TCS’ job cuts may not be about AI, but its fallout across sectors is visible

TCS CEO K Krithivasan

K Krithivasan, CEO and MD of TCS, told Moneycontrol that his company’s decision to shed about 12,000 jobs, or about 2% of its global workforce, is unrelated to AI induced efficiency gains. However, popular interpretation of the move tilts towards labour displacement on account of AI.

Labour displacement because of AI has been a subject of extensive global research. Yet, in India, when there’s a significant layoff in a blue chip IT firm, a constituent of the most widely tracked equity indices, it still comes across as an unsettling event.

It’s important to first contextualise what’s happened at TCS. It’s easy to dismiss it by pointing to India’s overall workforce size, around 565 million people, and juxtaposing it with the loss of a mere 12,000 jobs. It’s not the scale of job loss that’s of paramount importance. Rather, it’s the message that’s rippling out. A sector that recruited skilled employees and where the median pay remains relatively high is very vulnerable to a tectonic technological shift we are living through.

AI is one of the technologies undergirding Industry 4.0, or the fourth industrial revolution. The other technological pillars of Industry 4.0 are the Internet of Things, cloud computing, edge computing and machine learning.

The takeaways from the first three industrial revolutions provide us an idea of what’s likely coming our way in the near future.

Mark Carney, in his earlier avatar as the governor of the Bank of England, distilled the lessons of the preceding industrial revolutions. He classified them in the following manner:

# First industrial revolution (1760-1840) saw the mechanisation of industry along with the introduction of steam power.

# Second industrial revolution (1860-1914) witnessed the introduction of electricity to manufacturing and assembly lines.

# Third industrial revolution (1970-2000) saw the move from analog to digital and the widespread use of electronics.

The fourth industrial revolution that we are living through has seen the advent of machines mimicking cognitive functions that were thus far unique to humans.

A framework to understand the implications of as complex a process as an industrial revolution requires us to categorise its fallout into three phases.

Destruction effect is the early stage when labour is displaced by technology, and there a knock-on effect on incomes and employment.

Productivity effect comes with a lag when the technological transformation makes those in the workforce more productive and is usually accompanied by a rising share of income.

Creativity effect is the long-term effect of a technological transformation and jobs which don’t exist in the first two stages are created. For example, the growth in the service sector in most economies could have come about only after technological changes transformed manufacturing.

There’s no compelling reason to believe that this time it’s different as far as the three stages are concerned. However, timelines are another matter because the speed of technological diffusion need not be the same across each industrial revolution.

That said, there’s reason to believe that Industry 4.0 may see a compression in timelines. Recently, World Economic Forum’s ‘Future of Jobs Report 2025 made a couple of important points.

# Most employers expect broadening digital access to be the most transformational force over the next five years.

# Within that framework, it is AI and information processing technologies that are expected to have the greatest impact.

Separately, an IMF study concluded almost 40% of global employment is exposed to AI. Moreover, AI displacement risks extend to higher wage earners.

The direction in which research on AI’s effects is going suggest that the TCS incident is probably a precursor of things to come as the company has attributed layoffs to skill gaps and limited redeployment opportunities. It’s destruction effect which is the initial phase of an industrial revolution.

From within the technology industry, the forecasts can at times be bleak. A few months ago, Dario Amodei, CEO of Anthropic, forecast that AI could wipe out half of all entry-level white collar jobs.

The advent of GenAI has made white collar workers more vulnerable than blue collar workers, an inversion of the traditional cycle.

For sure, AI and machine learning will add hugely to global economic output over time. But the winners and losers among workforce may not be easy to gauge.

Historian Yuval Noah Harari hit the nail on the head last year when he said: “AI that we are familiar with today in 2024 is just a very, very primitive first step of the AI revolution. We haven’t seen anything yet.”