Industry 4.0 is evident across India's shop floors, where industrial robots are increasingly being deployed. According to International Federation of Robotics 2023 data, China had the most robot installations worldwide. India ranks 7th, with robot numbers rising by almost 60% each year, led by the auto industry, which accounts for 40% of them.

The northern cluster of the auto industry along NH48 from Gurgaon to Alwar also has a vibrant component manufacturing industry, owing to Haryana's early role in hosting Maruti-Suzuki and Hero-Honda JVs in the 1980s. An 80:20 split exists between MSMEs and top-tier global exporters of auto parts. While automation is on an upward trend, in some cases, it's galloping, in others, it's a slow trot, primarily influenced by the firm's nature.

Large, globally-connected tier-1 companies are rapidly automating to meet quality and precision standards. They have invested in robots for welding, forging, material handling and automated inspection.

Automation in mid-sized and smaller firms is shaped by labour regimes. Almost all workers in automotive manufacturing are contract labourers, recruited through a manpower agency from which firms can hire or fire, depending on production requirement.

The flipside of such flexibility is that contractual workers have a weak attachment to the workplace and greater absenteeism. Mid-sized firms are adopting robots in response to labour volatility during festivals, when migrant workers go to their hometowns and overstay or do not return.

'Robots do not fall sick, take leave or vary in their productivity,' a second-generation owner of a ₹60 cr plastic auto parts company told me. He's replacing people with machines wherever he can afford to, prioritising production lines that involve repetitive tasks, high temperatures or high levels of precision that are unsustainable for workers.

Small manufacturers, caught in a vicious cycle of limited working capital and small order sizes, are unable to automate their outdated processes, despite enthusiasm to do so. Effectively, they have not even crossed the starting line in the race towards Industry 4.0. 'If I could, I would kick out half my employees tomorrow and replace them with robots,' declared the owner of a smaller ₹20 cr company. But he's stymied by limited shop floor space, lack of capital to buy more land, and absence of economies of scale that makes investments in robots unviable.

In the world of white-collar workers, there's near panic that increasing deployment of technology (read: AI) will lead to massive job losses. This is already evident. But what is the effect of automation on blue-collar workers?

Workers do not view robots as a threat - yet. Instead, they acknowledge that automation has improved safety, reduced physical strain and created opportunities for them to move into supervisory roles. Asked about future job losses, one union leader took a generous, macro view and told me that robot manufacturing factories will hire more workers, and, so, overall, it evens out for workers. This echoes international evidence that suggests that while robots may displace certain repetitive tasks, they don't necessarily eliminate employment in aggregate.

But transition from human labour to robots is creating new gaps:

Skill Automation requires different skills from manual work. Workers who adapt and learn gain higher wages and stability, while those who do not risk marginalisation.

Intra-industry Slower automation among smaller firms in the northern auto belt puts them at a competitive disadvantage relative to larger, automated tier-1 firms.

Regional Uneven automation may widen regional disparities, with tier-1- heavy clusters advancing faster, while MSME-dominated regions like Delhi-Haryana risk stagnation.

Policy can address these risks through the following interventions:

Institutions that run programmes to bridge domain-employability skill gap must factor in the rapid adoption of robots.

Supporting MSMEs through subsidised credit, shared automation centres for testing pilot projects, and cluster-based facilities to reduce capital costs.

Recognising that not all workers can transition to automated roles and creating alternative pathways for decent work to prevent polarisation of labour.

Robots are marching into factories. What matters now is how firms and workers adapt. And how policy supports that transition.