Artificial intelligence is creating new business opportunities for technology service providers, but it is also changing what customers expect to pay for software development, consulting and digital transformation.
Infosys has lowered its revenue-growth forecast for the 2027 financial year, citing a more challenging operating environment as clients demand greater productivity and competition intensifies.
The revised outlook, announced alongside the company’s second-quarter results on October 23, highlights a central challenge for the IT services industry: companies must turn AI adoption into new revenue while managing pressure on their traditional service businesses.
What changed in Infosys’ outlook?
Infosys revised its full-year fiscal 2027 revenue-growth forecast to 1%–2% in constant-currency terms.
The company reported revenue of $5.145 billion for the quarter ended September 30, 2026. Revenue grew 1.5% year over year in constant-currency terms, while operating margin remained at 21%.
The lower forecast came despite several positive indicators in the quarterly results, including significant new contract wins and growing revenue from AI-related services.
Reuters reported that investors were concerned about the combination of slower demand, tougher competition and AI-driven pricing pressure. Infosys shares fell during trading on October 26 following the revised outlook.
The company has not attributed its slower forecast to AI alone. Weak spending in some client industries, changes in outsourcing arrangements and the exit from a large European manufacturing contract were also cited in analysts’ assessments.
Why is AI creating pressure for IT service providers?
Technology consulting businesses have traditionally earned revenue by helping clients build, maintain and modernise software systems. Much of that work involves skilled employees, project-based contracts and long-term service relationships.
AI tools can now assist with parts of software development, testing, documentation and routine technical support. This creates opportunities for service providers to deliver work more efficiently.
It also changes the conversation with customers.
If a team can complete a task in less time with AI assistance, a client may expect the savings to appear in the price of the service. Providers could therefore face pressure to deliver more work without a proportional increase in revenue.
The effect will differ across projects. Some tasks may become faster or less expensive, while complex systems integration, security, architecture and regulatory work may still require substantial human expertise.
For service providers, the challenge is to capture value from productivity improvements rather than simply pass all the benefits to customers through lower prices.
The important counterpoint: Infosys’ AI business is growing
The revised forecast does not mean Infosys is failing to benefit from AI.
In its second-quarter results, the company said AI-related revenue represented 10.5% of total revenue and grew 29% sequentially.
Infosys also reported $5.2 billion in total contract value from large deal wins during the quarter, with 62% classified as net new business.
These figures suggest that customers are spending on technology transformation and AI-related services even as the broader growth outlook becomes more cautious.
However, the figures need to be interpreted carefully. Sequential growth in AI-related revenue does not automatically mean the company’s entire business will grow quickly, and the value of signed contracts is not the same as revenue already recognised.
The contrast is the important point: demand for AI services can rise while overall growth remains constrained by pricing, client budgets and other parts of the business.
How are customers changing their expectations?
Companies adopting AI increasingly want measurable improvements rather than technology projects that produce only experimental results.
They may ask service providers to demonstrate how AI reduces software-development time, improves reliability, lowers operating costs or speeds up business processes.
Those expectations can affect how contracts are priced and delivered.
For example, a client paying for software maintenance may want to know whether AI-assisted coding allows the provider to resolve more issues within the same budget. A company commissioning a new application may expect AI to reduce development time without sacrificing testing or security.
Service providers need to show that their use of AI produces reliable outcomes. They also need to manage the cost of adopting the technology, including training, infrastructure, governance and quality assurance.
This is a commercial challenge as much as a technical one.
What does this mean for IT service companies?
Infosys’ results highlight several pressures that technology service providers should monitor.
Pricing models may change. Clients could become less willing to pay solely for hours worked if AI reduces the time required for routine tasks.
Demand may shift towards higher-value work. Complex integration, AI implementation, cybersecurity and business-process redesign could become more important as routine work is automated.
Productivity gains need to be measurable. Providers will need evidence that AI improves delivery speed, quality or cost, rather than relying on general claims about efficiency.
Competition may intensify. Customers can compare established service providers with in-house teams, specialised AI firms and software vendors offering more automated services.
Revenue growth may become uneven. Strong demand in AI-related services may not offset weakness in other sectors or existing service lines immediately.
These changes do not mean traditional IT services will disappear. They indicate that the way those services are priced, delivered and evaluated is evolving.
What should businesses take from this?
For companies buying technology services, AI creates an opportunity to reconsider how projects are scoped and measured.
Instead of evaluating a provider only by the number of employees assigned to a contract, customers can set clear expectations around delivery time, software quality, reliability and business outcomes.
They should also consider where human expertise remains essential. AI-generated code and automated workflows still require appropriate testing, security review and accountability.
For technology service providers, the priority is to develop offerings that customers value enough to pay for, while ensuring that productivity improvements translate into sustainable margins.
The companies best positioned to adapt will likely be those that combine AI capability with industry knowledge, dependable delivery and measurable results.
What happens next?
Investors and customers will be watching whether Infosys can return to stronger growth while maintaining margins and converting its AI investments into sustainable revenue.
The company’s next results should help clarify whether the lower outlook reflects temporary client caution, structural pricing changes or a combination of factors.
Its AI revenue performance, large-deal conversion and growth across major client industries will be important indicators.
For the wider industry, the same questions apply: how quickly are clients adopting AI, where are they willing to spend, and how much of the productivity benefit will service providers retain?
The takeaway
Infosys’ lower growth forecast illustrates the two-sided effect of AI on technology services.
AI can create demand for consulting, implementation and automation, while simultaneously making some existing services faster to deliver and harder to price as before.
The opportunity is real, but it does not guarantee rapid revenue growth. For providers and customers alike, the focus is shifting towards demonstrable business value, effective implementation and sustainable economics.
Sources for this report