Change, not disappearance how AI tools are transforming jobs in technology.
Artificial intelligence is one of the most influential forces shaping the world of work right now. From powering tools that write text and code to automating data analysis and customer service tasks, AI systems are rapidly improving. This has led to a wave of speculation that many jobs, including those in software engineering, might soon disappear. But according to industry leaders, that view is overly simplistic and overlooks how technology evolves with human skill rather than against it. A key voice in this debate is Salil Parekh, CEO of the Indian multinational technology company Infosys, who has offered a grounded and optimistic perspective on what AI really means for engineers.
A Balanced View from an Industry Leader
Salil Parekh heads one of the largest IT services companies in the world. Infosys works with global clients to build large scale technology and business services. Last month, in a conversation with The Economic Times, Parekh addressed the fear that artificial intelligence will quickly make engineers obsolete. Although AI tools are becoming more capable, he said, “it is not that overnight everything is going to be replaced.” He explained that foundational AI models are indeed innovative, but their actual deployment inside complex enterprise systems still requires skilled engineers. His point was clear: AI can help, but humans are still essential to adapt and operate these systems at scale.
This is not just corporate reassurance. Parekh looked at the scale of the global technology services market estimated at around $1.5 trillion and compared it with the size of AI specific services, which he placed at roughly $300 to $400 billion. This contrast suggests that while AI is a fast-growing segment, it is only part of a much larger ecosystem that still needs human expertise. Based on this, Parekh argued that the Indian IT sector, and the broader global technology services industry, is likely to grow and evolve rather than shrink.
What AI Can and Cannot Do
Many executives are wrestling with the same questions about the impact of AI on employment and work. Studies have shown that large language models (LLMs) and other AI systems can write code, translate languages, and even generate creative work. Research from academic sources points out that AI models are increasingly effective at basic programming tasks and generating boilerplate code but they still struggle with deep design thinking, long term maintenance, and understanding complex business requirements. Engineers do much more than produce lines of code they solve problems, design systems, and ensure software works reliably in real world environments.