The world five years from now

01The back office, department by department

And the price of all of it falls. The main paid AI plans cost about $20 a month today. The cost of the same level of AI capability has been dropping about 10x a year, a trend Andreessen Horowitz calls "LLMflation". All the AI you need to run a business will probably cost about what you pay for your phone.

So who's left? People for judgement and vision: at the top, and at department-head level. Very few roles below them.

02This isn't far off: the numbers today

• McKinsey estimates that current generative AI could automate work activities that take up 60 to 70% of employees' time.
• The IMF estimates that almost 40% of jobs worldwide are exposed to AI, and about 60% in advanced economies.
• Goldman Sachs estimates AI could expose the equivalent of 300 million full-time jobs to automation.

Those are today's estimates, made with today's AI. I think they're low.

03Two ways this goes

Here's the sequence we have to get right. It splits into two streams, and which one we get depends on one thing: whether governments are ready.

Stream one: the happy ending

AI makes productivity insanely high. Then the layoffs avalanche begins. Strangely, GDP holds steady for a while, because the machines keep producing.

This is the moment that matters. Governments have the cash handouts ready. The avalanche hits, and the government drops money straight into everyone's account.

Demand slows. GDP goes down. Then deflation begins, in a big way: when AI does the work, everything costs a fraction of what it did.

And here's the twist. The money in everyone's account isn't much. With deflation, it's actually plenty. People start buying again. Demand picks up. The economy rebalances, and demand and GDP grow briskly, even though most of the world is quite jobless.

A world that runs, grows and looks after people, without needing most of them to work for it. That's the happy ending, and it's within reach.

Stream two: governments aren't ready

Same start. Productivity soars, the layoffs avalanche begins, and GDP looks fine for a while. But there's no cash ready.

People are broke. Demand crashes. GDP crumbles. Tax revenues are gone. Businesses are gone. A terrible economic crisis, and it's hard to see how we'd recover from it anytime soon.

The tools already exist

When demand collapsed in the Great Depression, US unemployment reached about 25% in 1933. That's stream two in miniature. But we also know how to drop money into accounts fast. In 2020 the US sent most households up to $1,200 per adult within weeks of the shutdowns. Alaska has paid every resident a yearly dividend since 1982. When Finland paid 2,000 unemployed people about $600 a month for two years with no conditions, they were less stressed and reported better wellbeing. The only question is whether governments have it ready before the avalanche, not after.

04What you need to be ready

Adaptability. The tools you learn will be replaced. One simple tool that anyone can use to do everything will be commonplace. Your job may become AI's job. What remains is what AI can't sign for.

The world five years from now won't reward knowing a tool. It will reward knowing what to build, who to build it with, and when to say no.

05The short version

• Within five years, AI does the back office of a business, for about the price of a phone plan.
• Today's estimates: 60 to 70% of work time automatable, 40% of jobs exposed, 300 million jobs' worth of work.
• Stream one, the happy ending: the cash is ready, deflation turns a small payment into plenty, and the economy grows briskly with most of the world jobless.
• Stream two: no cash ready, demand crashes, and everything goes with it.
• What to be ready with: adaptability, plus what AI can't sign for: ideas, vision, judgement, taste, partnerships, trust and accountability.

06Sources

• Appenzeller, G. (2024). Welcome to LLMflation: LLM inference cost is going down fast. Andreessen Horowitz.
• McKinsey Global Institute (2023). The economic potential of generative AI: The next productivity frontier.
• Georgieva, K. (2024). AI will transform the global economy. Let's make sure it benefits humanity. IMF Blog, 14 January 2024.
• Briggs, J. and Kodnani, D. (2023). The potentially large effects of artificial intelligence on economic growth. Goldman Sachs Global Economics Analyst.
• US Bureau of Labor Statistics. Historical unemployment estimates for 1929 to 1939.
• US Department of the Treasury (2020). Economic Impact Payments under the CARES Act.
• Alaska Department of Revenue. Permanent Fund Dividend Division: history of the dividend.
• Kela (2020). Results of Finland's basic income experiment 2017–2018.

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