Artificial Intelligence is beginning to weaken the traditional scale advantage enjoyed by the country’s largest information technology services firms, with mid-cap players gaining ground through faster execution, lower-cost delivery and quicker workforce retraining. Yet, in an uncertain macroeconomic environment, global clients continue to favour large incumbents for bigger outsourcing contracts, slowing momentum in large deal wins for smaller firms.
Mid-cap IT firms witnessed a year-on-year decline of around 10% in large deal wins during FY26, even as large IT companies recorded around 12% growth in such deals, according to data from CareEdge Research. The divergence comes despite mid-cap firms continuing to outperform larger peers on revenue growth and execution.
“The divergence is primarily driven by cautious discretionary spending and delays in decision-making by clients due to a mix of global macroeconomic uncertainties,” said Tanvi Shah, senior director at CareEdge Advisory. “Additionally, enterprises might have preferred established large IT players due to their broader capabilities and stronger execution scale.”
What does an aggregate analysis suggest?
An aggregate analysis of mid-cap firms including Coforge, L&T Technology Services, Mphasis and Persistent Systems showed quarterly revenue growth improved from 2.1% in Q3FY26 to 2.6% in Q4FY26. On a yearly basis, revenue growth stood at 14.3% in Q4FY26, compared with 4% growth reported by large-cap peers including TCS, Infosys, HCLTech, Wipro and Tech Mahindra.
However, the pace of expansion has moderated from the stronger growth levels seen a year ago, reflecting the broader slowdown in discretionary technology spending globally. “While AI-related spending continues to create new opportunities, the cautious approach towards discretionary spending by firms across sectors and its impact on deal momentum would be the key factor to be monitored,” Kalpesh Mantri, assistant director at CareEdge Advisory, said.
Industry executives said the rise of AI-led delivery models is beginning to alter competitive dynamics in the sector by reducing the importance of sheer workforce scale. Mid-cap firms, operating with lower margins and smaller employee bases, are increasingly using flexibility and pricing to compete for transformation projects.
“Tata Consultancy Services has Ebitda margins of 18%, which is by far the best in the industry surpassing even global counterparts like Accenture or Cognizant. This has given mid-cap IT firms the ability to offer deep discounted deals in AI as they’re not as concerned to maintain a better margin profile,” Gaurav Vasu, CEO and founder of UnearthInsight, said.
Executives at mid-cap firms also said smaller size was proving advantageous in adapting to AI-led operating models. Coforge, which reported a 30% rise in fourth-quarter revenue and a 134% jump in net profit, said rapid workforce retraining had helped the company address new opportunities.
“There are new value pools that can be addressed by nimbler players who can re-orient themselves and re-train their staff quickly,” Coforge CEO Sudhir Singh said during the company’s earnings call. “Because we’re smaller, in the past three years we’ve been able to take 35,000 people and re-train them at a speed that is reflective in our performance.”
Manish Tandon, CEO & MD of Zensar Technologies also shared that in the current environment of tight demand, speed matters. “AI is not a disruption risk but a net positive for us; it improves productivity, accelerates transitions, and enables more scalable delivery” he noted.



















































































































































































































































































































































































































































































































































































































































































































































