🤯 The terrible truth is that AI will cause more massive job loss than either the agricultural revolution or the industrial revolution, both of which changed the world.
Here’s the worst part: the agricultural revolution took 10 thousand years to spread around the world; the industrial revolution took 150 years. AI will turn the world upside down in single digits, leaving us little time to retrain and adapt.
Speed is the enemy.
Society doesn’t struggle with change as much as it struggles with the rate of change relative to how fast institutions, skills, and norms can adjust.
The agricultural revolution unfolded over roughly 10,000 years as farming techniques spread region by region, limited by geography, trade routes, and slow cultural transmission.
The industrial revolution took about 150 years, accelerated by steam power, rail, and telegraphy, but still bottlenecked by physical infrastructure (building factories, laying track, training workforces by hand).
AI, by contrast, is software. A model improvement or capability jump can spread globally via the internet in days or weeks, not decades. There’s no need to build factories or lay track. Just deploy an API or download an update.
Previous revolutions were largely confined to specific sectors first (agriculture: farming; industrial: manufacturing) before slowly spreading into adjacent industries. AI’s argument for exceptionalism is that it’s a general-purpose technology from day one, capable of touching law, coding, customer service, design, medicine, and logistics simultaneously, rather than sequentially. That parallel rollout compounds the speed problem.
Human retraining (new degrees, apprenticeships, career pivots) operates on a timescale of years. If AI capability jumps happen on a timescale of months, the retraining pipeline structurally cannot keep pace, unlike previous revolutions, where multi-generational timelines allowed labor markets, education systems, and social safety nets to co-evolve with the technology.
Agricultural and industrial change spread unevenly. Some regions industrialized decades or centuries after others, giving late adopters a preview and time to prepare policy responses. Cloud-based AI has no such lag; a capability available in one country is often available everywhere at once.
AI handles information-heavy work, while robots handle physical work, so together they can cover both “office” and “hands-on” labor. That combination matters because it expands automation from routine computer tasks into warehouses, factories, driving, inspection, delivery, and some service jobs.
The realistic ceiling is usually highest for jobs made up mostly of predictable tasks, not whole professions. Studies and reporting point to invoice processing, inventory management, some programming, basic customer outreach, and certain factory or logistics tasks as especially exposed, while judgment, care, negotiation, and leadership are much harder to automate.
Clerical/admin work
The vulnerability: Repetitive digital tasks are easy for software to do.
Likely limit: Humans still handle exceptions and coordination.
Warehousing and logistics
The vulnerability: Robots can move, sort, and pick items, while AI optimizes routes and demand.
Likely limit: Messy environments and edge cases remain difficult.
Driving and delivery
The vulnerability: AI can plan, and robots can operate vehicles or delivery systems.
Likely limit: Safety, regulation, and unpredictable roads slow full replacement.
Manufacturing
The vulnerability: Robots excel at repeatable assembly and inspection.
Likely limit: Flexible, custom, or high-mix production is harder.
Customer support and sales
The vulnerability: AI can handle scripts, triage, and outreach.
Likely limit: Complex persuasion and emotional situations still need people.
Jobs that rely on trust, responsibility, and messy human interaction are much harder to fully replace. Reporting on AI and robotics specifically notes that leadership and communication are among the least automatable skill areas, and even highly automated fields like medicine still tend to keep humans in the final decision loop.
1. Don’t read about it, do it.
The single highest-leverage thing you can do is use AI tools directly in your actual work, not read about them. Someone who’s spent 100 hours prompting, iterating, and finding failure modes has a real skill; someone who’s read 10 articles about AI does not. This applies regardless of your field: writing, coding, analysis, design, or sales.
⭐️(That was just one of eight. The other seven are below. 👇👇)
Comments
Nothing yet. Say the first thing.
Sign in to join the conversation.