India employers lag on AI training as skills gap widens

Randstad Digital has published a report on the widening gap between AI investment and workforce readiness, highlighting a growing challenge for employers in India.

Many organisations are increasing spending on AI tools without building the talent base needed to turn those investments into stronger business results. The report describes this as an "AI Productivity Paradox", where gains in task efficiency fail to deliver broader organisational improvement because staff still spend time on rework, oversight and managing added complexity.

Across global markets, 63% of employers invested in AI training over the past year, with IT services and telecom among the sectors most active in reshaping workforces around AI. Yet 74% of professionals said they need to improve their AI skills to remain relevant, underlining the pressure on workers to keep pace with changing job demands.

The study also found that 52% of tech talent are seeking training independently because employer-led programmes are not keeping up. Nearly one in four, or 23%, said they had left jobs because they lacked access to learning and upskilling opportunities geared to future needs.

This has direct implications for employers trying to retain skilled staff while introducing AI across more of their operations. The main constraint, the report argues, is no longer access to technology but whether organisations can create the learning structures staff need to use it effectively.

India focus

In India, about 50% of organisations said they now offer AI training. That remains below what is needed as digital transformation expands, Global Capability Centres grow, and more enterprises adopt AI across business functions.

The report also points to a shift in hiring patterns. More than 30% of organisations in India said they plan to reduce graduate hiring as AI adoption rises, suggesting companies are rethinking entry-level recruitment as automation changes the mix of skills required.

A gap is also emerging between what employers believe they are providing and what workers say they need. This mismatch highlights the need for more structured, continuous approaches to skill development rather than one-off training efforts.

Demand for AI-related skills has risen by 1,587%, based on the report's analysis of global job postings. The increase reflects how quickly job requirements are changing and why companies are under pressure to update workforce skills in step with new tools.

While more than 60% of workers reported productivity gains from AI adoption, many employers are still struggling to convert those gains into better business outcomes. Time saved on individual tasks is often absorbed elsewhere in workflows unless organisations redesign processes and improve staff readiness.

Learning model

Randstad Digital argues that employers need to move beyond periodic training programmes and build what it calls capability infrastructure. In practical terms, that means embedding learning into daily work, tailoring it to specific roles, and linking it more directly to operational goals.

Continuous upskilling, personalised learning and "Training as a Service" are central to that model. The organisations most likely to benefit from AI, it says, will be those that can reskill workers quickly and repeatedly as technologies evolve.

This idea is reflected in the report's emphasis on "learning velocity", defined as the speed at which organisations can adapt, reskill and build AI-ready talent systems. Rather than focusing only on rates of AI adoption, the study argues that future competitive strength will depend on how quickly workforces can absorb and apply new skills.

The research draws on insights from more than 27,000 individuals and 1,225 employers across 35 markets, alongside secondary analysis of more than 3 million global job postings. That dataset supports the report's broader conclusion that employability is shifting towards a skills-based model shaped by constant learning rather than static qualifications.

For Indian employers, the challenge will not stop at deploying AI tools or expanding digital operations. They will also need to address retention, redesign training and align workforce planning with a faster-changing skills market.

Milind Shah, Managing Director, Randstad Digital, said: "Enterprise AI is not failing at the model level, but at the implementation layer. When organizations increase the velocity of tools without building the capability to use them effectively, it creates complexity rather than value. The focus for leadership now needs to shift from investment levels to learning velocity. Upskilling must be treated as core business infrastructure."