AI is increasing demand for some IT services while putting pressure on others. Spending is growing around cloud and AI infrastructure, software, implementation, data and integration—but automation can reduce the labor needed for repeatable support and operations. That means technology spending can rise even as some labor-heavy consulting and outsourcing work faces tighter pricing or changing scope.
What is changing—and why the market can look contradictory
AI is redistributing demand, not simply making the entire IT services market bigger or smaller. Companies are buying infrastructure, cloud capacity and AI-enabled software, and they need help integrating those tools into real business processes. At the same time, AI can automate parts of service delivery that once required repeated human effort.
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It helps to separate three measures: technology spending, signed outsourcing contracts and consulting labor revenue. They are related, but they are not interchangeable. For example, spending on an AI cloud service may grow without creating an equivalent increase in consulting fees, while a consulting project to integrate that service may be brief, small or priced differently from a traditional labor-based engagement.
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Infrastructure, cloud and software
Gartner’s September 2026 forecast puts worldwide AI spending at $2.7 trillion in 2026, a projected 49.5% increase from 2025. Its AI infrastructure category is the largest of the three categories below. These are spending forecasts, not a measure of consulting revenue.
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| Gartner AI spending category | 2026 forecast | What it measures |
|---|---|---|
| AI infrastructure | $1.484 trillion | Infrastructure spending within Gartner’s AI spending framework |
| AI services | $576.481 billion | Gartner’s defined AI services category; it is not the entire IT consulting market |
| AI software | $461.637 billion | Software spending within Gartner’s AI spending framework |
Gartner attributes the spending increase to demand for AI infrastructure and the incorporation of agentic AI into established software. In practice, companies may fund AI through data-center capacity, cloud consumption, subscriptions to existing business applications and new software features—not just through stand-alone AI consulting contracts. Gartner also revised its 2026 forecast for AI application development platforms to 39% growth.
Large cloud contracts are growing faster than managed services
ISG’s Q2 2026 Index shows a similar contrast in commercial outsourcing contracts. The figures below are annual contract value (ACV) signed in the quarter, not revenue recognized during that quarter. ISG’s Index includes contracts with ACV of at least $5 million and combines managed services with cloud-based XaaS.
| ISG measure | Q2 2026 ACV | Year-over-year change |
|---|---|---|
| Combined technology-services market | $42.4 billion | Up 43% |
| Cloud-based XaaS | $31.5 billion | Up 65% |
| Infrastructure as a service (IaaS) | $25.8 billion | Up 78% |
| Software as a service (SaaS) | $5.7 billion | Up 25% |
| Managed services | $10.9 billion | Up 2.7% |
The contrast matters: rapid growth in cloud contract value does not mean every service line is growing at the same pace. ISG’s measure also excludes smaller contracts and does not capture all consulting engagements, vendor revenue or project labor.
What companies need help doing
Moving from pilots to production
Many organizations have moved beyond asking what AI might do and are trying to make it work reliably in day-to-day operations. ISG reported that enterprise discussion shifted toward execution, return on investment and business outcomes. Steve Hall, ISG’s chief AI officer and leader of the ISG Index, put it this way: “Management teams are spending less time talking about AI opportunity and much more time talking about execution, return on investment and business outcomes.”
That shift creates work around selecting valuable use cases, building applications or agents, connecting them to existing systems, preparing data, setting controls and tracking whether the deployment delivers the intended result. Gartner also describes providers being engaged for smaller projects that use AI features in incumbent software, alongside custom application work and help managing cost and usage.
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Integration, data and modernization
AI systems depend on more than a model or a demonstration. They need suitable data, context, access controls and connections to the applications where employees work. Boston Consulting Group (BCG) identifies agentic application development, implementation, data operations, context pipelines, enterprise integration and infrastructure modernization as areas that could benefit from demand. Gartner points to custom AI applications and cost management; ICRA identifies GenAI-led transformation, application modernization, data engineering, cloud and cybersecurity as opportunity areas for the Indian providers in its analysis.
These are places where buyers may need help, not guarantees that every project will proceed or that every provider will win new revenue. Gartner’s John-David Lovelock described a shift toward smaller projects that exploit existing software: “Meanwhile enterprises are turning to service providers less often to help them manage the business transformation, and more often for the smaller indirect projects to exploit AI features of their incumbent software system,”
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Where AI puts pressure on services and pricing
AI can reduce paid effort when work is repeatable and requires limited human judgment. ISG says labor-intensive managed-services tasks are increasingly being displaced by large language models and describes pricing deflation and provider-funded AI transformation embedded in contracts. BCG identifies potential effort reductions in infrastructure managed services, customer experience, business-process outsourcing (BPO) and application managed services. Examples include level 1 and level 2 incident management and some end-to-end customer inquiries.
This is task-level exposure, not evidence that entire service lines are about to disappear. The likely effect is a changed mix of work: less time on some routine activities and more need for people to configure, supervise, integrate and improve automated workflows. Whether the provider captures value from that change depends partly on how services are scoped and priced.
ISG’s Q2 2026 report said engineering, research and development (ER&D) ACV fell 6% year over year against a strong comparison quarter, even as deal volume rose 34%; it noted effects in software and embedded engineering. Across the first half of 2026, ISG reported ITO ACV down 5.6% year over year and ER&D ACV down 2.8%, while BPO ACV rose 47%. That divergence argues against treating all outsourcing or consulting as one market with one trend.
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How provider relationships and contracts may change
AI-related work does not always appear as a wholly new contract. ISG says sourcing portfolios are being reshaped, with activity reflecting both work moving between providers and changes in operating models. It reported record new-scope managed-services ACV of $8.2 billion in Q2 2026. Renewals, re-sourcing and redesigned scopes can therefore affect providers alongside net-new demand.
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Labor-based pricing can create a tension: if a provider uses AI to complete the same scope with fewer billable hours, its revenue may fall unless the contract changes or it takes on new work. A provider that can deliver implementation, integration, governed automation or measurable outcomes may be better positioned to win that work. This is a practical implication of the reported pricing and scope trends, not a quantified rule that applies to every contract.
ISG’s Steve Hall also noted the economics facing providers: “Providers are facing more competition and changing economics, include pricing deflation and more provider-funded, AI-powered transformation embedded within contracts.” Buyers and providers should make explicit who pays for transformation, who benefits from productivity gains and how performance will be assessed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the evidence says about jobs and skills
The available evidence supports a change in task mix, but it does not establish the net employment effect across the global IT services and consulting sector. Automation can reduce effort in repeatable operations and engineering tasks; AI deployments can also create demand for architecture, data, integration, governance and domain expertise.
Deloitte’s 2026 survey found that nearly 70% of surveyed technology leaders planned to grow teams in direct response to generative AI. That is a reported intention, not a count of jobs created. The survey also found that 64% of surveyed organizations planned to increase AI investment over the next two years, and that the average technology-budget allocation expected for AI would rise from 8% to 13% over that period. These are expectations from respondents, not confirmed spending or hiring outcomes.
How to compare AI implementation partners
Use a proposal review to test whether a provider can deliver a working, supportable solution rather than only a convincing pilot. Ask for evidence and contract terms against criteria such as:
- Production delivery: How will the provider turn the use case into an application or agent, and what acceptance criteria determine whether it is ready?
- Integration: Can it connect the solution to the ERP, CRM, data, cloud and software systems the business already uses?
- Data and controls: How will it prepare data and context, protect access, support governance and address data-sovereignty needs?
- Operating cost: How will cloud and model usage be tracked, and who is responsible for controlling costs as usage changes?
- Outcomes: Will performance be measured through business results, service quality or cycle time, rather than only hours saved or pilots completed?
- Commercial terms: Who funds implementation, who captures productivity gains, how will changes in scope be handled and what performance measures appear in the contract?
These are evaluation questions, not a standardized provider ranking. The best fit depends on the systems, data, business process and risk requirements of the specific deployment.
How to interpret the market forecasts
The headline figures come from different kinds of evidence and should not be combined into a single growth rate. Gartner’s numbers are spending forecasts; ISG tracks qualifying commercial contract ACV; Deloitte reports survey intentions; and BCG’s estimate is a modeled outlook. ICRA’s forecast applies to a sample of Indian IT services companies, not the global market.
| Source and measure | Reported outlook | Scope and qualification |
|---|---|---|
| BCG, 2026 | Up to $200 billion net uplift in tech services’ total addressable market over five years; equivalent in its analysis to 6%–8% CAGR through 2030 | Consultancy estimate, not observed market growth |
| ICRA, 2026 | 3%–5% USD revenue growth in FY2027 | Forecast for ICRA’s sample of Indian IT services companies |
ICRA cites moderated traditional demand, delayed discretionary spending and GenAI-related uncertainty while identifying AI transformation, modernization, data engineering, cloud and cybersecurity as potential opportunities. Neither that forecast nor BCG’s modeled estimate guarantees growth for an individual firm or service line.
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