Infosys is planning to hire another 20,000 college graduates in the current financial year even as approximately 80,000 of its employees already use artificial intelligence (AI) coding tools on client assignments and internal projects. The recruitment plan highlights a significant shift in the Indian IT services industry: companies are increasingly using AI to improve productivity while hiring people who can help customers implement the technology across complex business systems.
Infosys CEO and Managing Director Salil Parekh has said the company hired around 20,000 graduates in the previous financial year and intends to recruit a similar number again. More than 4,000 had already joined in the first quarter, according to his recent comments. The apparent contradiction is that AI can automate parts of software development, but deploying it at enterprise scale creates additional work involving integration, testing, security, legacy-system modernisation and employee training.
Key Takeaways
- 20,000 graduate hires planned: Infosys intends to recruit a similar number of college graduates to last year’s intake.
- 80,000 employees use AI coding tools: These tools support work on client projects and internal assignments.
- AI services are growing: The business contributed more than 8% of Infosys’ revenue in the previous quarter, according to Parekh.
- New skills are required: Graduates are being trained to work with AI systems, support enterprise deployment and help customers adapt their operations.
- Hiring does not eliminate automation risks: Some tasks may require fewer hours or fewer people even as new AI-related services create demand elsewhere.
Why Is Infosys Hiring While AI Automates Coding?
The simplest explanation is that using AI to write code is not the same as delivering a complete technology solution to a business.
AI coding assistants can generate functions, suggest fixes, explain unfamiliar code and automate repetitive development tasks. These capabilities can help engineers complete some activities faster. However, enterprise software projects involve much more than producing lines of code.
A client may need to connect an AI application to existing databases, integrate it with older software, ensure it follows company policies, test it against real-world conditions and protect sensitive information. The solution must also be reliable enough to operate within the customer’s business.
These tasks require people who understand the technology and the customer’s requirements. AI-generated code still needs to be reviewed, tested and maintained, while business users need help understanding how a new system changes their workflows.
Infosys operates as a technology services company, helping enterprises build, maintain and modernise software. If customers increase their spending on AI implementation, the company can find new work even as AI reduces the time required for some traditional programming activities.
This does not mean AI will have no effect on employment. It means the relationship between automation and hiring depends on whether demand for new and improved services grows enough to offset productivity gains that reduce the labour needed for existing work.
What Do the 80,000 AI Tool Users Actually Tell Us?
Parekh has said that approximately 80,000 employees out of a workforce of around 300,000 are using AI coding tools on client engagements and internal projects.
| Reported metric | Figure |
|---|---|
| Employees using AI coding tools | Approximately 80,000 |
| Total workforce cited in recent reporting | Approximately 300,000 |
| Share of workforce represented by those users | Around 27% |
| Graduate hires planned for the current financial year | 20,000 |
| Graduate hires in the previous financial year | Around 20,000 |
| Graduates onboarded in the first quarter | More than 4,000 |
The 27% figure is an approximate calculation based on the reported workforce and AI-tool adoption figures. It is not a measure of how much work has been automated.
The number also does not establish how frequently every employee uses these tools, which tasks they automate or how much time the company saves. An employee may use an AI assistant for a limited part of a project while continuing to perform substantial engineering, testing and client-facing work.
It is therefore important to distinguish AI adoption from full automation. A company can have tens of thousands of employees using AI without eliminating their jobs, because the tools may change how those employees perform their work rather than remove the need for their roles altogether.
The more important long-term questions are how productivity changes, how client demand evolves and whether employees can transition into work that requires different skills.
AI Services Could Become a Much Larger Part of Infosys
The recruitment plan comes as Infosys expands its AI-related business. Parekh said AI services contributed more than 8% of the company’s revenue in the previous quarter and were growing at a double-digit sequential rate.
He also indicated that AI services could represent 20%–30% of the company’s work within a few quarters if the current pace of growth continued, potentially approaching half of its work over two to three years.
These are management projections, not guaranteed outcomes. They also refer to the potential share of work represented by AI services, which should not automatically be interpreted as an equivalent share of revenue, profit or employee headcount.
The company’s AI-related activities include developing AI agents, modernising older technology, supporting coding work and helping businesses deploy AI across their operations. These projects can involve significant consulting and implementation work alongside software development.
For example, a bank exploring AI-based customer support may need assistance with data preparation, integration with existing banking systems, access controls, compliance checks and monitoring. A manufacturer using AI to improve operations may need help connecting software to production systems and evaluating the reliability of its results.
In both cases, the AI model is only one component of the final solution. The services provider must help the customer make the technology useful within an existing business environment.
If demand for these services grows, Infosys will need employees who can work with AI tools, understand enterprise software and help clients implement the technology safely.
Why Fresh Graduates Still Matter
Hiring graduates allows Infosys to build a talent pipeline rather than relying entirely on experienced employees who already have specialised skills.
The company has a long-standing graduate training programme that teaches new employees technical fundamentals, professional skills and specialisations aligned with business requirements. Its annual report describes training in more than 40 technology streams and the introduction of generative AI and prompt-engineering courses.
This training model can help graduates move into areas such as AI-assisted software development, testing, data-related work and technology modernisation. New employees can also learn how to evaluate AI-generated output instead of relying on it without verification.
Graduate hiring may also help the company manage its workforce costs. Experienced specialists in AI architecture, cybersecurity and enterprise transformation can be expensive and difficult to recruit in large numbers. Hiring graduates and training them internally gives Infosys a way to develop some of the capabilities it needs over time.
However, graduates are not immediately interchangeable with experienced engineers. Training requires time and investment, and new hires generally need supervision before they can independently manage complex client assignments.
The business case depends on whether Infosys can train employees quickly enough to meet customer demand while maintaining project quality and profitability.
The Tasks Are Changing, Not Simply Disappearing
AI tools can reduce the effort needed for some activities, particularly routine code generation, documentation and parts of software testing. As those tasks become faster, employers may need fewer hours for a given amount of work.
At the same time, customers may want to modernise more applications, build new AI products or introduce automation into business processes that previously received little technology investment. This creates the possibility that total demand for technology services could increase even while individual tasks become more efficient.
For Infosys, the key is whether the expansion of AI-related work creates enough additional business to offset the productivity gains from automation.
The answer may differ by role. Demand for repetitive tasks could weaken, while demand for AI engineering, systems integration, data management, security and business-process redesign could rise. Some jobs may change substantially, and not every worker will transition smoothly into the new roles.
This is why a graduate hiring target should not be interpreted as proof that AI will have no impact on entry-level employment. It demonstrates that Infosys expects to continue recruiting at scale under its current business outlook, not that every traditional fresher role will remain unchanged.
What This Means for Freshers Seeking IT Jobs
For students and new graduates, Infosys’ plans provide a useful signal: learning to code remains valuable, but coding alone may not be enough to stand out in an AI-assisted workplace.
A strong foundation in programming helps candidates understand what AI tools generate and identify errors. Without that foundation, a developer may struggle to assess whether suggested code is correct, secure or appropriate for a particular problem.
Graduates should also learn debugging, data structures, databases, APIs, version control, testing and basic software architecture. These skills help developers work with existing systems rather than only generate isolated pieces of code.
AI tools should be treated as assistants, not substitutes for understanding. Candidates who can explain their code, investigate unexpected behaviour, test their work and communicate technical decisions are better prepared for real projects.
Knowledge of cloud platforms, cybersecurity, data engineering and AI application development can provide additional opportunities. The right specialisation will depend on the candidate’s interests and the needs of employers, so building fundamentals before chasing every new AI framework is a practical approach.
The broader lesson is that learning does not end when a graduate completes a training programme. As software tools change, employees will need to keep updating their technical knowledge and learn how to apply it to customer problems.
The Bigger Picture
Infosys’ decision to continue graduate hiring while expanding AI adoption reflects the tension between productivity and demand in the technology services business. AI can make certain tasks faster, but enterprise deployment creates work around integration, security, modernisation and organisational change. If customers expand their use of AI, the resulting demand may support continued recruitment even as traditional job responsibilities evolve.
The outcome is not predetermined. AI may reduce the labour required for some projects, and demand for new services may not grow evenly across all skill areas. Infosys’ hiring plan signals management’s current expectations, but the long-term effect on employment will depend on actual revenue growth, productivity gains, the mix of client work and the company’s ability to retrain employees.
What Happens Next?
The next indicators to watch are Infosys’ actual graduate onboarding numbers, the contribution of AI services to revenue, workforce trends and the company’s ability to sustain growth in its traditional and newer businesses. These measures will help show whether AI-led demand is creating enough additional work to balance productivity improvements.
For graduates, the most useful response is to build strong programming fundamentals and learn how to use AI tools responsibly. The future is unlikely to be defined simply by whether AI can write code; it will also depend on who can turn that code into secure, reliable and useful systems for real businesses.
FAQs
1. Why is Infosys hiring 20,000 graduates if AI can write code?
Infosys expects continued demand for technology services, including AI implementation, software modernisation, integration and testing. Graduates can be trained to support these projects, although AI may change the tasks they perform.
2. How many Infosys employees use AI coding tools?
CEO Salil Parekh has said approximately 80,000 employees use AI coding tools on client assignments and internal projects.
3. What share of Infosys revenue comes from AI services?
Parekh said AI services contributed more than 8% of Infosys’ revenue in the previous quarter. The company expects the area to expand, but future growth projections are not guaranteed.
4. Will AI eliminate fresher jobs in India’s IT industry?
Some entry-level tasks may become less labour-intensive, while new work may emerge in AI implementation, testing, data, security and integration. The net effect on fresher hiring will depend on demand growth, automation and how quickly graduates acquire relevant skills.
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