Indian IT Was Supposed To Die From AI. Instead It's Billing for the Cleanup.
Two years after generative AI was supposed to render India's $250 billion IT services industry obsolete, the sector is finding that enterprises still need someone to handle the unglamorous plumbing work that large-scale AI deployment demands. Less than 15% of organizations are meaningfully deploying the new technology, according to investment bank UBS, and Indian IT firms are positioning themselves to capture the preparatory work -- data cleanup, cloud migration, system integration -- that channel checks suggest could take two to three years before enterprise-wide AI becomes feasible. The financials have held up better than the doomsday predictions suggested. Infosys now calls AI-led volume opportunities a bigger tailwind than the deflation threat, a reversal from 2024, and orderbooks held steady in the third quarter even as pricing pressure filtered through renewals. Infosys expects its orderbook to grow more than 50% this quarter, anchored by an NHS deal worth $1.6 billion over 15 years. The companies have been restructuring accordingly. TCS cut headcount by 2% and invested in a 1GW data-centre network while acquiring Salesforce advisory firm Coastal Cloud. HCLTech reduced margins by 100 basis points and became one of the first large systems integrators to partner with OpenAI; this week it announced acquisitions of Jaspersoft for $240 million and Belgian firm Wobby to expand agentic AI capabilities. The bear case for the Indian IT sector assumed that AI would work out of the box. Two years in, it does not. Read more of this story at Slashdot.
Two years after generative AI was supposed to render India's $250 billion IT services industry obsolete, the sector is finding that enterprises still need someone to handle the unglamorous plumbing work that large-scale AI deployment demands. Less than 15% of organizations are meaningfully deploying the new technology, according to investment bank UBS, and Indian IT firms are positioning themselves to capture the preparatory work -- data cleanup, cloud migration, system integration -- that channel checks suggest could take two to three years before enterprise-wide AI becomes feasible.
