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AI-Driven Job Displacement vs. Augmentation in the Indian Gig Economy & Services Sectors: Policy Challenges for Viksit Bharat @2047

Year: 2026
Type: article
Abstract: Artificial intelligence is disrupting jobs worldwide. With a large gig and service economy, India finds itself at a crossroads. This paper evaluates the impact of generative AI on both the gig economy and services in general. We compare displacement (potential automation due to AI capability) with augmentation (increasing productivity and generating jobs) due to AI. Based on data collected in 2025-2026 (including from Goldman Sachs, NITI Aayog, ICRIER, Nomura, and PLFS/CMIE), it becomes clear that the former is lower than the latter: roughly 42-48% of non-agricultural jobs are supplemented by AI, while 8-12% are under threat of being automated by it. As far as the gig economy is concerned, AI technologies (data labeling, routing optimization, etc.) increase income for 70% of people working in the industry while introducing a lot of uncertainty to low-skill workers, such as drivers and delivery guys. The story is similar in the service sector (IT, BPO, customer experience): thanks to AI-driven productivity, there is net job creation, although there is a sharp decline in entry-level hiring after ChatGPT. According to Human Capital Theory and AI augmentation-based analysis, the study finds inequality might become worse (the Gini coefficient may go up 0.03-0.04 for every increase in platform/AI utilization). Proposed policies include a National Mission for Digital ShramSetu, AI-driven skill development courses, portable social security for gig workers, and welfare boards for gig workers. This strategy correlates with Viksit Bharat @2047, as it ensures inclusive and future-proof employment. Unless India takes necessary steps now, the country will have a “low-wage job trap” in the service sector and even higher levels of uncertainty in the gig economy. An annual net productivity increase of 0.4 percent can enhance economic performance, provided that upskilling is done on purpose.
DOI: 10.5281/zenodo.22732195
Language: English
Open Access status: green
OpenAlex ID: W7212424662
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