By Greg Holmes, EMEA Field CTO at Apptio, an IBM company
With the rapid pace of AI adoption, there has been a notable shift towards technology decisions now shaping business strategy at the highest level. One knock-on effect of this is that budgets have grown quickly, with 68% of UK organisations stating that they are managing increasing IT budgets in 2026 as revealed by Apptio’s 2026 Technology Management Report. In many cases, business units wanting to add new AI driven services is driving this cost up.
The impact of this is twofold. More funding will allow teams to take on new projects and refine existing systems, but this will also add to existing pressures to clearly articulate value and results. In a period of economic uncertainty and relentless change, organisations need to be able to implement technologies like AI and hybrid architecture while proving that every penny is delivering measurable business value.
However, this isn’t an easy job and IT teams are struggling. According to Apptio, nearly half (44%) of IT professionals cite uncertainty about returns as having a major impact on their ability to make investment decisions which can slow progress and growth. Two issues often at the heart of this are a lack of visibility and a doubt around data accuracy. So, how can technology leaders overcome these barriers to get a firmer grasp over their IT spend and manage c-suite expectations?
Data Uncertainty
The foundation of any ROI strategy is reliable data. Without it, it’s nearly impossible to prove the results of any investment or project. Despite this 40% of UK businesses report a distrust of data sources as one of the most pressing challenges impacting confidence. This isn’t just a technical problem; it’s a critical business risk that creates a “credibility gap” for leaders. Often the data used to prove ROI for an upcoming project is not an operational source that can be used during development or in production to track achievement of business value.
Fears over data inaccuracy often stem from disconnected systems and manual reconciliation efforts. When cost data from cloud bills to project management tools exist in silos, the manual effort required to stitch them together inevitably introduces errors and inconsistencies.
Consequently, when teams are questioned on specifics, they can’t drill down into the details with confidence. If the base numbers are uncertain, any ROI calculation becomes a work of fiction, making it impossible to confidently prove the value of an investment. To combat this IT teams must prioritise individual accountability, integration and implement regular audits to improve data accuracy.
A Lack of Transparency
Once you know your data is accurate, you then need a full view of your tech stack, which can be tricky. As technology spend continues to sprawl and new innovations enter the market, many businesses are incorporating fresh projects and systems at immense speed. From a competitive perspective, this can help create an edge but from a visibility point of view, it adds layers of complexity.
Apptio data shows that only 30% of UK organisations have a clear view of their AI-specific spend, with 63% of FinOps teams (a framework that maximises business value from cloud spending) still relying on manual processes for managing cloud costs. What does this mean? No single source of trust, an inability to measure AI’s true ROI and added difficulties when it comes to identifying and scaling successful initiatives. Also many technology teams are trying to do this without the business data showing what outcomes are achieved – meaning they are blind to the actual value.
The solution requires a paradigm shift from viewing technology as a cost centre to managing it as a value-creating engine. Achieving clear, comprehensive visibility is an essential step toward regaining control. This starts with better integration of technology costs, unifying data from disparate sources like cloud providers, on-premises systems, and SaaS applications. A full view provides the context needed to move beyond raw cost data, and IT teams can then implement cost allocation models that show exactly which business units are consuming which resources and at what cost, making it easier to evaluate ROI.
Final Thoughts
Regardless of industry, boards and CFOs are demanding clear value for their tech investments. To make this job easier for technology leaders, it is key that they are taking steps to ensure they have the data and visibility to demonstrate the impact of every investment and how it is contributing to wider business goals. By focusing on connecting systems, increasing data accuracy and transparency, this can enable teams to highlight progress and tweak strategies as needed, so that they achieve business value.