Infosys reported its Q2 FY27 results on October 23. AI revenue reached 10.5% of total revenue, up from 8.2% the quarter before, and grew 29% sequentially. Total revenue grew 1.5% year over year in constant currency. The company lowered its full-year growth guidance to 1% to 2%, from 1.5% to 3% earlier. CFO Jayesh Sanghrajka said Infosys has seen "pricing pressure on the back of competitive intensity and higher ask on productivity," and expects that pressure to continue into the second half of the year.
Those are the facts as reported. Everything below is my opinion.
My position: clients have figured out that AI makes delivery cheaper, and they want their share of the savings. Selling hours is getting harder every quarter. The firms that win will price the outcome and staff it with senior people who know how to use the tools.
The productivity dividend belongs to someone
When a team ships the same work in fewer hours, somebody keeps the difference. For years, services firms kept it by billing the same rate card and quietly improving margins. Buyers have caught up. They read the same headlines about AI coding assistants and test automation, and they now walk into renewals expecting a lower number.
That is what "higher ask on productivity" means in plain words. The client is saying: you got faster, so I should pay less.
Why hourly billing is the weak spot
If you sell time, every efficiency gain is a revenue cut. You can fight that by hiding the gains, but buyers are not naive, and the trust cost is high. The alternative is to stop selling time.
Fixed-scope projects, outcome-based milestones and managed capacity with clear deliverables all let a vendor keep part of the productivity gain while the client still pays less than before. Both sides win, and nobody has to pretend AI did not happen.
What smaller firms can take from this
Large IT services companies are built on headcount, so this shift hurts them most. Smaller firms have an advantage if they move first.
Price the result. Agree on what done looks like and what it is worth to the client, then price against that.
Staff senior. One experienced engineer with good AI tooling often replaces a pyramid of junior billable hours. Clients notice the difference in quality and speed.
Show the math. Tell the client where AI saved time and what you did with it. Transparency turns a pricing fight into a partnership conversation.
A fair counterpoint
To be fair, Infosys also signed $5.2 billion in large deals this quarter, including a net-new mega deal of over $2 billion, so demand for big transformation work is real. Pricing pressure is not the same as shrinking demand. My view is only that the old way of charging for that demand is under strain.
The payoff
Infosys shows that AI revenue and pricing pressure can grow at the same time. The lesson for services leaders is to stop selling effort and start selling outcomes. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Clear scope and senior people were the engine. Strong people on profitable work raise the whole company.
Want help delivering outcomes instead of hours? Visit tdzpro.com.
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