AI To Create And Destroy Jobs In India: A Mixed Bag
The COVID-19 pandemic posed unprecedented challenges for employment in India. Data from the Centre for Monitoring Indian Economy (CMIE) paints a sobering picture, showing a decline in total employment from 412.7 million in 2016-17 to 387.2 million in 2020-21, with a partial recovery to 405.8 million in 2022-23. However, the lost ground has not yet been fully regained, raising important questions about the nation”s employment landscape. A closer examination of CMIE”s Consumer Pyramid Household Survey reveals several noteworthy qualitative insights.
Changing Age Demographics:
The decline in India”s employment, with a compound annual rate of -0.28% over six years ending in 2022-23, is primarily concentrated in the 15-39 age group, indicating that younger workers are exiting the job market. Their share in total employment has dropped from 50% to 37%. In contrast, those aged 40-59 have seen their share increase from 42% to 59%. This shift may be attributed to younger individuals struggling to secure employment or opting out, while older workers may have family obligations or debt responsibilities influencing their choices.
Gender Disparities:
The proportion of women in the workforce has decreased from 13.1% to 9.4%, possibly due to family obligations, presenting a setback for gender empowerment.
Educational Background:
The share of individuals with a graduate or higher-level degree remains steady at 12.5%, indicating that most employed individuals have lower educational qualifications. This becomes concerning when combined with the decline in employment among those under 40, questioning the demographic dividend theory. It emphasises the need for comprehensive education and job-oriented courses, as reskilling becomes challenging when individuals lack adequate foundational education.
Shift in Employment Types:
The percentage of salaried workers has remained nearly unchanged at around 21%, while self-employment has increased from 13% to 20%. This suggests a growing preference for entrepreneurship or a possible reluctance among companies to expand their workforce as they embrace artificial intelligence (AI) and machine learning (ML) technologies. The adoption of AI and ML could further reduce the demand for labour, particularly in a labour-surplus economy.
Changing Job Sectors:
The share of small traders and wage labourers has decreased from 42% in 2016-17 to 31%, reflecting declining job opportunities in small and medium enterprises. Concurrently, the percentage of farmers has risen from 23.2% to 27.6%, indicating reverse migration from urban to rural areas. This trend highlights the mismatch between job creation and urban growth, influenced by high living costs and a lack of affordable housing.
Sector-Wise Job Distribution:
In terms of sector-wise employment, agriculture and industry have shown negative growth, while services have experienced growth at 1.5% annually. Services, comprising 36% of employment, have overtaken agriculture. Within the industry sector, real estate and construction account for 17.5%, while manufacturing lags at 8.8%. This shift underscores the importance of the services sector in job creation.
Religion and Employment:
CMIE data on employment across religions reveals intriguing observations. The share of Hindus and Muslims in employment has declined, while Christians, Buddhists, and Jains have seen increases. Sikhs” share remains unchanged, possibly to their affinity for trading, a sector that has witnessed significant growth.
The CMIE data on employment trends in India raises important questions about the impact of AI and ML on job opportunities, especially among younger age groups and women. The shift back to agriculture challenges the urban migration narrative, while the limited contribution of manufacturing to employment defies conventional wisdom. These findings warrant a robust debate on the appropriateness of increased AI and ML adoption, considering India”s unique needs. Finally, addressing the educational gap and promoting job-oriented courses becomes crucial as AI-driven automation continues to transform the workforce.
