Land, Technology, and AI: Who Owns the Future Economy?

For thousands of years, land meant power. Whoever controlled fertile fields, water, and resources controlled wealth. Kings, empires, and colonial powers rose on the back of territory.

Today, technology has displaced land as the main driver of economic dominance. Google, Apple, and Microsoft have more global influence than many land rich nations. Yet, climate change, resource scarcity, and food security are pushing land back into focus.

So which will matter more by 2040: technology, or land?

❓ Will technology always evolve, or will land become more powerful again?

• Technology Compounds Exponentially: AI is improving faster than Moore’s Law predicted. Training compute for large models has grown 300,000x since 2012 (OpenAI).

• Land & Resources Are Finite: Arable land has shrunk by one-third globally in the last 40 years (FAO). By 2050, the world needs 50% more food with 20% less farmland.

• Energy Transition Shifts Value Back to Land: 1,500 solar panels per hour are installed worldwide (IEA 2024). Access to land for renewables will be as strategic as oil fields once were.

👉 Conclusion: Technology will continue to evolve, but land will not be dethroned. Instead, the fusion of AI + land (precision agriculture, renewable grids, mineral mining for chips) will define power.

❓ Big picture economic prediction

By 2040, global economic power will likely consolidate around:

1. AI Infrastructure (compute, chips, data).

   
   

   • AI chips are projected to be a $400B+ market by 2030 (McKinsey).

   • NVIDIA alone already controls 80% of AI GPU market share (2025).

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3. Energy + Compute Integration.

   
   

   • Data centers are projected to consume 8% of global electricity by 2030.

   • Whoever controls renewable energy land will control the AI grid.

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5. Biotech & Health.

   
   

   • Longevity biotech projected to be a $600B market by 2040.

   • AI driven drug discovery cuts costs from $2.6B per drug to under $500M (Insilico, DeepMind).

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7. Food Security.

   
   

   • Global food demand will grow 56% by 2050 (World Resources Institute).

   • Agri-tech + robotics projected to be a $1T+ industry by 2040.

   
   

👉 Prediction: The most powerful companies will fuse digital dominance with physical resource control.

❓ What companies will be the best in that timeframe?

• NVIDIA (or its successor) → “The AI utility,” leasing compute like electricity.

• Microsoft, Google, Amazon → Still dominant, owning global cloud & AI ecosystems.

• Saudi Humain, Chinese State AI Firms → State-backed titans combining sovereign wealth with AI.

• Agri-AI Firms (Proveye, Niqo, FarmWise) → Precision agriculture + robotics = global food monopolies.

• Biotech AI Giants (DeepMind Health, startups) → Drug discovery, longevity, telemedicine, monitoring and genetic engineering.

👉 By 2040, expect companies with 10,000–50,000 employees but trillions in market cap — massive scale with minimal staff.

❓ With AI advancing, will these companies have fewer people working there?

Yes. AI scales without labour.

• In the 1960s, GM employed 600,000 workers at peak.

• Today, Apple employs 160,000 but generates 3x GM’s peak revenue.

• AI will accelerate this: Goldman Sachs estimates 300M full time jobs could be automated globally by 2030.

👉 By 2040, the world’s biggest companies may look like digital empires with skeleton crews.

❓ What year will big tech companies have very few employees?

• 2030 → First wave of reductions: coders, analysts, customer service automated.

• 2035 → Middle management, finance, legal, even creative roles shrink drastically.

• 2040 → Companies stabilise with lean workforces. Imagine trillion-dollar firms with fewer than 25,000 staff.

❓ What new companies might emerge as leaders?

• Edge AI Pioneers (Axelera AI, startups) → On-device AI brains for robotics, vehicles, IoT.

• Synthetic Biology Firms → Engineering food, medicine, and materials.

• Climate-Tech Giants → Controlling carbon capture, geoengineering, and water purification.

• Compute Sovereignty Startups → Offering decentralised AI chips and cloud to reduce dependency on megacorps.

❓ Will inequality rise if this is the occasion?

Almost certainly.

• Today, the richest 1% own nearly 50% of global wealth (Oxfam).

• AI-driven productivity could add $15.7T to the global economy by 2030 (PwC). But without redistribution, most gains will flow to shareholders and governments, not workers.

• By 2040, the wealth gap could look like two species of humanity:

  
  

  • Elites living with AI-enhanced lifespans, private data companions, space access.

  • Average people scraping by with AI-supplemented incomes in digital economies.

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What role will the service economy play in this transition?

The service economy currently accounts for over 65% of global GDP and employs more than 50% of the workforce worldwide. But AI and automation are transforming services:

• Customer support, finance, marketing, logistics, and even healthcare advisory roles are increasingly automated.

• The service sector may shrink relative to AI-driven production and resource management industries.

• New service niches will emerge—creative, community-focused, and tech-augmented—but the total workforce may be smaller, with higher specialization.

The service economy will be a key indicator of economic adaptation: if it shrinks without alternative employment or redistribution, inequality worsens. If it evolves alongside AI and grassroots innovation, it could support broader prosperity.

🌍 Grassroots Economics: The Counterbalance

If left unchecked, we face “AI feudalism” — digital empires ruling over dependent populations.

But grassroots economics could change the trajectory:

• Community Energy Cooperatives → Local solar/wind powering AI systems.

• Open-Source AI → Hugging Face, Stability, Mistral as commons-driven alternatives.

• Regenerative Agriculture Networks → Shared infrastructure, drones, sensors, and soil data to optimise land.

• Digital Mutual Aid Platforms → Communities pooling AI compute and skills.

• Community Wealth Funds → Cities and nations owning shares in AI infrastructure, redistributing profits.

👉 These bottom-up strategies could ensure AI benefits flow to many, not just a few.

🎯 Final Thought

Technology will continue to evolve, but land will never lose its strategic importance. By 2040, economic power will belong to those who control both compute and resources.

The path ahead has two forks:

• 🚨 Concentration: A world of mega AI firms, extreme inequality, and digital feudalism.

• 🌱 Commons: A world where open AI, grassroots economics, and public ownership create broad abundance.

Which future we get depends not only on technology but on how societies choose to govern, share, and organise around it.