A viral research paper has shaken world markets and given India a firm warning. The report, ‘The 2028 Global Intelligence Crisis’, claims that AI systems which can act on their own will completely change outsourcing economics. It connects this change to a quick re-evaluation of the market, a disappearance of the advantage from providing services, and a possible fall in the rupee’s value.
A viral idea hits tech and worries India
The selling began with many announcements of AI agent tech, and got worse after the report came out. India’s main tech share index fell 4.9 per cent in only one day – the biggest fall since August 2023. So far this month, the Nifty IT Index has gone down around 21 per cent, losing over $54 billion.
Traders are now expecting the worst month since September 2008, when the world’s finances fell apart. The worry isn’t a normal, small drop in profits, but a big, lasting change. The worth of companies is decreasing as investors put a price on lasting difficulty for the profits from outsourcing.
The end of cheap labor?
For many years, India’s top IT businesses have done well because of cheap labor: good, skilled workers at a lower cost. This benefit gave global contracts to businesses such as TCS, Infosys, and Wipro. The new idea is that AI which can act on its own is removing this benefit at a rate never seen before.
The report says that the extra cost of an AI coding agent is now close to the cost of electricity. As AI systems which can act on their own do coding, testing, and project managing, customers in the West can skip using vendors completely. Contracts could be cancelled slowly through 2027, making the advantage from services much smaller.
This isn’t a forecast of slower growth, but a likely, big structural change. The ability of AI systems to act on their own challenges why groups of people outside a company are needed. If purchasing moves toward delivery led by machines, people working overseas become a cost which can be avoided.
Macroeconomic risk: rupee, jobs, and spending
The results go much further than quarterly profits. India’s software industry is expected to be worth $315 billion by March 2026, and will give work to around six million people. Software exports have strongly helped the current account and made the rupee’s value more stable.
The report shows a sharp reversal if the advantage from services disappears. It warns that the rupee could fall by as much as 18 per cent in four months. By early 2028, it suggests early talks with the IMF to make the economy stable.
India has not asked the IMF for help since its balance-of-payments problem in 1991. The comparison shows how serious the report is, not that this will happen. People who make policy would probably use reserves, ways of adding money to the economy, and targeted help well before that point.
Automation also threatens demand from the household side. Production could rise as machines do more work, but wages may not keep up. If white-collar jobs fall by 5 per cent in 18 months, spending could become much weaker.
In India, people’s personal spending accounts for well over half of GDP. A fall in the wages of skilled workers would affect urban services and lending. That situation could make cost-cutting stronger and increase the downturn.
Winners, losers, and what comes next
The writers of the report see this time as Phase 2 of the AI trade. The market is changing from being very excited about hardware, to operations, efficiency, and replacing labor. That change puts the winners and losers across industries and countries in a new order.
Chipmakers, data centers, and labs which make basic models stand to gain the most. Their ability to set prices rises as company spending targets computing and managing. On the other hand, intermediaries face difficulty as AI removes friction from deals.
The report introduces Agentic Commerce, where software agents pay and deliver without old systems. If an AI books travel, it uses direct, programmable payments, reducing card fees. That explains the sharp selling of payments and delivery stocks.
Wider indices showed the shock, with software shares leading the falls. A software-focused exchange-traded fund dropped almost five per cent in one day. One famous company which provides services to businesses had its worst fall in over twenty years.
Policy choices: lessening the shock without stopping progress
Co-writer Alap Shah argues that policy should see AI’s uneven gains. He has put forward an AI tax on profits from automation to fund help for people changing jobs. The goal is to slow the link between job losses and falling spending.
For India, the choices are wider and time is short. Choices include faster reskilling in managing agents, cybersecurity, and making sure AI is safe. Incentives could favor services where people are in the loop, safety tools, and platforms for specific fields.
Financial buffers and targeted credit could help urban households which are at risk. Guarantees for export credit could make good contracts stable during talks with vendors. Clear rules on using AI would improve what workers and investors know.
India could also make important infrastructure for its own AI computing. Partnerships between the public and private sectors can secure energy, cooling, and semiconductor supply chains. That cushions upstream changes and attracts high-value AI engineering work.
What Indian IT can do now
Technology services businesses must move up the chain before customers move away. Priorities include making reusable IP into products, pricing based on results, and managed AI operations. Making platforms for managing and making AI safe could become a strong advantage.
Vendors should change from staffing models to service lines which come first with automation. That means sending out internal agents, measurement frameworks, and guaranteed rises in production. Being in line with rules, being reliable, and keeping data in one place will make offers different as risk rises.
Being careful with the balance sheet and hedging currency will be important in a changing market. Choosing to buy companies can add depth in healthcare, finance, and manufacturing. The fastest integrators of human expertise with AI systems which can act on their own will gain share.
The widely shared report is not what will happen, but a wake-up call. Markets are marking down models which depend on cheap labor rather than engineered leverage. India’s path through Phase 2 will depend on speed, clear policy, and doing things well.
