FinOps can provide the visibility that tech investment decisions need
Managing technology as a portfolio often depends on having enough financial and operational visibility to connect spending and consumption to capabilities, outcomes, and risks. FinOps has traditionally focused on understanding and optimizing tech consumption. As technology investments become more dynamic, its role can expand to support the broader tech portfolio.
As Daniel Torunian, former vice president of employee technology at PayPal and former CIO at Adecco, explained in in interview, “Over the past decade-plus, much of technology financial management shifted toward consumption management and expense optimization. Those disciplines remain critical, but AI adds back the need to make deliberate, multiyear strategic investment decisions.”
Seventy-four percent of respondents say demonstrating strong financial and operational discipline is a strategy priority for their tech function in 2026. AI makes that harder: Costs depend on pricing models, usage volumes, and the number of steps in a workflow. Costs can rise quickly as adoption grows, placing pressure on tech and finance leaders alike. TIAA, for example, is applying FinOps-style governance to AI, treating tokens as a managed enterprise resource by closely tracking consumption, monitoring usage patterns, and steering employees toward the most cost-effective models and prompts for each task, instead of allowing unrestricted use.2
Significant transformation might be needed to bring AI tokens into strategy and management processes. However, better financial and operational visibility can provide CIOs and their finance and business partners the information they need to determine where investment is creating value, where costs are scaling faster than expected, and where technology decisions might be increasing future cost and complexity. It can also provide the data needed to demonstrate the tech’s impact on the business.
Technical debt illustrates why this issue matters. Today, 61% of respondents estimate that the cost of wasted IT resources across people, processes, and technology—known as technical debt—is equivalent to 21% to 40% of their organization’s revenue. A similar proportion of respondents (59%) expect their technical debt overhead to be up to 20% of revenue by 2028 as they work to remediate it. Yet a meaningful share still expects technical debt to remain above 20% of revenue, as agents introduce new inefficiencies (figure 4). For CIOs, then, technical debt has become an investment allocation issue. What organizations spend today on modernization, remediation, or short-term workarounds can affect how much capacity and capital remain available for future priorities. The CIO story is not simply controlling AI consumption. It is understanding the economics well enough to make portfolio decisions about where to scale, optimize, redirect, or stop.
