Robots are Ready on India's Factory Floors, But There's No One to Operate Them

While the Galgotias University’s robodog was a national embarrassment, it didn’t quite tell India’s automation story. Robots are quietly entering Indian industries, working alongside humans in logistics, warehousing, construction, and agriculture.

The country installed a record 9,100 industrial robots in 2024, ranking sixth globally by annual installations, according to the International Federation of Robotics. The country's robotics manufacturing market, valued at over $1.4 billion, per Ken Research, is projected to nearly double by 2032. 

And yet, across factory floors, university labs, and startup boardrooms, a crisis persists: the people who are supposed to operate, build, and scale these machines often aren’t professionally trained to handle them. 

The skilling gap in Indian robotics is not simply about a shortage of engineers. It is structural, a mismatch between what institutions teach, what industry needs, and what the labour market can absorb. 

The Industry-Academia Disconnect

At the heart of India's robotics talent problem is a failure of communication between the entities best placed to solve it. 

Raghu Venkatesh, Co-founder and CBO of ANSCER Robotics, is blunt. “There is no connection between an industry and institution. The industry is not able to go tell institutions what problems they have, and institutions are also not interested in coming and asking,” he tells AIM.

The gap is driven by outdated pedagogy, lack of hands-on training, and minimal research collaboration. This disconnect produces graduates who are technically trained but industrially unprepared. Many arrive on factory floors with little understanding of ISO standards, safety compliance, or deployment constraints. 

“Most of these people have learned from a very hobby-grade product… they have no clue what industrial standards are,” Venkatesh notes.

Startups like ANSCER are tackling talent shortages by hiring from tier-3 and tier-4 cities, and conducting practical training programmes.

Additionally, government initiatives such as FutureSkills PRIME aim to reskill professionals across emerging technologies, including robotics, AI, and IoT. The programme has already trained over 15.78 lakh individuals in AI-related domains and emerging technologies.

The Software-Hardware Imbalance

India’s comparative advantage in software has not automatically translated into leadership in robotics. The institutional skilling ecosystem remains heavily software-oriented, while robotics requires expertise across embedded systems, electronics, mechanical design, and real-world deployment.

Manish Gupta, General Partner at GrowX Ventures, frames this carefully. “I would prefer companies or founders who are building their own IP,” he says, adding that manufacturing can follow suit. But he also acknowledges a systemic gap: “People who are coming up with IP probably have not done manufacturing before.”

This creates a dual challenge of building intellectual property without hands-on manufacturing experience and scaling products without sufficient system integration skills. However, Gupta notes that manufacturing itself is not the primary bottleneck.

“Manufacturing is just something that you can obviously create with time… I would rather optimise for owning the IP.”

Meanwhile, Sadhika Agarwal, Lead of Investments at Equirus InnovateX Fund, prioritises teams that understand supply chains, certification cycles, and last-mile integration “because that’s often where robotics deployments stall.”

The skilling gap is closely tied to deeper gaps in India’s hardware ecosystem. In drones and robotics, critical areas such as propulsion systems, advanced materials, and precision manufacturing capabilities required for long-endurance applications remain underdeveloped.

Agarwal also highlights that companies merely “assembling off-the-shelf components without meaningful differentiation” are increasingly difficult to back.

A recent report by the Standing Committee on Communications and Information Technology acknowledges similar challenges, noting that building domestic capabilities in emerging technologies requires targeted skilling, R&D investment, and institutional capacity-building. It emphasises the need to strengthen talent pipelines alongside infrastructure and innovation ecosystems.

Reskilling on the Shop Floor

The skilling problem is not limited to engineers. It extends to the workforce operating alongside robots on factory floors.

Venkatesh describes a system marked by inefficiencies, high attrition in material-handling roles, fatigue from repetitive manual work, and limited career progression. Workers often perform physically demanding tasks, such as moving heavy loads, with little opportunity for upskilling.

Automation improves efficiency but requires workers to adapt to new systems. Government programmes are trying to recognise this shift. Initiatives such as YuvAi and the Visvesvaraya PhD Scheme aim to strengthen research pipelines and build advanced technical expertise. However, the effectiveness of these programmes depends on execution and alignment with industry needs.

The “AI for All” approach, mentioned in the report, explicitly notes that while technology may disrupt jobs, “work does not disappear… only its nature changes,” emphasising the need for large-scale reskilling. Yet, translating this into robotics-specific training remains a work in progress.

Even where talent exists, there is limited adoption as companies want robotics to reflect on their P&L sheets as quickly as possible.

“Customers compare the cost of labour versus robotics,” he says. “Indian corporates don’t spend enough time or money to do pilots.”

This weak demand signal has cascading effects. Startups struggle to validate products. Engineers lack exposure to real-world deployments. Investors face uncertainty. The result is a cycle where low adoption reinforces the skilling gap.

A recurring theme is the distinction between assembling hardware and building proprietary technology. While India has made progress in manufacturing, ownership of core IP remains limited.

Gupta emphasises that long-term value lies in IP ownership rather than assembly. However, achieving this requires deep technical expertise, interdisciplinary training, and sustained R&D investment, all of which depend on a stronger skilling ecosystem.

Without this, India risks remaining dependent on imported designs while focusing on assembly, limiting its competitiveness in high-value segments such as defence, drones, and advanced robotics.