Incentivise job-intensive industries, says Mohandas Pai

Amid reports that job creation in India remains inadequate, technology investor T V Mohandas Pai has suggested that the country must incentivise job-intensive industries to boost opportunities.
"India is creating large-scale jobs. New members of EPF and ESI clearly show decent job creation, but this is inadequate for our needs," Pai, a former board member of Infosys, said.
"To boost employment, the government must incentivise employment-intensive industries like garments, textiles, auto and infrastructure and not capital-intensive ones as done hitherto," he told PTI.
"Our wrong policies of favouring capital intensity instead of employment intensity has hurt us badly."
According to Pai, the government has taken many initiatives to generate jobs, but they are not bearing fruit as investment is down, especially in the private sector.

"Agriculture has been stressed and that has pulled down growth," he added.

Pai made a pitch to reduce the number of people dependent on agriculture.
Today, about 52 per cent of Indians depend on agriculture which, at 15 per cent of GDP, is growing at 3 per cent per annum whereas some 48 per cent are dependent on industry. The services sector is growing at over 10 per cent, Pai added.
"The wide disparity in growth is creating greater divergence and social stress. There is a need for more than 30 per cent to shift to industry and services if their income has to grow. There is no way agriculture can sustain such a large number of people as their primary source of income," he said further.

Pai, a former chairman of Sebi Primary Markets Advisory Committee, also said formal jobs being created are inadequate to meet India's needs.
"I estimate that 60-80 lakh formal jobs are being created every year which pay PF or ESI. This is against 1.8 crore who need jobs every year."
The chairman of Manipal Global Education Services and Aarin Capital Partners is of the view that sectors such as financial services are prone to technology disruption and automation, especially with many new start-ups coming up.
"In banking, over the last 15 years, both assets and liabilities have grown by over 10 times, but employment by only five per cent. This is the result of automation and very high increase in labour costs. The technology sector is seeing reduction in employment as it adjusts to more automation, severe competition, a slowing global economy and stress in the financial sector," Pai added.

Pai termed the World Bank research as "grossly exaggerated" which predicted that automation threatens 69 per cent of the jobs in India.
On what Indian IT needs to do in the age of automation,
Internet of Things, cloud computing and the overall move towards going digital, he said: "To catch trends as they emerge and invest ahead of need, to lead than be led, to innovate faster to lead the market."
Pai does not see any significant increase in IT manpower working on back-end applications, but also not an overall reduction of installed base as new work needs to be done. "As more back-end work gets automated, more work also becomes the back end. (But) growth of manpower is coming down," he added.

He is on the same page as analysts who have projected that traditional customers would spend lesser and lesser on traditional services, predicting that there is going to be only marginal growth in traditional services till 2020, and incremental spending would go to newer areas thereafter.
On doomsday prophecy of "death of code", Pai said: "Code will continue, huge legacy of around USD 4 trillion of code to work on. A large part of new code is getting automated, but building blocks (are) available. The breadth of need is so large that code will never die but can be done easier because of building blocks and automation."

A former chairman of Sebi Primary Markets Advisory Committee, Pai termed as "premature" talk in some quarters that computers in future "will not be programmed but trained as dogs".
"Training a computer by AI, ML (artificial intelligence, machine-learning) needs large number of cases to be out into databases to enable pattern recognition. Analytics would be needed on top and interpretation of analytics and decision making. Rule-based work would be diminished," he added.