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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallAI is shifting demand across IT services and software consulting, not simply increasing or eliminating it. Spending is growing around infrastructure, cloud, AI-enabled software and implementation, while automation can reduce the labor required for repeatable support and operations. Those trends can happen at the same time—and higher technology spending does not automatically mean higher consulting revenue or more jobs.
What the latest market figures show
The figures below describe different things: forecast spending, large outsourcing contracts, survey intentions and modeled market growth. They are useful indicators of direction, but they are not interchangeable measures of IT consulting revenue.
| Measure | Figure | What it covers |
|---|---|---|
| Worldwide AI spending | $2.7 trillion forecast for 2026, up 49.5% year over year | Gartner’s global AI spending forecast. Gartner identifies AI infrastructure as the largest spending area. |
| AI services spending | $576.481 billion forecast for 2026 | Gartner’s defined AI services category; it is not the whole IT consulting market. |
| AI software spending | $461.637 billion forecast for 2026 | Gartner’s AI software category. |
| AI infrastructure spending | $1.484 trillion forecast for 2026 | Gartner’s AI infrastructure category. |
| AI application development platforms | 39% growth forecast for 2026 | Gartner revised its forecast for this category to this growth rate. |
| Combined technology-services contract ACV | $42.4 billion in Q2 2026, up 43% year over year | ISG Index commercial outsourcing contracts with annual contract value (ACV) of at least $5 million; combines managed services and cloud-based XaaS. |
| Cloud XaaS contract ACV | $31.5 billion in Q2 2026, up 65% year over year | ISG Index cloud-based anything-as-a-service contracts meeting its $5 million ACV threshold. |
| Infrastructure-as-a-service contract ACV | $25.8 billion in Q2 2026, up 78% year over year | ISG Index contracts meeting its $5 million ACV threshold. |
| Software-as-a-service contract ACV | $5.7 billion in Q2 2026, up 25% year over year | ISG Index contracts meeting its $5 million ACV threshold. |
| Managed-services contract ACV | $10.9 billion in Q2 2026, up 2.7% year over year | ISG Index managed-services contracts meeting its $5 million ACV threshold. |
ISG’s figures capture qualifying contracts, not all consulting engagements, small projects, vendor revenue or project labor. The gap between growth in cloud XaaS and the much slower rise in managed-services ACV illustrates why “the IT services market” can tell an incomplete story unless its segment and measurement are specified.
Which IT services are gaining demand?
Cloud, infrastructure and AI-enabled software
Building and running AI systems requires computing capacity, cloud services, data infrastructure and software. Gartner’s forecast points to infrastructure as the largest AI spending category, while ISG’s Q2 2026 contract data show strong growth in cloud XaaS, especially IaaS. SaaS contract ACV also grew, though more slowly than IaaS. Some AI investment therefore appears as cloud consumption or features added to existing software—not necessarily as a stand-alone AI consulting project.
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Getting from pilots to production
Companies need more than a promising demonstration to put AI into routine use. ISG described enterprise conversations shifting toward execution, return on investment and business outcomes. Gartner also reported demand for smaller projects that use AI features in existing software, as well as for custom AI applications and help tracking costs and usage. The consulting opportunity is increasingly about deploying useful systems inside real business operations, rather than simply proving that a model can work in isolation.
Application development, integration and data work
AI-related projects can require custom applications or agents, data engineering, preparation of business context, integration with existing systems, infrastructure modernization, security and governance. BCG identifies these kinds of implementation and integration needs; Gartner notes demand for custom applications and cost management. In India, ICRA also points to GenAI transformation, modernization, data engineering, cloud and cybersecurity as potential opportunity areas for providers.
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These are areas of potential demand, not a guarantee that every provider—or the industry as a whole—will grow. ICRA forecast 3%–5% USD revenue growth in FY2027 for its sample of Indian IT services companies, citing moderated traditional demand and delayed discretionary spending alongside possible AI-related opportunities. That forecast is specific to its sample and geography.
Where AI puts pressure on services and consulting
AI can reduce the human effort required for work that is repeatable and follows predictable patterns. ISG says labor-intensive managed-services tasks are increasingly exposed to displacement by large language models, and reports pricing deflation and more provider-funded AI transformation embedded in contracts. BCG identifies possible effort reductions in infrastructure managed services, application managed services, business-process outsourcing and customer experience—for example, some level 1 and level 2 incident handling or routine customer inquiries.
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This is pressure on tasks and the economics of delivery, not proof that entire service lines are disappearing. When a contract is priced mainly by labor hours or staffing levels, delivering the same scope with fewer hours can squeeze revenue unless the contract is redesigned. A provider may instead seek work in implementation, integration, governed automation or outcomes-based delivery. How gains are divided depends on the contract: buyers and providers need to agree who funds transformation, who captures productivity benefits, how scope changes and what performance measures apply.
ISG’s other figures also resist a one-direction story. In the first half of 2026, BPO contract ACV was $4.8 billion, up 47% year over year, while ITO ACV was $15.5 billion, down 5.6%, and ER&D services ACV was $1.8 billion, down 2.8%. In Q2, ISG reported ER&D ACV down 6% year over year despite deal volume rising 34%, noting effects in software and embedded engineering against a strong comparison quarter. Those contract measures vary by service line and period; they do not establish that outsourcing overall is either disappearing or uniformly expanding.
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How buyer-provider relationships are changing
AI is affecting both what companies buy and how they arrange delivery. ISG reports that enterprise sourcing portfolios are being reshaped, sometimes because work is moving between providers or operating models rather than because a company is outsourcing entirely new work. New-scope managed-services ACV reached a record $8.2 billion in Q2 2026, according to ISG. Renewals and transitions can therefore involve a redesigned scope, not just a like-for-like continuation.
For providers, automation creates a commercial challenge: clients may expect productivity gains to lower costs, while providers must pay for the transformation that produces them. ISG’s reported pricing pressure and provider-funded AI work point to a need for clearer pricing and accountability. For buyers, the practical question is not only whether a vendor can demonstrate AI capability, but whether the contract specifies implementation responsibilities, operating costs, service levels and how measurable gains will be assessed.
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Will AI replace software consultants or increase hiring?
It is changing the mix of work, but the available figures do not settle the net employment effect across the global IT services and software consulting sector. Repeatable support and engineering tasks may require less effort, while production AI projects call for architecture, data, integration, governance and domain expertise.
Deloitte’s 2026 report found that nearly 70% of surveyed technology leaders planned to grow teams in direct response to generative AI. That is a stated intention, not a count of jobs created. In the same report, 64% of surveyed organizations planned to increase AI investment over the next two years, and average technology-budget allocation to AI was expected to rise from 8% to 13% over that period. These are survey expectations, not realized spending or hiring outcomes.
BCG estimated that AI could add up to $200 billion to technology services’ total addressable market over five years, equivalent in its analysis to 6%–8% compound annual growth through 2030. That is a modeled estimate, not observed growth; it depends on new work outweighing the reduction in effort for existing services. Neither it nor survey plans prove how many jobs the sector will ultimately gain or lose.
How to evaluate an AI implementation partner
Use these questions to compare providers for a specific business project. They are evaluation criteria, not a standardized industry ranking.
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- Can the provider take a use case into production? Ask for clear acceptance criteria, an operating plan and a definition of what success means beyond a working demonstration.
- Can it integrate with your existing environment? Explore experience with the ERP, CRM, data, cloud and software systems the solution must work with, rather than only an isolated prototype.
- How will it prepare and protect your data? Ask about data engineering, context preparation, access controls, security, governance and data-sovereignty requirements.
- Can it explain operating costs? Request a plan for cloud and infrastructure spending, usage tracking and cost management after launch, not just an estimate for implementation.
- How will outcomes be measured? Agree on appropriate evidence, such as service quality, cycle time, customer outcomes or return on investment, instead of relying only on hours saved or pilot counts.
- How does the contract allocate cost and benefit? Clarify who funds implementation, who captures productivity gains, how scope changes are priced and how performance is measured.
A provider’s ability to describe these trade-offs is more useful than a broad promise that AI will reduce costs. Production performance depends on the use case, data, integration and operating model, so define what the project must deliver before comparing proposals.
