Why AI is more likely to create jobs than destroy them

Past performance does not predict future returns. You may get back less than you originally invested. Reference to specific securities is not intended as a recommendation to purchase or sell any investment.

This article is featured in the Q1 2026 Future Strategist newsletter, you can read the rest of the newsletter here.

Many white-collar workers feel uneasy right now. The software they once used as tools now acts more like a co-worker, and sometimes even a rival. News stories warn of major job losses across law, finance, consulting, media and technology. It’s no wonder people are anxious. 

But history points to a different result. When something essentially becomes much cheaper, demand usually rises. For over a century, automation has transformed economies, yet jobs and incomes have grown. Jevons Paradox explains why: as things get more efficient and cheaper, we use more, not less. AI, by lowering the cost of intelligence, is poised to create new jobs and industries, just as past technologies have done. 

This pattern has repeated throughout history. From the arrival of textile machines in the 1800s to Ford's assembly line and the spread of computers, each wave of automation made products cheaper and more accessible. Instead of shrinking the workforce, new industries and job categories emerged, and demand for goods and services soared. 

AI operates on the same principle, but at a broader scale. It reduces the cost of drafting, analysing, coding and customer engagement. A small business owner can now design marketing campaigns, build a website and manage customer enquiries without hiring outside specialists. Tasks that once required consultants or agencies can now be done internally at far lower cost. This is Jevons Paradox in real time. When the cost of intelligence falls, its use spreads. Because AI is ultimately software, falling code and deployment costs mean more applications are built, more processes are automated and more intelligence is embedded into everyday business activity. 

When things get cheaper, more people want them. A service that used to be affordable for 10,000 customers can now reach 100,000. Companies respond by doing more business. Even if some tasks are automated, the total workload increases. For example, an accounting firm that can process tax returns faster doesn’t just stick with its current clients – it takes on more small businesses. A radiology practice using AI to review scans more quickly doesn’t close departments; it reads more scans and helps more patients. 

Platforms like Shopify now include AI tools, making it easier for more entrepreneurs to start and grow businesses. As more companies are created, the need for logistics, payments and customer support also grows. The amount of work increases. Early data already show that jobs needing AI skills often pay more in many developed countries. 

Experienced professionals gain leverage from AI, making decisions faster and at scale, whilst their responsibility and judgment become even more valuable. In law, an experienced attorney can use AI to rapidly review thousands of documents and identify relevant cases. But it’s still the lawyer’s expertise that crafts arguments, understands client needs and makes strategic decisions in court. AI does the heavy lifting, but real value comes from human insight and judgement. 

The real story about jobs is growth. When building and launching products becomes cheaper, more people try, leading to new businesses and more jobs. Lower barriers to entrepreneurship and expansion, which fuels job creation across industries. 

The biggest changes will happen in entry-level jobs. Tasks that used to help people learn on the job are now being automated. Junior analysts and developers can’t depend on repetitive work anymore. This shift might feel tough at first, but it changes how people gain experience. For example, a new analyst might use AI to create a first draft, then spend more time checking assumptions and explaining risks. A junior developer might review AI-generated code and fix any problems. The learning process moves from doing the same thing over and over to evaluating and improving. Work gets done faster, but good judgment is still up to people. 

Disruption is nothing new. ATMs, e-commerce and automation all changed the nature of work, but each also opened doors to new industries and roles. Technology transforms the tasks we do, but it never limits our ability to adapt and thrive. 

Some worry AI might replace jobs faster than new ones appear. This risk is real, but history shows that as key inputs get cheaper, new uses and industries arise, usually faster than old jobs disappear. The real question is when will the biggest growth and opportunities emerge. 

AI isn’t some outside force taking over the economy – it is software. Like past software revolutions, it drives efficiencies and unlocks new opportunities for growth. While disruption is inevitable, history shows that automation creates more jobs than it destroys. The challenge ahead is not job losses but adapting to new ways of working and ensuring people are ready to take on new roles. 

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