Approaching Horizon: AI and the Coming Economic Re-Ordering

Where We Are

I think it’s not an over-exaggeration to have the view that “Post-ChatGPT’ world is significantly different than most of us thought of how the near term future would look like in 2021. LLMs have broken out of research labs and pulled the entire global economy into a transition far larger than most citizens - or our leaders - can grasp.

Many countries, though starting from very different places, now appear to be converging on similar economic paths. Taking India as an example, the computer and internet booms turned white collar services into the engine of middle-class prosperity, yet manufacturing still falls short of creating enough jobs that pay ₹300,000 – ₹600,000 a year. Meanwhile the very sectors that powered upward mobility - IT services, business-process outsourcing, routine software development are being rapidly automated. Large firms may endure, but with far leaner payrolls; if 40–50 % of office roles disappear, the consumer demand that sustains corporate revenue will shrink in tandem.

In the West the risk is different only in detail, not in scale. The industrial and internet revolutions took decades and mostly shifted labour from one sector to another. By contrast, the AI revolution threatens to commoditized and erase cognitive work at a speed for which societies are profoundly unprepared.

While we may or may not be on path to AGI. The fact that LLMs will result in significantly more automation is pretty much undisputed.

The social contract of - "You do a job for 'X' years, you retire and get benefits", which was already looking like a pipe dream to most millennials, is pretty much dead now. So what comes next? Mass unemployment followed by societal upheaval? Fundamental new jobs/ways of working? UBI? Governments/Militaries once again becoming major employers to support the coming conflicts ?

Pressures on the Economy and Cascade Effects

Uneven Returns to Work - Technology has always stretched the gap between average and exceptional contributors; AI accelerates that divergence. Mediocre programmers struggle to stay employed while world-class specialists command record compensation, and the pattern is repeating in law, design, and finance. The bottom of the pay scale is anchored at zero, but the top now floats higher than ever.

The prevailing corporate wisdom celebrates cost savings from "dark factories" and generative coding assistants, yet overlooks a first principle: a healthy top line depends on customers with disposable income. Wide-scale white-collar redundancy undermines that base, threatening demand for everything from smartphones to urban housing. A sudden realization — say, news that five to ten million Indian office jobs are disappearing annually - could hammer equity markets, real estate, construction, and the materials supply chain in a single feedback loop.

Beyond balance sheets lies growing anxiety and existential dread. If machines can already draft contracts, propose medical regimens, or generate entire client pitches, what remains uniquely human? Is everything we do pointless — documents written by AI, only to be summarized and consumed by another AI, hollowing out the act of communication itself?

Factory workers had decades to adapt to mechanization; today's knowledge workers may have less than five years before their roles are fundamentally altered or eliminated entirely. The fear grows darker when you ask: what is real anymore? Is the new song you loved born of human experience or algorithmic generation? Is the new trending video generated by Veo just to instil a response from you?

Opportunities and a Way Forward

Even optimists concede that large language models alone will not deliver true AGI, and that productivity gains from today's architectures may plateau along with reaching compute ceilings. AI labs are pivoting to more narrowly focused applications, such as software engineering. Yet the next breakthroughs are already gestating in systems that learn from direct interaction with the physical world - the "Era of Experience" — building entirely new capabilities.

Just as the airplane enabled flight, a capability that did not exist before, we must think of AI in terms of what it allows us to do for the first time.

More down to earth, here are a few opportunities that will continue to exist and have growth potential:

• Education, Legal Services, Healthcare — ripe for process-level automation and personalized delivery.
• Robotics and Advanced Manufacturing — oil platforms, deep-sea operations, and military logistics still need rugged, adaptable machines and underwater drones.
• Game Development and Interactive Media — historically labour-intensive projects can shrink from thousands of contributors to small studios.
• Protein and Bio-engineering — AI-accelerated discovery (e.g., regex-style proteome searches) hints at whole new industries.

If you are in high school or your family members are, the above is where your focus should be - beyond computer science.

Micro-Entrepreneurship as a Safety Valve

While large employers shed headcount, AI tools also lower the cost of launching tiny, capability-rich ventures: one-person SaaS products, niche content studios, hyper-local robotics integrators. Competition will be fierce, but the barrier to entry is collapsing.

For adaptable workers, micro-enterprise could provide the fastest path to relevance. I also believe we are entering an era where a small team of software engineers delivers high-impact projects for companies and moves on. The companies can choose different contractors to maintain, or maintain the same software in-house. It might be similar to how teams of contractors build houses, offices, and buildings right now, then move on with specialized sub-contractors.

Software engineering is definitely moving a step below in the economic value pyramid as it's going to be significantly more democratized. Work in engineering has to be pivoted to reflect that.

Long Term

The long-term solution must be bolder. The survival of our economic and social structures may depend on our willingness to pursue endeavors that currently reside in the realm of science fiction. We must think crazily.

The need of the hour is to create entirely new industries, just as the semiconductor industry did not exist before the 1980s and the internet sector was nascent before 1999. Investing heavily in a new space race, asteroid mining, and large-scale bio-research should not be seen as fanciful luxuries but as essential projects for a species whose terrestrial, cognitive labour is being automated into irrelevance.

If a task is brand new and fundamentally complex, it will take a long time to automate.

Ultimately, the AI revolution, for all its terror, may be the kick in the butt that humanity needed. It is forcing us to move beyond a paradigm of optimizing existing processes and instead to ask:

What is fundamentally new, what is uniquely human, and what is worth pursuing.

The greatest motivation has always been survival, and in the face of this unprecedented challenge, our survival may depend on our capacity for imagination.