The Impact of Automation on Jobs

I would like to state upfront that I am not against AI. The article may feel unsettling at points, but I am only trying to present my perspective here, as honestly as I can.

Tech layoffs are escalating daily. Tech giants are rapidly advancing in Artificial Intelligence (AI) race and as a result, more layoffs are anticipated in the near future.

CEOs around the world are pumping hundreds of billions of dollars into AI infrastructure and restructuring their entire organizations around it. This strategic pivot has led to massive layoffs globally — and the numbers are not slowing down.

The Macro Trend: Tracking Global Layoffs

According to data from Trueup.io, 150,096 employees have been laid-off globally in 2026 so far (as of June 7, 2026). This translates to roughly 950 professionals losing their jobs every single day.

Company	Estimated Layoffs
Oracle	~30,000
Amazon	~16,000
Meta	~10,000+
TCS	~8,000

A closer look at the industry giants reveals the systematic nature of these cuts:

• Meta - As reported by Reuters, Meta laid off approximately 8,000 employees in May 2026 alone. This is just the first wave. More rounds are expected to roll out over the next few years. Note that Meta had already fired over 2,000 employees earlier in 2026.
• Oracle - Oracle laid-off around 30,000 employees globally this year. Not only this, but Oracle revoked some placement offers made to students across IITs and other Engineering institutes in India - including full-time roles for graduates and summer internship positions.
• Amazon - Amazon laid-off about 16,000 employees so far in 2026, with more cuts rumored to follow in coming months.
• Tata Consultancy Services (TCS) - TCS reduced its workforce by roughly 8,000 employees around April this year.

I won’t name specific companies, but some companies have also put hiring on a complete freeze - which makes the whole scenario even more precarious.

These laid-off professionals are, almost without exception, highly skilled in their domains. Some have over a decade of experience. We can’t simply expect a generation of software engineers and data architects to transition into manual trades like plumbing to make ends meet.

The Timeline of White-Collar Automation

Now, among all this, Microsoft AI CEO, Mustafa Suleyman gave a statement that is not very comforting -

“So white-collar work, where you’re sitting down at a computer, either being a lawyer or an accountant or a project manager or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months.”

But, where are we heading after so many layoffs? If Mustafa Suleyman is right then over 5 million jobs in India alone are at stake.

Mustafa Suleyman also said that he is working on Super Intelligence (or AGI). And, not just him, other tech giants are also working on the same.

Now, just for a minute, think of it like this - we don’t even yet have a Super Intelligence but still almost all the white-collar jobs are at stake. And when Super Intelligence arrives, what would be the situation?

Honestly, I am not very optimistic about it in terms of employment and living conditions of humans.

Current Situation - Globally

As mentioned above, over 150K jobs have already been eliminated in 2026 and we are barely midway through the year. To put this in context, the entire year of 2025 saw about 245,953 tech layoffs.

The most alarming part? These cuts are coming even from highly profitable companies like Meta, Amazon, Oracle, etc., these are not distressed businesses - these are cash-rich organizations. They are cutting jobs not because they cannot afford people, but because they have decided they no longer need as many of them.

The corporate lexicon calls this “AI-driven restructuring”. But to me, it feels like: AI inherits the production, while humans are handed severance.

Global Research Data on Automation Risks

• McKinsey Global Institute published a comprehensive report titled - ‘Agents, robots, and us: Skill partnerships in the age of AI’. As per this report, current-day technologies possess the theoretical potential to automate approximately 57% of all work hours in the United States.
• Goldman Sachs published a research titled - ‘The Potentially Large Effects of Artificial Intelligence on Economic Growth (Briggs/Kodnani)’. This research projects that generative AI could affect up to 300 million full-time jobs globally, with around two-thirds of current occupations exposed to some degree of AI automation.
• Anthropic’s CEO, Dario Amodei, predicted in 2025 that AI could eliminate roughly 50% of all entry-level white-collar jobs. However, Sam Altman and Dario Amodei are both walking back their AI jobs apocalypse prophecies as their respective firms prepare for high-valuation Initial Public Offerings (IPOs).

The Micro Impact: The Reality in India

Let’s take an example of one of the fastest growing fields - Data Science. This is one of the most touted fields of these days. I was checking on Naukri.com (a job portal in India) and found that some of the job postings have over 20,000 applications and that too within a few days of posting the job post on the platform.

The supply of skilled human labor vastly outstrips corporate demand.

This is the current situation in India. What’s going to happen if Mustafa Suleyman’s statement or prophecies come true?

There’s More To Add For The Current Situation in India

I speak from my personal experience - Candidates, here in India, with a career gap or break are seen as if they have committed some kind of a crime. You are expected to remain employed throughout your life; you can’t take a break. If you take a break then good luck getting a job because you are just not fighting competition, but you are fighting the psychology too.

India’s Position In The AI Value Chain

India missed the AI race, totally. With no foundational AI infrastructure, domestic tech institutions remain primarily consumers and downstream implementers of western-engineered software or AI advancements.

We hardly hear anything related to AI advancements from Indian tech giants like TCS, Infosys, Wipro, etc. Or perhaps, these companies have a totally different perspective and business plan. However, if mere lay-offs are the plan to stay afloat, then their viability will face severe challenges in an era of autonomous software agents and after the arrival of Super Intelligence.

• Most impacted industries in India - Business Process Outsourcing (BPO) and IT Services
• Least impacted Industries in India - Agriculture, and Core Healthcare.

Access To Opportunities

Graduates from Tier-1 institutions at least have the networks and resources to attempt a pivot. But what about graduates from Tier-3 colleges, or those from institutions so small that they don’t even manage to claim any official ranking? Where can they go when the entry-level jobs, the very positions they were hoping to land, are the first ones to be automated?

There is a silver lining that is worth mentioning: smaller companies now have an opportunity. The recently laid-off workforce is extraordinarily skilled, possesses deep domain experience, and many are now willing to work for salaries that match smaller company budgets or salaries lower than they used to get in MNCs. For a startup or an SME, this is a rare window to hire talent that was previously out of reach.

Now, this may sound to be a positive sign or a ray of hope for newly laid-off workforce from MNCs but this raises the competition even higher for graduates from lower-tier college.

Upskilling, Is It Even A Real Option?

There is a standard answer given every time the jobs-versus-AI question comes up - “People need to upskill”.

But, I think this answer deserves more scrutiny than it usually gets.

Consider a Data Science professional, someone who has invested years learning statistics, Excel, Google Sheets, machine learning frameworks, Python, SQL, GA4, and business intelligence suites like Power BI, Tableau, Google Data Studio, etc. These are not trivial skills and yet, a modern LLM/ AI can write the code, execute the regression model, map the visualization, and generate an executive summary in seconds.

Can a human professional truly compete with that speed and scale? Perhaps at the higher strategic and architectural level but what about the large majority who are doing the more routine, operational work?

The Economic Ripple Effects

The damage isn’t just limited to the individuals and their careers. It’s showing up in markets and entire business models as well.

Consider what happened to Chegg, one of the biggest EdTech companies in the United States, valued at nearly $16 billion at its peak in 2021. Within a few months of ChatGPT’s launch in late 2022, Chegg’s paid subscriber base began crumbling. Students simply started using AI for homework as they could do the same thing instantly and for free. Chegg’s stock, which once traded around $113 per share, is today trading around $1 (June 7 2026). An entire business model, built over years, serving millions of students, was rendered obsolete in a matter of months.

Indian equity markets reflect a similar structural anxiety. The NIFTY IT Index has fallen sharply from its high of about 45,995.80 made on December 13 2024 and it traded around 28,690 on June 7, 2026.

Individual Enterprise Valuations Show A Parallel Correction-

• TCS - TCS made a high of 4,553.75 on August 30, 2024, and on June 8, 2026 it traded around 2,149
• Wipro - Wipro made a high of 355.75 on January 7, 2022 and on June 8, 2026 it traded around 181.
• Infosys - Infosys made a high of 1,999.70 on December 13, 2024 and on June 8, 2026 it traded around 1,187.

The Consumption Paradox: The Fatal Flaw of Hyper-Automation

If we fire all the humans and make the AI do all their jobs then who is the consumer here?

If humans have no income, corporations have no market.

Businesses exist because people have money to spend. People have money to spend because they have jobs. If AI displaces millions of white-collar jobs then those people will not simply disappear, they will tighten their belts, reduce spending, step back from urban lifestyles. This shrinks the very economy that the profitable companies depend on.

AI can write code on demand, generate endless marketing campaign ideas and helpful material, audit thousands of tax returns in seconds and can do much more. But, AI can’t buy a car, house, etc. AI may be able to drive very high productivity but consumption is still bound to human income.

White-collar tech professionals are not just employees. They are the premier consumers also. They buy SaaS subscriptions, cars, houses, smart home gadgets, use food delivery apps, etc. By eliminating them, tech companies seem to be inadvertently damaging their own customer base.

When 10,000 employees receive their salaries, that money moves instantly through local economies (groceries, real estate, stock market, local businesses, etc.). When that same capital is retained as corporate profit or paid out to a handful of venture capitalists, it pools stagnantly at the top. This dramatically slows down the velocity of money.

Going Exactly The Opposite Of What History Taught Us

In 1914, Henry Ford introduced a significant shift in labor practices. He announced that Ford Motor Company would double the wages of its workers to $5 a day for an eight-hour workday. His logic was brilliant and not philanthropic. Mr. Ford realized that if his own assembly-line workers couldn’t afford to buy a Model T, mass production would eventually choke on its own supply. He understood that a healthy economy requires a continuous, circular flow of capital.

Today’s tech-driven corporate landscape is running Mr. Ford’s thesis completely in reverse.

Tech giants replaced thousands of human professionals with their autonomous AI systems and considering this as their win. However, they only achieved a short-term operational efficiency. They are ignoring a glaring asymmetry - An AI agent does not participate in the consumer economy. An LLM workflow doesn’t rent an apartment, doesn’t order food delivery, doesn’t upgrade its smartphone, and it certainly doesn’t buy subscriptions to digital platforms.

The white-collar professionals are the very super-consumers who fund the modern digital ecosystem. When they are displaced, you don’t just solve a corporate expense problem; but you are also destroying market demand.

This structural collapse hits developing economies like India even harder. The entire India’s modern middle-class expansion was built on labor arbitrage - skilled professionals working for Western organizations at competitive rates. If a business in California can get their technical tasks done for a fractional of the cost than what they had to pay for outsourcing the talent from India, then the geographical cost advantage of human talent is rendered meaningless.

By automating everything to satisfy short-term quarterly earnings, corporate leadership is actively starving the consumer ecosystem they require to grow further. This is no longer just a technological transition; it is a profound crisis of economic equilibrium. And, the people paying the price for this imbalance are not the stakeholders, they are the highly-skilled professionals watching their careers disappear, one AI development at a time.

Final Thoughts

We are building a hyper-efficient world. Machines will manage the production of goods and services. But, somewhere in this frictionless future, we seem to have forgotten to ask - where do the humans go?

This is simply my honest attempt to look at where things are heading, not just for the early adopters and the investors, but for the millions of ordinary, hard-working people whose livelihoods are being quietly restructured out of existence.

Shouldn’t this conversation be happening louder, sooner, and with far more urgency than it is?

Also, I would love to know where you stand on this. Have you or someone you know been affected by this wave of change? Do you think upskilling is a realistic answer, or is it just a comforting story we keep telling ourselves? Share your thoughts in the comments below, or share this with someone who you think needs to read it. Because the more people are thinking about this, the better our chances of arriving at real answers.

Written as a personal opinion. All statistics and data points are linked to their original sources. The author holds no position for or against any company mentioned.

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Featured image generated using Gemini.