AI Zeitgeist: Who Wins, Who Loses?
I don’t believe in luck. I call it preparation (and anticipation). - Blue Bloods
The 2026 India AI Impact Summit in New Delhi shows that Artificial Intelligence (AI) is the defining spirit of the present day. In economic terms, such moods are called “K-waves”. But what is a K-wave?
The world economy goes through cycles, called Kondratieff cycles (K-waves). These K-waves are 40-to-60 year cycles of boom and bust, driven by major technological innovations and infrastructural shifts. Developed by Russian economist Nikolai Kondratiev, these "long waves" have two phases: economic expansion, followed by contraction.
For example, the industrial revolution started the first wave. The second was led by railways and steel, and the third wave by electricity/chemicals/internal combustion engine.
The current wave can be traced back to the 1980s, and its propellants are: microchips, internet, globalization, and financialization. Now, it seems we are on the cusp of the sixth wave empowered by AI, clean energy transition, robotics & automation, and biotechnology breakthroughs.
Another phenomenon is the emergence of secular trends.
A secular trend is a long-term directional movement that lasts decades, reshapes multiple sectors, and persists through recessions and political cycles (e.g. declining birth rates, rising automation, urbanization).
In this sense, AI is a secular trend because it is built on long-term exponential improvements in computer power and data availability. It also penetrates multiple industries simultaneously: healthcare (diagnostics, drug discovery); manufacturing (robotics + predictive maintenance); finance (risk modeling, fraud detection); agriculture (precision farming); logistics (routing optimization), and; creative industries (design, media).
AI’s reach resembles earlier general-purpose technologies like electricity or the internet. This will accelerate across the economy and rearrange the economic hierarchy, creating winners and losers. Let us look at what this looks like:
Income increases for some varieties of software engineers/data scientists, AI specialists and English-speaking knowledge workers.
Pressure on call center agents, back-office processing staff, routine coding jobs and basic clerical roles.
India’s IT-BPO sector has been a major middle-class engine. If AI automates entry-level cognitive work, the ladder narrows. This will widen inequality between elite tech workers and the broader educated workforce.
Rural regions dependent on agriculture, low-skill manufacturing, and informal services may see slower income growth. Unless AI tools are adapted for agriculture and rural productivity, capital will cluster in existing urban tech ecosystems - increasing regional inequality.
Secular technology trends will tend to reward equity/land holders, founders, investors, and platform owners. India already has high wealth concentration. Without broad asset ownership, the gains won’t distribute evenly.
AI increases the premium on advanced technical skills, analytical ability, creativity, and adaptability. If only top-tier graduates benefit from AI growth, inequality within the educated class widens.
India has benefited from a cost arbitrage through its outsourced service work. If AI reduces the need for outsourcing (automation replacing offshore labor), India’s comparative advantage could shrink. That would affect entry-level white-collar jobs, service export growth, which have traditionally helped reduce poverty and expand the middle class in the present K-wave.
AI has the potential to improve public service delivery, expand digital education access, increase farm productivity via precision tools, enable small entrepreneurs with automation and reduce corruption through automation
The expected effects of AI in the short and long run are:
Short- to medium-term
Inequality will likely increase before it stabilizes. As high-skill wages rise faster, capital income grows and routine white-collar jobs compress; urban tech clusters outperform.
Long term
Outcomes will depend heavily on education reform, reskilling at scale that anticipates AI-induced change, rural tech diffusion, SME adoption support, and broader capital participation.
As secular trends amplify whatever structural strengths and weaknesses already exist, India’s inequality trajectory will depend more on policy and institutional adaptation than on AI itself.
