted without compensation by 2035.13

With AI Middle Way

+$3.75 Trillion

Cumulative GDP gain through sovereign AI governance, cooperative formalization, and managed AI transitions.14

8 million jobs displaced — with transition programs. 150–200 million people move up to middle-class status.15

90% of data value retained locally. $170 billion in cumulative data sovereignty gains.16

Scaling to the Full Global South by 2035

The founding coalition of six nations is the proof of concept. Adding India, Brazil's regional partners, and broader Africa creates a market that fundamentally reshapes the global economy.

Phase Nations Population Combined GDP Lower-Middle Class
Phase 1 (2026–28) Thailand, Indonesia, Mexico, Peru 500 million $3.87 trillion ~255 million
Phase 2 (2028–30) + Brazil, South Africa 850 million $6.45 trillion ~400 million
Phase 3 (2030–35) + India, Nigeria, Kenya, Vietnam, Colombia, others 2.6–2.8 billion $14–18 trillion ~1.5 billion
Full Coalition Potential (2035) 2.8B $14–18T 18–22% of global GDP

The Third Consumer Market

By 2035, the AI Middle Way coalition becomes a third consumer market alongside the US ($10T) and EU ($8T). With 2.8 billion people, a $5–6 trillion consumer market, and $300–400 billion in tech spending, it commands a scale that neither superpower can afford to ignore — and a growth rate (4–5% annually) that far exceeds either.17

What Middle-Class Formation Looks Like

At the individual level, the AI Middle Way transforms a motorcycle taxi driver earning $5,500/year in Thailand into an e-commerce operator earning $18,000. A street vendor in Mexico earning $12,000 becomes a supply chain assistant at $24,000. An informal trader in Indonesia earning $8,000 becomes an SME manager at $16,000.18

By 2035, the coalition defines middle class differently from the developed world: built on cooperative ownership rather than individual home ownership, data ownership rather than passive consumption, and multiple income streams rather than single-employment dependency. But it is genuine middle class — with economic security, savings capacity, access to credit, and the dignity that comes with formal participation in the economy.19

The Infrastructure Investment Required

Transforming the Global South requires massive infrastructure — but the costs are not as insurmountable as they appear, especially when shared across a coordinated coalition.

Global AI Infrastructure: The Scale of the Challenge

McKinsey projects global AI data center capital expenditure between $3.7–7.9 trillion by 2030, with a mid-range scenario of $5.2 trillion.20 JPMorgan estimates more than $5 trillion in data center and AI infrastructure spending over five years.21 Nearly 100 GW of new data centers will be added between 2026 and 2030, doubling global capacity.22

But the vast majority of this spending is concentrated in the Global North. The Global South's share of this investment is less than 5% — despite being home to 85% of the world's population.23

What the Coalition Needs: Component-by-Component

Infrastructure Component Global South Cost (10-year) Coalition Share Key Challenge
Compute & Data Centers $300–500 billion $120–200B Power availability, cooling
Internet Connectivity (Fiber & Satellite) $200–300 billion $80–120B Last-mile access, rural coverage
Electrification & Power Generation $400–600 billion $160–240B Grid stability, renewables
Network Infrastructure (5G, Edge) $200–300 billion $80–120B Low-latency requirements
AI-Capable Devices (Smartphones, Tablets) $150–250 billion $60–100B Affordability at $4–10/day income
Education & Skills Training $150–250 billion $60–100B Teacher training, curriculum
E-Government & Digital Public Infrastructure $100–150 billion $40–60B Data governance, cybersecurity
Total 10-Year Requirement $1.5–2.35 trillion $600B–940B

Sources: McKinsey Global AI Infrastructure Report, CSIS Global South AI Analysis, ITU Broadband Commission, IEA World Energy Outlook, World Bank Digital Development.20,24,25,26

Why Coordination Drops the Price

When six nations deploy AI infrastructure individually, the total Phase 1 cost is $4.698 billion. When they coordinate through the AI Middle Way coalition, the effective deployment capacity rises to $5.506 billion — a 17.2% efficiency gain worth $808 million — without any increase in foundation grants or concessional financing.27

$333M
Foundation Grants & PRIs
$645M
Development Bank Finance
$1.08B
Sovereign Wealth Funds
$1.81B
Infrastructure & Connectivity
$1.12B
E-Gov & Consumer Products

Eight-tier financing flow across the coordinated six-nation coalition. Total: $5.506 billion (Phase 1).27

Economies of Scale at Coalition Level

Financing Layer Individual Approach Coordinated Coalition Scale Benefit
Sovereign Wealth Fund Investment $935 million $1.085 billion +16%
Internet Infrastructure $1.465 billion $1.805 billion +23%
Electrification Upgrades $620 million $723 million +17%
E-Government Services $540 million $612 million +13%
Consumer Products $435 million $505 million +16%
Total $4.698 billion $5.506 billion +17.2%

The efficiency gains come from bulk procurement, shared technology platforms, joint negotiation with satellite providers (e.g., Starlink reduced-rate agreements), coordinated device manufacturing (dropping smartphone costs by 15–25%), and shared e-government code bases that avoid redundant development across six nations.27,28

Why Both Superpowers Benefit

The AI Middle Way does not exclude the US or China — it creates market incentives for both to collaborate rather than compete in the Global South.

Under the current fragmentation scenario, duplicated infrastructure (US-aligned vs. China-aligned systems) adds a 40–60% cost premium for Global South nations forced to maintain parallel ecosystems. Competing technical standards increase development costs and reduce network effects. Semiconductor supply chain decoupling adds 25–35% to chip costs.29

The Collaboration Dividend

Area Fragmented Scenario Coordinated Scenario Savings
Infrastructure Buildout (Global South) $300 billion $180–200 billion 33–40%
AI Compute Costs Baseline 30–40% lower 30–40%
Time-to-Market (Applications) Baseline 2–3 years faster Significant
Standards Development Costs Doubled (two ecosystems) Unified standards 50–60%

For the US, a coalition of 2.8 billion consumers with growing purchasing power represents the largest untapped tech market on Earth. For China, it means access to markets where its cost-effective AI solutions can scale. For both, the alternative — a coordinated Global South that excludes uncooperative partners — creates powerful incentive to negotiate on terms favorable to all parties.30

Nation-by-Nation Impact (Phase 1–2)

Conservative projections for each founding nation, assuming 50% adoption among the lower middle class by 2035.

Nation Lower-Middle Class Current Avg. Income 2035 Projected Income GDP Impact Investment (Phase 1)
Thailand 10 million $12,000 $18,000 (+50%) +$85B $720M ($36/capita)
Indonesia 26 million $9,000 $14,000 (+56%) +$120B $1.575B ($22/capita)
Mexico 15 million $25,000 $35,000 (+40%) +$180B $1.160B ($29/capita)
Peru 4 million $8,500 $13,000 (+53%) +$35B $333M ($37/capita)
Brazil 40 million $11,000 $16,500 (+50%) +$185B $1.830B ($18/capita)
South Africa 14 million $7,500 $12,000 (+60%) +$42B $450M ($32/capita)
Six-Nation Total: 109M people +$647B $6.068B

Income figures are per-capita annual averages for the lower-middle-class tier in each nation. GDP impact reflects cumulative gains from formalization, skills upscaling, and data sovereignty through 2035.14,15,18

The Window Is Closing

AI infrastructure investments become path-dependent by late 2027. Once locked in, the architecture of the global AI economy will be extraordinarily difficult to change.

Inference workloads are projected to overtake training as the dominant AI requirement by 2027.31 At that point, the geographic distribution of inference centers — close to users, integrated with local data ecosystems — becomes fixed. Nations without sovereign governance frameworks will find themselves permanently dependent on external infrastructure, their data flowing outward with no return.

The AI Middle Way Coalition was launched — not out of theoretical interest, but because 2026–2027 represents the final practical window for establishing governance frameworks before infrastructure lock-in makes the current global AI architecture permanent.32

2026 → 2035

From Bangkok Declaration to Global Transformation

April 21, 2026: Bangkok Declaration signed by founding nations plus the Vatican.
2026–2028: Phase 1 proof of concept across Thailand, Indonesia, Mexico, and Peru.
2028–2030: Phase 2 expansion to Brazil and South Africa.
2030–2035: Phase 3 cascade to 15–20 nations, 2.8 billion people, 18–22% of global GDP.

References & Sources

  1. [1] International Data Corporation (IDC). "AI to Add $19.9 Trillion to the Global Economy by 2030." Cited in CSIS, "An Open Door: AI Innovation in the Global South Amid Geostrategic Competition," October 2025. csis.org
  2. [2] CSIS. "An Open Door: AI Innovation in the Global South Amid Geostrategic Competition." October 2025. Only 3% of projected AI economic benefits to Latin America; 8% to Africa, Oceania, and developing Asia combined. csis.org
  3. [3] Market capitalization data for Apple, Nvidia, Microsoft, Alphabet, Amazon, Meta, and Tesla ("Magnificent Seven"). S&P 500 data shows these companies representing approximately 34.4% of the index. Multiple sources including Bloomberg, Reuters, and AFL-CIO Executive Paywatch, 2024–2025.
  4. [4] CSIS. AI-related private investment data. The United States secured $109.1 billion in 2024, 8.7 times more than China, the second-highest country. October 2025. csis.org
  5. [5] OMFIF. "How the Global South May Pay the Cost of AI Development." July 2024. Two-thirds of existing data centers located in the US, China, or Europe. omfif.org
  6. [6] CSIS. "From Divide to Delivery: How AI Can Serve the Global South." October 2025. Africa accounts for less than 1% of global data center capacity despite 18% of world population. csis.org
  7. [7] Brookfield Asset Management and IEA data on per-capita data center electricity consumption. US at 540 kWh per capita (2024), Africa at less than 1 kWh per capita. Projections from International Energy Agency, World Energy Outlook 2024–2025.
  8. [8] World Economic Forum. "How AI Can Help to Unlock the Global South's Job Market." August 2025. AI dramatically lowers cost of delivering vital services and creates new professional categories. weforum.org
  9. [9] AI Middle Way Coalition internal analysis drawing on World Bank informal economy data, ILO Global Employment Trends 2024–2025, and IMF World Economic Outlook. Coalition consumer market projections modeled on EU-scale comparison at 2.8B population.
  10. [10] Income growth scenarios modeled on Indonesia's Gojek platform effects (2015–2024), Thailand's Meaningful Broadband implementation (2006–2016), and Mexico's fintech sector formalization data. Conservative bounds assume linear adoption, not exponential.
  11. [11] IMF. "AI and the Global Economy." 2024. Growth impacts in advanced economies potentially more than double those in low-income countries under fragmentation. Cumulative loss calculated across Thailand ($85B), Indonesia ($120B), Mexico ($180B), Peru ($35B), Brazil ($450–600B), South Africa ($120B) based on IMF displacement modeling.
  12. [12] World Bank. "Generative AI and Jobs in Latin America and the Caribbean." 2024. Estimates up to 5% of jobs at risk of full automation from generative AI. Foreign Policy, "AI Is Bad News for the Global South," December 2024. foreignpolicy.com
  13. [13] Coalition modeling based on current data extraction valuation. Global consumer data market estimates from IDC and Gartner, 2024–2025. $20B/year represents estimated value of uncompensated data extraction from six-nation coalition populations by US and Chinese tech firms.
  14. [14] AI Middle Way Coalition. "Eight-Tiered Macroeconomic Financing Architecture." January 2026. Phase 1 ($2.51T gain) + Phase 2 ($1.24T gain) = $3.75T cumulative gain. Methodology based on IMF AI productivity premium capture rates (22–28% capture with governance vs. 8–12% without).
  15. [15] Job transition figures from ILO managed transition models applied to coalition nations. 150–200M middle-class formation projection from World Bank income mobility data combined with AI-augmented skills premium estimates (15–20% entry-wage increase for AI-literate workers).
  16. [16] Data sovereignty value calculated as difference between fragmentation scenario ($20B/year extraction) and Middle Way scenario ($3B/year extraction, 90% local retention). 10-year cumulative difference: $170 billion.
  17. [17] Consumer market comparison: US ~$10T, EU ~$8T (2024 data from World Bank and Eurostat). Coalition projection of $5–6T consumer market and $300–400B tech spending based on income growth scenarios applied to 2.8B population with 4–5% growth trajectory.
  18. [18] Income transition examples from AI Middle Way Coalition modeling, December 2025. Based on observed income effects from Gojek formalization in Indonesia, Thailand's digital economy growth data, and Mexico's fintech inclusion studies (Banxico Financial Inclusion Reports, 2023–2025).
  19. [19] Middle-class definition adapted from World Bank "Global Economic Prospects" and Brookings Institution "The Emerging Middle Class in Developing Countries" (Kharas, 2017). $15,000–40,000/year combined household income threshold adjusted for purchasing power parity.
  20. [20] McKinsey & Company. "The Cost of Compute: A $7 Trillion Race to Scale Data Centers." April 2025. Mid-range scenario: $5.2T in capital expenditure, 125 incremental GW added 2025–2030. mckinsey.com
  21. [21] JPMorgan Chase & Co. Global data center and AI infrastructure analysis. More than $5 trillion projected over five years; 122 GW of capacity expected 2026–2030. datacenterdynamics.com
  22. [22] JLL. "2026 Global Data Center Outlook." January 2026. Nearly 100 GW of new data centers expected 2026–2030, doubling global capacity. 14% CAGR through 2030. Average global construction cost: $11.3M per MW in 2026. jll.com
  23. [23] IDC. Global AI infrastructure market data, Q2 2025. US accounts for 76% of global AI infrastructure spending; China 11.6%; Asia-Pacific (inc. Japan) 6.9%; EMEA 4.7%. techloy.com
  24. [24] ITU/UNESCO Broadband Commission for Sustainable Development. Global connectivity investment estimates. ITU estimates $983 billion needed for universal affordability including smartphones and services.
  25. [25] International Energy Agency (IEA). Data center electricity consumption reached 415 TWh in 2024 (~1.5% of global demand), expected to triple by 2035. cited via CSIS
  26. [26] World Bank. Digital Development overview and "Connecting for Inclusion" reports. Only 35% of people in developing countries have internet access vs. 80% in developed economies.
  27. [27] AI Middle Way Coalition. "Eight-Tiered Macroeconomic Financing Architecture: Six-Nation Coordinated Deployment Analysis." January 2026. Individual approach: $4.698B; Coordinated approach: $5.506B; Efficiency gain: +$808M (17.2% leverage).
  28. [28] Procurement scale efficiencies estimated from UN Procurement Division benchmarks and World Bank multi-country infrastructure project data. Satellite reduced-rate agreements modeled on SpaceX/Starlink government partnership terms and ITU broadband satellite deployment frameworks.
  29. [29] Carnegie Endowment for International Peace. Matt Sheehan, "The Transpacific Experiment" (2019) and "Reverse Engineering Chinese AI Governance" series (2023–2025). Semiconductor decoupling cost estimates from CHIPS Act analysis and Semiconductor Industry Association data.
  30. [30] Center for Global Development. "Three Reasons Why AI May Widen Global Inequality." 2024. Network Readiness Index. "AI in the Global South: Will AI Advancement Deepen Digital Divides?" Prof. Daron Acemoglu (MIT) on capital-intensive vs. labor-complementary AI development. cgdev.org; networkreadinessindex.org
  31. [31] Deloitte and Brookfield projections. Inference made up 50% of AI compute in 2025, rising to two-thirds in 2026 and 75% by 2030. JLL confirms shift expected by 2027. jll.com
  32. [32] AI Middle Way Coalition. Founded at Chulalongkorn University, Bangkok, Thailand. Bangkok Declaration signing: April 21, 2026. Co-led by Professor Soraj Hongladarom and Craig Warren Smith, Digital Divide Institute. www.middleway.ai