S&P Global Ratings is sounding a fresh alarm for Indian IT services, warning that competition from AI-native firms will intensify over the next three years and test long-established outsourcing models. S&P expects these AI-focused rivals to challenge traditional players on pricing, speed, and automation, pressuring both revenue and margins.
The findings are detailed in S&P’s report, “Credit FAQ: AI Impact On Indian IT Firms Will Be Uneven,” released on July 13. The report argues that the threat from AI-native firms will not be evenly distributed across the sector, with business models, client profiles, and service mixes shaping how vulnerable each company is to disruption.
To stay competitive, S&P says Indian IT firms will have to step up their investments in AI capabilities, move swiftly to safeguard high-margin recurring business, and lean more heavily on partnerships with global capability centres. Those that successfully bundle AI into their offerings and deepen integration with client operations are more likely to defend share and pricing.
Even for the better-positioned players, S&P expects growth to moderate. The agency projects industry revenue expansion could slow to just 2% to 4% by FY28, constrained by AI-led pricing pressure and evolving contract structures that favour outcome-based and consumption-linked models over traditional time-and-materials engagements.
The report also situates Indian IT within a broader technology spending reset as global clients scrutinise how they buy and deploy services. Enterprises are rethinking outsourcing scopes, automation roadmaps, and cloud strategies, which could lengthen decision cycles and reduce large deal volumes.
S&P’s warning arrives against a backdrop of mounting concern about AI’s wider economic fallout. The firm notes that its PMI data point to AI having a net negative employment impact in 2026, particularly worrying for services-heavy economies that rely on large, skilled workforces. That raises questions about job transitions, reskilling needs, and credit quality in sectors exposed to rapid automation.
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