📰 Key Takeaways

The latest quarterly results from India’s two IT services giants, Tata Consultancy Services (TCS) and Infosys, give the market both hope and worry. According to analysts, AI adoption in enterprises’ legacy software systems is accelerating and driving growth in high-margin contracts. On the other hand, the productivity gains from AI are also squeezing revenue in traditional business segments, putting pressure on overall revenue. In terms of numbers, TCS’s annualized AI revenue grew more than 19% in the July–September quarter, while Infosys’s AI revenue grew 29% from the previous quarter. In other words, AI-related income has become a growth pillar for both companies, but it’s not yet enough to fully offset the revenue lost from traditional services as efficiency improves. This “AI eats away with one hand and props up with the other” dynamic keeps the industry cautious about what comes next. The original summary only covers the points above; for details like each company’s total revenue, segment performance, and management outlook, please see the original article.

💬 JudyAI Lab Take

TCS and Infosys’s latest quarterly results send two signals at once: AI revenue is growing fast, while traditional services are shrinking because of efficiency gains. This story matters because it shows the two-sided effect of AI on enterprise revenue in concrete terms.

TCS’s annualized AI revenue grew more than 19% in the July–September quarter, and Infosys’s AI revenue grew 29% from the previous quarter. That shows that bringing AI into legacy software systems really can drive high-margin contracts. But the same productivity gains are also compressing revenue in the traditional segments, and the new AI income isn’t yet enough to fully offset it. For AI builders, this points to a design question worth thinking about: the more successfully you sell an efficiency tool, the fewer billable hours your customers need to pay for. When we plan our own products, we should be clear about whether our pricing logic is tied to time spent or to outcomes delivered, because the former shrinks naturally as AI improves.

I’d suggest taking another look at your own products or services. List which revenue sources depend on “time spent,” and think about whether you can shift to outcome-based pricing.

📅 Source Info

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