Enterprise technology budgets are expanding again in 2026, despite wavering confidence that investments — particularly in AI — will deliver measurable returns.
IT cost management software provider Apptio highlighted the operational and financial complexities still shaping AI adoption, offering a more measured view of the market’s progress than recent vendor-funded research in a February report. The IBM-owned company surveyed more than 1,500 IT decision-makers in IT financial management and FinOps roles.
The report found a widening gap between spending and expectations.
While nearly three-quarters of organizations reported increasing their IT and software investments, many leaders said they are struggling to justify those decisions internally. As a result, return on investment has become a dominant concern. Nine in 10 respondents said doubts about value affect technology investment decisions, up from 85% the prior year. Nearly half classified the impact as major.
Data challenges are contributing to the uncertainty. A majority of respondents cited distrust in data as influencing decision confidence, while 80% pointed to persistent data silos that make generating the insights needed to justify spending more difficult.
Collectively, these factors appear to be slowing decisions at a time when AI adoption is accelerating.
Organizations feel pressure not just to invest, but to defend those investments.
“The era of cost control alone is over,” Apptio said in the report. “Today, boards and CFOs expect technology leaders to prove that every dollar drives measurable business value.”
Cybersecurity and AI ranked as the dominant priorities for 2026, cited by 94% and 91% of respondents, respectively. At the same time, these categories are attracting increased financial scrutiny. Nearly two-thirds of respondents said they closely monitor cybersecurity spending, while others highlighted scrutiny of cloud services and AI investments.
The findings underscore a growing tension between strategic necessity and cost control, as leaders balance the risks of underinvestment against fears of unpredictable or escalating expenses.
Funding trade-offs
Cost controls are reshaping how AI initiatives are funded, according to Apptio.
Rather than relying on net-new budget allocations, most organizations are redirecting existing internal capital to fund AI. Two-thirds of AI investments were funded through internal budget reallocation, the researchers found, a notable increase from 50% the prior year.
Nearly half of respondents said their organizations are paying for AI by reinvesting savings already generated from the technology. Nearly as many cited dedicated innovation funds as a funding source. Both figures increased compared to Apptio’s previous survey.
The shifts underscore a broader reality. AI may be viewed as strategic, but it is rarely insulated from financial trade-offs.
“Emerging technologies promise growth, but they also introduce vulnerabilities like governance challenges and cost volatility,” Apptio analysts said. “Technology spend continues to rise, especially for cybersecurity, AI and cloud, yet heightened cost sensitivity signals intensifying scrutiny. Proving value requires closing critical data gaps and aligning spend with strategic outcomes.”
ROI unease has helped make spending guardrails a central focus for FinOps teams. Improving cost visibility and forecasting accuracy ranked among the top management priorities, according to the report.
More broadly, respondents reported growing emphasis on aligning both cloud computing and AI spending with measurable business outcomes, cited by 53% and 42% respectively.
The partner angle
A disconnect between perceived financial control and operational capability represents an opportunity for technology partners.
While 59% of ITFM professionals said their forecasts are highly accurate, only 35% reported using purpose-built ITFM platforms. Most organizations continue relying on ERP systems or spreadsheets, according to the survey. The chasm suggests many enterprises may be overestimating their financial visibility, creating potential advisory opportunities for partners focused on financial management modernization.
The report raises similar questions about FinOps maturity. Although more than 70% of FinOps leaders rate their practices as established or higher, only 14% report achieving full chargeback for cloud costs. Meanwhile, 90% still depend on manual processes for resource optimization, Apptio found. The mismatch reflects a familiar challenge for partners navigating customer environments shaped by strategy confidence but constrained by tooling and automation limitations.
Emerging workloads further are intensifying visibility pressures. Apptio found that 89% of respondents lack active cost management mechanisms for Kubernetes environments. While nearly all FinOps teams report managing AI-related expenses, only 13% said they are actively optimizing AI and machine learning cloud costs.
The data suggest cost governance practices are struggling to keep pace with increasingly dynamic technology architectures, opening potential opportunities for partners specializing in cloud financial management, cost visibility and optimization.
These trends highlight the increasingly complex balancing act technology leaders and their channel partners face.
Apptio recommends organizations — and by extension, their channel partners — take several steps:
- Unify insights by integrating financial and operational data to establish a single source of truth for cost, usage and value.
- Modernize capabilities by adopting tools and automation designed to replace manual workflows and improve accuracy.
- Plan dynamically by moving beyond rigid annual cycles toward more agile planning models.
- Prepare for variability by anticipating shifting priorities and cost fluctuations across the broader technology portfolio, including AI, containerized workloads and hybrid environments.
“By managing the complexity of technology investments today, organizations can transform them into engines of growth and innovation,” the analysts wrote.
