Lightspeed India Partner: Cheap Superintelligence Will Trigger 10x Workload Growth in the Next 5 Years
Lightspeed India partner Hemant Mohapatra pointed out that 99.9% of people globally are unaware that powerful and inexpensive intelligence is about to arrive in the next 5 years. People have developed a 24x7 screen dependency on information and will soon become addicted to superintelligence, leading to a 10-fold increase in workload rather than a reduction from current levels.
This view echoes his previous discussion of AI as a new type of 'natural resource' and observations of individuals' high-intensity daily use of tools like Claude, highlighting the accelerating trend of AI transitioning from an auxiliary tool to a core productivity driver.
Source: Public Information
ABAB AI Insight
This statement reveals the asymmetry of AI diffusion: a few early adopters have transformed cheap intelligence into daily productivity gains, while the majority remain at the level of information consumption. This cognitive gap will amplify productivity stratification—individuals and organizations that master the toolchain can achieve exponential output, while those who do not keep up will face a rapid decline in relative competitiveness. The judgment of workload expansion rather than replacement indicates that AI primarily serves to expand the boundaries of possibility rather than merely compress labor time, consistent with historical patterns following the widespread adoption of electricity or computers: new capabilities first generate more complex tasks, then slowly reshape distribution structures.
From a long-term structural perspective, this reflects the re-concentration of wealth and opportunity under technological substitution. AI lowers the cost of acquiring intelligence but raises the threshold for its effective utilization, leading to the concentration of capital, technology, and talent at a few nodes. If institutional constraints and incentive mechanisms are not adjusted in tandem, this migration may exacerbate class solidification: early investors in AI infrastructure or application layers gain pricing power, while the traditional labor market faces overall increased task complexity.
The event is also placed within the larger context of the global AI race. The arrival of cheap intelligence is not evenly distributed but relies on the concentrated supply of computing power, data, and model training, reinforcing the dominance of a few innovation centers while forcing countries to reposition their roles in industrial migration. Ultimately, the distribution of the dividends from productivity leaps will depend on how institutions respond to this technology-driven rebalancing of power and capital, rather than the technology itself.