TCS quarterly profit rises 15% as annualised AI revenue tops $3.1 billion
publishers 17articles 74first reported 8 Oct, 11:00 UTCdeveloping since 8 Oct · 25 editions
Tata Consultancy Services reported consolidated net profit of ₹13,884 crore for the quarter ended September 30, 2026, up 15% from a year earlier. The Hindu reported quarterly revenue of ₹73,188 crore, an increase of 11.2% year-on-year and 1.3% sequentially, while The Indian Express put the year-on-year rise at 11.78%.
TCS said annualised revenue from artificial intelligence exceeded $3.1 billion and accounted for more than 10% of revenue. Total contract value stood at $9.6 billion. Net cash from operations was ₹14,190 crore, equivalent to 102.2% of net income, while net margin was 19% and operating margin was 24%.
Chief Executive K. Krithivasan said growth was broad-based across international markets and most industry segments. President and Chief Operating Officer Aarthi Subramanian said demand continued to accelerate for AI-native solutions, AI-led enterprise transformation and autonomous global business services.
The company had 598,056 employees at quarter-end, compared with 593,314 a year earlier, while IT services attrition was 13.3%. TCS said employee learning hours increased 17% sequentially to 17.1 million. Its board recommended a dividend of ₹12 per share, with payment scheduled for October 30.
HOW THIS STORY WAS MADE
Written from 5 articles, 5 with the publisher's own text; 2 independent newsrooms once syndicated copies count as one; this version written 234 h after the record first saw the story; the editor kept it as written.
- Publishers
- 17
- Source articles
- 74
- Given to the writer
- 5, 5 with the article's own text
- Independent newsrooms
- 2
- This version written
- 234 h after the record first saw the story
- Second model (editor)
- kept as written
- Publication gate
- passed
- Human review
- none
WHAT THE EDITOR DID
The second model checked the writer's draft against the same sources and published it as written.
Written by a language model from the sources above, then checked by a second model that may only cut, attribute or correct. How it works →