AI adoption is reshaping India's entry-level tech jobs, Infosys manager says

Artificial intelligence is changing the economics of Indian technology work, with routine roles under pressure and demand rising for staff who can build, supervise and improve AI-enabled systems, according to Rajeew Vishvakarma, a project manager at Infosys. In a Finextra community opinion, Vishvakarma cited a 33% annual AI talent hiring rate in India, nearly a 20% Indian contribution to global AI projects on GitHub and active AI use by 87% of Indian companies.

The shift has implications for India’s technology services industry, banking operations, fintech, software engineering, compliance, analytics and customer support. Vishvakarma said India is both a major user of AI tools and a producer of AI-driven work, leaving its labor market more exposed to changes in how clients value skills, output and cost efficiency.

Routine work faces pressure

Vishvakarma described a two-track labor market in Indian IT. Demand is increasing for AI engineers, data scientists, cybersecurity specialists and workers able to manage AI systems, while manual testing, basic coding and other process-led tasks face weaker prospects as automation improves.

The mechanism is task-level substitution and augmentation. Generative AI can draft code, test outputs, handle service requests and process data, reducing the need for some repetitive execution work. At the same time, firms still need employees who can define the business problem, validate model outputs, manage data quality and check for operational or compliance risk.

Vishvakarma said the pressure is not a broad replacement of workers, but a repricing of capability. Employees who can combine domain knowledge with AI tools may gain value, while roles built mainly on repeated execution could be more exposed.

Financial services adopt early

Banking and fintech are among the early adopters because they depend on large data sets and repeatable processes, Vishvakarma said. He pointed to uses in fraud monitoring, customer service, credit assessment and regulatory compliance.

Those applications also raise governance demands. In financial services, an incorrect model output can affect a customer decision, a risk control or a regulatory process. Vishvakarma said future finance roles will require a mix of subject expertise, data literacy, risk management and responsible AI deployment, including attention to fairness, privacy, explainability and auditability.

Entry-level pathway may need redesign

Vishvakarma said generative AI creates a specific challenge for graduates. Entry-level technology jobs have often functioned as training grounds, with junior staff learning through basic programming, testing, documentation and operational tasks. If those tasks are automated, companies may need new apprenticeship models so junior workers can still build judgment and experience.

He said fresh graduates will be expected to show familiarity with AI tools, the ability to question and validate outputs, communication skills and a clearer grasp of business context. Without redesigned early-career development, he warned that firms could face a later shortage of experienced workers, since senior capability depends on structured learning over time.

Vishvakarma also argued that India’s outsourcing model is shifting from labor cost advantage toward what he called intelligence arbitrage, where human expertise is combined with AI accelerators, reusable platforms, secure engineering and governance frameworks. He said clients are likely to emphasize outcomes and productivity more than staffing volume.

The International Labour Organization has said many jobs have some exposure to generative AI while a smaller share is highly exposed, Vishvakarma noted. He also cited the World Economic Forum’s projection of a net global increase in jobs by 2030, with growth in AI-related roles.

Vishvakarma said companies should map tasks according to whether they can be automated, augmented or retained for human execution, and should redesign roles rather than focus only on headcount cuts. He also called for practical reskilling paths and closer alignment among education providers, industry and regulators.

This story draws on original reporting from Finextra Research.