Customers of technology services expect their overall IT spending in 2026 to remain broadly in line with 2025 levels, while spending on technology services is set to increase modestly. These findings come from Bain’s latest survey of tech services customers. Although recent market dynamics have introduced some uncertainty around timing, customers across most industries are shifting priorities in ways that will require greater investment in technology services. The main exceptions are consumer packaged goods, business-to-business (B2B) manufacturing, and property and casualty insurance.

The scale of these increases reinforces a broader shift: Spending on technology services is no longer discretionary or project-based. It has become a core component of IT budgets, an essential capability that underpins productivity, resilience, and growth. As a result, expectations are rising for both reliability and strategic impact, highlighting the importance of partners who can scale quickly as demand accelerates.

How will spending on AI/ML grow?

The scale of tech investment in AI and machine learning (ML) signals clearly that executives at client firms no longer think of AI as something experimental. It’s becoming a core element of enterprise transformation and the CIO agenda.

Across most industries, 75% of executives said they expect at least 5% to 10% of spending to focus on AI/ML. In some industries (retail and institutional banking, oil and gas), a significant share said they would spend more than 20% of their tech budgets on AI.

They expect results from that spending

Executives also increased their expectations for productivity improvements, particularly in developer productivity, testing, and contact center automation. This will shift conversations from curiosity about capabilities to frank discussions about results. The highest expectations are in highly scalable, core activities that span industries. Repeatable solutions, not pilots or bespoke projects, will take the day.

One implication of this is that as clients demand double-digit improvements in productivity, they will push for lower delivery costs, faster timelines, and outcome-based pricing. This will increase pressure on the traditional FTE-based model, so tech services firms should redesign their pricing structures before clients ask for changes.

Ultimately, though, AI represents an opportunity for margin expansion. Higher productivity won’t benefit only clients; tech services firms will automate delivery, find creative ways to reuse assets, and shift to platform-based delivery. In addition, if executed right, AI will create more capacity, allowing it to be a lever not just for margin, but for growth as well.

Prioritizing security and AI

Client priorities are converging around a focused set of critical capabilities, with cybersecurity and AI-led initiatives consistently at the top of the agenda. AI is no longer a standalone capability but a unifying layer across enterprise enablement, data modernization, and process transformation, increasingly including agentic use cases. At the same time, foundational investments—core system modernization, cloud, and data—are being reframed through the lens of AI readiness, signaling a shift from incremental upgrades to integrated, future-back transformation programs.

For tech services firms, this marks a move toward larger and more outcome-oriented opportunities. Clients are signaling that they want outcomes with more value and tighter integration across AI, data, cloud, and security. The tech services firms that show up with fragmented capabilities will look outdated. The ones that show up with the right set of capabilities, domain expertise, talent pool, and commercial models are likely to emerge as winners.

Tech services companies have a great opportunity to deliver these outcomes, provided they can acquire and develop talent with the skills necessary to deliver. Executives across industries cited cybersecurity, AI/ML engineering, and data science as among the hardest skills to source talent for. Application programming interface engineering; full-stack, cloud-native engineering; and cloud modernization were also cited by many industries. 

This talent crunch is yet another reason that executives continue to use tech services firms for their AI priorities. Firms that bring a full set of capabilities to the table can help clients increase speed to market while also providing the thought leadership that a good partner can offer.