Artificial intelligence transforms industry and automates tasks that once required human labor. World Economic Forum Future Jobs Report 2025 By 2030, AI will expel 92 million people, creating 170 million new jobs, and 78 million jobs.
At first glance, these numbers seem encouraging. But the real problem is not the total number of jobs –That’s the timing. AI is poised to eliminate jobs much faster than new roles emerge, and that delay could drive a wave of unemployment before the labor market stabilizes.
The reason lies in the structure of the work. Today, in many industries, AI automates human tasks within current working systems. New employment only comes after the company rethinks and restructures its work on its own. This is a process that is generally delayed due to structural friction, tissue inertia and lack of skills. As a result, millions of workers could face long-term unemployment while the organization works to adapt.
The time taken to this transition depends on two important factors. It’s how quickly an organization can restructure its work for an AI-driven economy and whether it has the skills to step into the role that will ultimately emerge. Right now neither is happening fast enough. This should be a wake-up call to prevent massive skills gaps and the resulting unemployment.
Fast change in AI that replaces tasks
Automation of job exchange is nothing new. The mechanization of agriculture, the rise of assembly lines, and the emergence of computers all evacuated many workers at various points in history. However, past technological changes have allowed for staged adaptation, and the system of work has changed in tandem. The Industrial Revolution took place for decades. The digital revolution has given workers time to acquire new skills. In contrast, AI is progressing at an unprecedented rate.
Automating cognitive tasks into AI is particularly disruptive. Unlike past waves of mechanization that primarily affected physical labor, AI is now replacing white-collar workers, who are customer service representatives, legal researchers, financial analysts and even entry-level programmers. Goldman Sachs Globally, AI predicts that it could expose 300 million full-time jobs to automation in the coming years. While some occupations may not disappear completely, AI reduces the need for human input and reduces the availability of jobs.
Importantly, AI does not disrupt industry in a predictable and linear way. Some sectors, such as customer service and data entry, see immediate and large displacements. Others such as law and healthcare can experience slower and more gradual automation. However, if AI is skilled in each field, unemployment can be quick.
Stay in a legal industry. AI-powered contract review software can process thousands of documents in seconds, reducing the need for junior lawyers. In customer service, AI chatbots handle millions of interactions each day, eliminating the need for human agents in call centers. The retail division has already seen massive layoffs with self-checkout systems and warehouse automation. Additionally, knowledge-based occupations are not immune to being immune to generating AI tools like CHATGPT infiltrating content creation, translation and even marketing.
Slow speed of change in work systems and workers’ skills
In general, using new technology on older work systems means that new technology produces fewer jobs than the first ones they replace. When AI is deployed in older work systems, it automates existing tasks, such as call centers that replace human agents with chatbots, but does not change the structure of the work. However, when AI completely redesigns the system and eliminates the need for traditional workflows, real confusion arises. Instead of waiting for customers to make a call, AI-powered predictive analytics can detect and resolve issues before they occur, integrate services directly into the product, completely eliminating the need for a call center.
New jobs will eventually emerge, such as AI trainers and user experience designers, but this transformation is much slower than the move of work, creating painful delays that leave workers without immediate options. Many of the roles AI creates require advanced technical skills such as data annotation, AI model supervision, human collaboration management, and industry-specific digital ency.
Even in a technology-rich industry, AI-driven employment growth is limited. AI could create new forms of employment, such as AI auditors and AI ethics consultants, but these roles require specialized knowledge and are far fewer than jobs that are excluded. Today, even workers with cutting-edge technical expertise cannot afford to be complacent. both IBM and Boston Consulting Group We estimate that some technical IT skills have a half-life of less than three years. This means that the expertise in demand today can become outdated before the ink dries with certification. In this environment, lifelong learning is no longer an ambitious ideal. It’s a career survival strategy.
Transition delay results
This gap between displacement and job creation is where there is a real problem. Governments and businesses often assume that if new jobs finally emerge, they can manage short-term unemployment rates. However, history suggests that this is not the case. For example, the rise of cars left blacksmiths and carriers out of business, but the automotive industry ultimately produced millions of jobs. The Internet has expelled thousands of print media jobs, leading to a boom in digital marketing, e-commerce and software development. These transitions have been positive employment growth, but they still took decades.
As many workers struggle to make a quick transition, we predict that long-term discrepancies between job displacement and job creation are likely to lead to a short-term surge in unemployment. It is also likely that income inequality will increase as high-paying AI-related employment concentrates among highly educated individuals and low-skilled workers face lower wages.
Periods of economic transition have always been characterized by social and economic upheavals. The decline of coal mines in the United States, manufacturing outsourcing and automation of assembly lines have led to a wave of unemployment, a regional economic collapse, and an increase in populist politics. AI can cause similar confusion, but at a faster pace on a global scale. Wake-up calls and actions are required to prevent the potential consequences of this transition.
The opinions expressed in the commentary on Fortune.com are the views of their authors and do not necessarily reflect the opinions and beliefs of good fortune.
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This story was originally featured on Fortune.com.
