Thank the productivity paradox: AI isn’t the job killer it’s feared to be

As energy-efficient technologies emerge, individuals and businesses are motivated by reduced costs to increase consumption.
As energy-efficient technologies emerge, individuals and businesses are motivated by reduced costs to increase consumption.


  • AI doomsayers should accept how technology tends to generate more jobs than it threatens. It’s happened before and will likely happen again.

Artificial intelligence (AI) image generators are still struggling with getting human fingers right. They are not taking away human jobs anytime soon. If that does not settle doomsday prophesies, let us discuss it logically. With economic theory and data. Since the mechanical loom, every wave of new technology has created more jobs at higher wages throughout history. However, the fear remained that each such wave would deliver a death blow to human labour. And yet, here we are.

We have been through two such tech-driven unemployment panic cycles recently: outsourcing in the 2000s and automation in the 2010s. The reality: before the onset of covid, the world had more jobs at higher wages than ever in history. This time, it appears we finally have the technology that will take all our jobs and render human workers superfluous: Generative AI. It is seen as a killer meteorite that will wipe out all human jobs. I would argue to the contrary.

The fundamental mistake people repeatedly make is called the Lump Of Labour Fallacy. In the current context, it is the inaccurate notion that there is a fixed amount of work in the economy at any given time, and either machines or people do it. It follows that if machines do it, there will be no work for people. This conclusion doesn’t ring right.

When a process becomes more efficient thanks to technology, productivity grows. It results in lowering of prices for goods and services. We pay less for them as prices fall, leaving us more money to buy more. Demand in the economy increases, which drives innovation, which creates new products, industries and jobs for people, making up for those replaced by automation. The net result is a larger economy, with higher prosperity, more industries, new products and growing employment.

It does not end there. We also get higher wages. At the micro-level, the market sets compensation as a function of the worker’s marginal productivity. A worker in a tech-assisted business is more productive than a worker in a traditional one. The employer will either have to pay the worker more, as he is now more effective, or another employer will—pure capitalism. Technology introduced into any industry typically increases the number of jobs and raises wages.

The outlined phenomenon is Jevon’s Paradox at work, which postulates that as AI systems become more efficient at tasks, they may increase the demand for those tasks, resulting in more consumption of resources. The most quoted example of this paradox is in the energy sector. As energy-efficient technologies emerge, individuals and businesses are motivated by reduced costs to increase consumption. While automation has historically led to job losses in specific sectors, studies suggest it also creates new ones.

The introduction of spreadsheet applications in the 1980s decreased demand for bookkeepers by more than 40%. However, demand for accountants, auditors, financial managers and management analysts increased by a factor of four to one. When efficiency reduces the cost per unit output for a given process, it proportionately increases the demand for resources to meet the increase in overall output.

A 2023 report by McKinsey Global Institute found that automation in Asia could displace 88 million jobs by 2030 but also create 97 million new ones. So it would be job augmentation rather than elimination. A recent study by MIT and IBM concluded that only about 23% of wages paid for tasks involving vision are economically viable for AI automation. In other words, it makes economic sense to replace human labour with AI in under one-fourth of the jobs where vision is critical to work performance.

Now, let’s focus on India, which is no stranger to AI as a concept. We have stories that range from robots guarding Buddha’s relics to Barbarik the warrior robot and even the possibility that Kumbhakarna was some kind of robot. In modern times, we have among the world’s fastest-growing startup ecosystems. The latest Economic Survey states that India has over 100 unicorns (mostly tech-led), contributing significantly to job creation, not erosion. A 2022 study by IBM found that AI-augmented roles increased talent retention by up to 50% in Indian companies. It made human workers more productive, not obsolete.

An IT ministry study observed that digital interventions (including AI) could lead to the redeployment of 40-45 million workers and create 20 million new jobs in India by 2025. The Indeed Report (2023) states that 85% of Indian employers expect AI to create new jobs in the next 1-5 years. And 63% of job-seekers are excited about the potential, with 53% agreeing AI creates more jobs.

As outlined in an EY India report, Gen-AI can potentially add a cumulative $1.2-1.5 trillion to India’s GDP over the next seven years. Nearly 70% of its overall impact should be on business services, financial services, education, retail and healthcare.

AI will not kill us. Just like AI will not ruin society as we know it. Just like—and this is my personal favourite—AI will not make bad people do bad things. AI will not take away all our jobs in the foreseeable future.

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