Others will somehow manage!!

Earlier this week, I was reading the never-ending article from Citrini Research on how AI might trigger the Doomsday soon.

I would admit, it isn’t that I completely disagree with what they wrote in ~7000 words essay, but most of it got me thinking.

And then I placed myself, and also stepped into the shoes of my close friends, my relatives, to see who is getting impacted by how much.

Below is my agreement and disagreement with that article.

The “Safe” Path is Disappearing

I was recently talking to a friend who has spent 15 years in tech. He’s 38, has a young family, and has always been the “high achiever.” Few months back, his role was cut. Not because he wasn’t good, but because his company realized that an AI agent could do the heavy lifting of his architectural reviews for next to nothing.

He told me something that hit home: “I did everything by the book, but the book just got rewritten.”

If you’re in that 35-45 age bracket, which I will call the “sandwich generation”, you’re likely feeling this. You have aging parents to look after and kids to raise, but the corporate safety net is fraying.

We’ve seen nearly a million tech jobs vanish in the last few years. This isn’t just a “bad cycle”; it’s a fundamental shift in how the world values “brain work” versus “physical work.”

The “Average” Trap and the New Competition

We’ve always believed that if we upskill, we’re safe. But the speed of tech today is brutal. If you’re ~40, “just learning a new skill” or “getting a new certification” isn’t easy when you have a mortgage and small kids.

The reality is that for a lot of white-collar roles like mid-level managers, content creators, software testers, entry-level analysts – AI isn’t just a tool; it’s a replacement.

Why would a company pay for 2 hours of human work when they can get it done in 5 minutes by a machine? Anthropic is the most recent example.

The result? The “middle-tier” is being hollowed out. You’re either the brilliant strategist who knows how to run the AI, or you’re replaced by it. There is very little room left for the “average” office worker.

The “Consumption Paradox”: Who buys the products?

Here is the part that many people miss, and it’s a massive logical flaw in the current AI race. Companies are racing to replace humans to save costs. But if everyone is laid off, who is going to buy what these companies are selling?

• Robots don’t buy things: An AI doesn’t need a home loan, a car, or even a pack of diapers for its kids.
• The Velocity of Money: In a normal economy, I earn, I spend, and that money keeps moving. If all the profit goes to a few tech giants and the “consuming class” (people like you and me) loses its income, the whole system stalls.

If people aren’t earning, they aren’t paying GST or income tax. How is the government going to build the roads and power plants that these very AI data centers need to run? We’re heading toward a world of “Infinite Supply” but “Zero Demand.” That’s a recipe for a depression, not a boom.

Is Blue-Collar the new Gold-Collar?

While white-collar jobs are under fire, something interesting is happening in the physical world.

AI is great at “thinking,” but it’s terrible at “doing.” It can write a legal brief, but it can’t fix a short circuit in your house or install a precision HVAC system in a factory (just yet).

In India, we’re seeing a “Status Swap.” A specialized EV mechanic, a precision welder or (the best case) a miner, is starting to have more job security than a mid-level digital marketer or an entry level investment banker who previously devoted a lot of time to make presentations.

The “Hybrid” Professional: The big winners in the next decade won’t just be manual laborers. They will be the people who use AI to diagnose a problem but have the manual skill to actually fix it. If you can bridge the gap between “Code” and “Copper,” you’re un-fireable.

What about our kids? (The Grade 10 Dilemma)

I get asked this a lot: “My kid is in 10th grade and wants to study Computer Science. Should I stop them and encourage to move them to say Civil or Metallury Engineering?”

My answer: Don’t stop them, but change their focus.

• CS is the new English: You need to know it to talk to the world. But “being a coder” is no longer a career; it’s a basic skill.
• Add a “Physical” Moat: Encourage your kids to learn things that require fine motor skills or physical presence. Robotics, drone repair, specialized healthcare, or precision engineering.
• The Goal: They should be the person who can design the solution with AI, but also be the only one in the room who knows how to pick up a wrench and build it.

Why I Say That Others Can Manage Who Aren’t In 35-45 Years Bracket?

Let’s categorize people into 5 buckets as per age:

• Below 22 years: These are still students, either in school or in college, where most likely they will be studying the latest skills. Even if college wouldn’t have updated the curriculum, their ever upgrading surroundings will make them flexible right from their early days.
• 23 to 28 years: These will most likely be freshers, early in their jobs. Even if they aren’t in relevant futuristic jobs, and might be subject to layoff soon, they can easily upskill, do a post graduate course, etc. They might not have huge liabilities also.
• 29 to 35 years: They might be the recently married ones, and may be with none or one kid. Their parent might still be working (not retired yet) so the pressure isn’t too much from dependants point of view.
• 35 to 45 years: The entire article apart from this section is focusing on this bracket only.
• 45 years and beyond: With over 20 years in corporate, I am assuming these guys have invested enough to sustain themselves for many years to come. Also, these guys may serve as better consultants in managing humans or giving strategic advise. If someone is 60 years and beyond, and might not have enough savings left, at least they can depend on their 20s something kids to help them survive (we are talking about survival in this article, hence this argument is valid).

The Rise of the “Handshake Economy”

Last few years, we have seen a cumulative 1 million+ people being laid off from thei tech roles. Few of them must be in the age bracket of 35 to 40. What are they going to do next? They have been doing the same job, without upskilling themselves, for over a decade. And now, who is going to hire a middle aged person at a higher cost?

Most good guys who have been laid off are becoming “consultants,”. But can everyone do so? If 1,000 people do the same thing, it’s just a race to the bottom on price.

The only way to win in a world full of AI content is Authority and Trust.

AI can’t fake a 15-year reputation.

AI can’t give a “human handshake” or take accountability if things go wrong.

Whether you’re in finance, tech, or content, you have to move away from being a “worker” and start being an “authority.” People will pay a premium for a human they trust, especially when the internet is flooded with “perfect” but soul-less AI noise.

Why this isn’t a Doomsday (The “New Windows” of 2026)

So now, let’s also look at the other scenario, which according to me is the more plausible one.

It’s easy to get depressed by the layoffs, but history tells us that whenever “old” work gets automated, we find 10x more “new” work.

1. The Spreadsheet Lesson: When digital spreadsheets came out in the 80s, people thought accountants were finished. Instead, we have more accountants than ever. Why? Because it became so cheap to analyze data that every small business wanted it. AI is doing the same for high-end strategy. You don’t need to be a billionaire to have a “Family Office” anymore; AI can help a 40-year-old consultant provide that level of service to 50 clients at once, if the 40-year-old is good with his/her work.

2. The Democratization of Expertise: Because AI handles the “grunt work,” the barrier to starting a business has never been lower. You can be a “Company of One” in a tier 2 city and compete with a 100-person agency in Mumbai. AI handles your research, your formatting, and your initial drafts. You provide the Reputation and the Handshake, as described earlier.

3. New Careers we can’t even name yet: We are seeing a boom in “Human-in-the-loop” roles:

• AI Auditors: People who ensure the machine isn’t hallucinating or biased.
• Personalized Care Coaches: AI can track your health data, but it can’t sit with you and help you through a mid-life crisis.
• Hyper-local Logistics: As people move to Tier 2 cities, the demand for “Physical Delivery and Maintenance” in those towns is skyrocketing.

The Government’s Role Here

How can the Government help us in all this?

In the latest Feb 1st Budget, we saw a massive push for “Hard Infra” – ₹12.2 lakh crore for highways, data centers, and semiconductor plants. It’s impressive, but is it what we actually need right now?

Think about it: What’s the point of an 8-lane expressway if the middle class doesn’t have the money to buy the cars to drive on it?

We are at a point where the government needs to pivot from Physical Infrastructure to Social Infrastructure. Instead of just building roads, we need “Social Safety Nets” for the displaced:

• The “Transition Tax”: If a company replaces 500 workers with an AI agent, should there be a “Compute Tax” that goes directly into a re-skilling fund for those specific workers?
• Digital ShramSetu: We need systems that don’t just “teach code,” but help a 40-year-old manager transition into high-stakes consulting or technical trades.
• Healthcare as Infra: For someone in a Tier 2 city, a robust, AI-enabled local hospital is worth more than a highway to a city they can no longer afford to live in.

If the government keeps spending on “Concrete and Steel” while the “Human Capital” is being disrupted by AI, they are building a house with no one inside.

Final Thoughts

The world is moving fast. Maybe too fast for many of us to keep up comfortably. But the “Physical World” (commodities, energy, trades, and real-world infrastructure) isn’t going anywhere. While everyone is chasing the “Digital Gold Rush,” the real value is moving back to the things we can touch, fix, and trust.

It’s time to stop trying to out-run the machine and start doing the things the machine will never be able to do.

What do you think? Are you seeing this “White-Collar squeeze” in your industry too? Let’s discuss in the comments.