The Two Economies
The industrial economy is dying and the digital economy is booming — they coexist, widening the split
Daniel Priestley's synthesis of the current economic picture distinguishes two coexisting economies that are not transitioning into each other but diverging in parallel. Economy 1 is the industrial economy: office jobs, factory jobs, middle management, high-street retail — the structures built around the Industrial Revolution. This economy is being automated, offshored, or commoditised. Economy 2 is the digital and entrepreneurial economy: technology, media, software, professional services, AI infrastructure. The pandemic accelerated digital adoption by years, compressing a slow transition into a sharp discontinuity.
The split explains a paradox: macro data can show positive GDP while workers in the physical/service economy face the worst housing affordability in decades, highest energy prices in the Western world, and real wage stagnation. Workers connected to the digital economy are doing well or fine. Workers in the physical economy are facing compounding structural headwinds that are not cyclical — they are the permanent obsolescence of their economic category.
Technology's effect on jobs operates in three stages: first, it makes the job simpler and therefore more replaceable; second, it makes the job location-independent and therefore globally arbitrageable at lower cost; third, it automates the job entirely. Most industrial-economy roles are somewhere in this pipeline. The implication for individuals is clear — position in the digital economy before the pipeline reaches your role.
- Two distinct economies now coexist in the same country — the declining industrial economy and the growing digital economy — and they are diverging, not merging.
- Technology affects jobs in three sequential stages: simplification (more replaceable), globalisation (cheaper alternatives available), then automation (full displacement). Know which stage your role or sector is at.
- S&P 500 composition has shifted from 75% physical assets (1970s) to 95% intangible assets today — the entire value creation system has migrated to digital.
- Individual positioning strategy should prioritise adjacency to the largest concentrations of capital — in 2025, this means US tech, AI, and digital markets.
- Self-made wealth dominates ultra-high-net-worth demographics globally (65% of UHNWIs) — the digital economy creates more millionaires via entrepreneurship than the industrial economy did.
- Classify your current position in the two-economy frameworkHonestly assess whether your income, career, and business are in the industrial or digital economy. Industrial markers: physical location dependency, mass-employment role, commodity product/service, exposure to offshoring. Digital markers: location-independent income, scalable without proportional headcount growth, software or media-based product.Pro tipThe test is whether a remote worker in the Philippines or Vietnam could do your job at 30% of the cost — if yes, you are in the industrial economy regardless of your industry label.
- Identify where the largest capital concentrations are formingThe digital economy is not evenly distributed — it concentrates around AI infrastructure, US tech, software platforms, and data. Map where the money is flowing at the macro level (S&P 500 intangible asset composition, VC deployment data, government tech investment by country) and position toward those concentrations.Pro tipDaniel's heuristic: 'stand next to the biggest piles of money you can find.' In 2025, the US and China are actively pulling AI companies inside their borders — Europe and UK are not. Location of digital-economy participation matters.WarningDo not confuse tech consumption with tech creation — working for a tech company in a non-technical role is not the same as digital-economy positioning.
- Assess which stage of the technology pipeline your sector is atDetermine whether your sector is at stage 1 (simplification — job is easier, more replaceable), stage 2 (globalisation — job can be done remotely from low-cost locations), or stage 3 (automation — AI or robotics is replacing the role entirely). The timeline for stage 3 varies by sector but the direction is consistent.Pro tipGary Stevenson's career is cited as an example of stage 3 already reached — short-term interest rate trading is now done by AI robots. The framework predicted this before it happened.
- Build or join a digital-economy business with geographic mobilityThe self-reinforcing property of the two-economy split means that being in the digital economy is also a hedge against national-level economic deterioration. A digital business can relocate with a board resolution. An industrial-economy worker cannot. Prioritise business models and income sources that are jurisdiction-agnostic.Pro tip120,000 British people now live in Dubai. The mobility option is increasingly exercised — being positioned in the digital economy means you have it.WarningDo not interpret this as advice to exit all physical-economy exposure immediately — it is a direction of travel framework, not a liquidation trigger.
During the pandemic, the Magnificent 7 (Apple, Microsoft, Google, Amazon, Meta, Tesla, Nvidia) went from $5T to $17T in combined market capitalisation. Physical retail, hospitality, and services contracted. The divergence was not cyclical — it was the acceleration of a structural shift that had already been underway.
After lockdowns ended, UK employers discovered they could hire equivalent talent from the Philippines, India, and Vietnam at 30% of UK cost for roles that had become location-independent. This was not outsourcing in the traditional sense — it was the full globalisation of stage-2 industrial jobs enabled by digital infrastructure.
Daniel Priestley draws this framework from his experience running seven companies across education, software, and agency services over 20+ years, observing how the pandemic restructured which businesses thrived and which collapsed. The framing crystallises into a Two Economies model because the aggregate statistics mask the divergence — GDP, employment rates, and even productivity figures can look benign while the industrial economy components are in structural decline. The Magnificent 7 statistic ($5T to $17T during the pandemic) is his empirical anchor — the same data Gary uses to illustrate extraction, Daniel uses to illustrate where value creation has definitively moved.