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The IT Investment Paradox: Why Bigger Budgets Are Creating Slower Decisions

Eugene Khvostov
Apptio

It's the paradox at the heart of enterprise IT in 2026: teams secure a record-level budget, but instead of immediately innovating and evolving with new tools and seeing results, decision-making has slowed to a crawl. They're flying blind, unable to connect massive investments in areas like AI and cloud to the one thing the business actually cares about: value.

For technology leaders, 2026 is the year to bring business context and value back into the IT conversation. Apptio just released its 2026 Technology Investment Management Report, which revealed 74% of organizations are increasing their IT budgets, yet there is a staggering disconnect. While priorities are clear — with 94% of leaders focusing on cybersecurity and 91% on AI — nearly half (49%) struggle with cloud cost volatility and 43% are concerned about the costs of AI/ML. As budgets scale, the sheer complexity of the IT landscape is outpacing the tools to manage it, making it difficult for leaders to obtain the forecasting needed to make confident decisions and translate investments into results. This isn't just a temporary challenge; it's a sign of a much deeper evolution.

By building IT Financial Management (ITFM) resilience, shifting from project-based to product-based operating models, and incorporating AI-powered financial intelligence, an agile, outcome-driven approach is possible, helping teams work efficiently and eliminate ROI uncertainty. The old playbook for managing technology is outdated, and a new one is taking its place, defined by three seismic shifts that are already separating the leaders from the laggards.

The Confidence-Capability Gap

Reliance on outdated tools is directly impacting leader confidence and slowing down critical decisions, presenting a significant, untapped opportunity for organizations. The report found that 90% of leaders say uncertainty about ROI has a moderate to major impact on their investment decisions — an increase from 85% in 2025. This doubt is fueled by a disconnect between perception and reality. While nearly 59% of ITFM professionals believe their forecasts are highly accurate, only 35% use purpose-built ITFM tools. Nearly 47% still rely on generic ERP systems, with others still dependent on manual spreadsheets.

Disconnected systems and unclear metrics compound the confidence problem. Distrust in data (84%) and persistent data silos (80%) make it even harder to find the insights necessary to justify spend. These manual and generic tools introduce delays and inaccuracies that limit scalability, making it difficult for leaders to achieve the transparency and agility stakeholders now expect. When nearly every leader questions ROI, investment decisions stall, and the gap between what leaders think they know and what they can prove continues to widen. By integrating IT Services Management (ITSM) anchored in Technology Business Management (TBM) practices, enterprises can increase visibility and understand the true ROI across labor, licenses and infrastructure.

Building ITFM Resilience

Many teams continue to struggle with visibility, alignment and forecasting, creating not only operational and confidence gaps but also major business risks, including runaway cloud spend, stalled innovation, and diminished stakeholder confidence. Closing the confidence gap requires more than just optimism; it requires building ITFM resilience through deliberate, strategic action.

First, start with the basics. Establish foundational capabilities like complete cost transparency and accurate forecasting. Second, modernize the toolkit to automate data integration and finally reduce the risky reliance on spreadsheets, as they create delays and impact decision-making capabilities. From there, adopt dynamic planning, moving beyond rigid annual cycles to an agile, iterative model that can keep pace with the business and evolve alongside it. Finally, build stakeholder alignment by engaging finance, IT, and business leaders with a common, data-driven language for IT spend.

ITFM maturity isn't about perfection — it's about progress. Taking these steps creates a single source of truth that can shift IT from operating as a siloed cost center to becoming a strategic and connected business asset driving innovation and growth.

The Shift from Projects to Products

The data reveals why a fundamental shift from project-based to product-based operating models is no longer optional — it's critical. The pressures forcing this change are already clear. With FinOps teams growing in both size and cross-functional diversity (61% are now over six people) and AI funding becoming more dynamic (67% of organizations are reallocating internal capital), the rigidity of static, annual project plans has become a primary roadblock to innovation. Without strong FinOps fundamentals — visibility, forecasting, and accountability — organizations risk runaway cloud spend, delayed innovation and diminished stakeholder confidence.

To manage this new reality, teams must operate like product development engines, with defined sprints, clear OKRs, and intense scrutiny on business performance to unlock more agile ways of working and allow funding and resources to track product success in real time. This is where integrating ITSM with TBM becomes critical. The integrated framework provides the real-time visibility needed to track product performance, understand ROI across labor, licenses and infrastructure, and ultimately unlock a more accountable, outcome-driven way of working that closes the gap between strategy and execution.

AI as the Enabler for Real-Time Intelligence

This agile, product-centric model is impossible without an equally agile approach to financial data — one powered by AI. The AI era requires near real-time, integrated financial and operational information to make sound decisions at high speed. AI-powered financial intelligence is the key that eliminates data silos, connecting disparate costs to direct business value and democratizing insight for every user. By pairing this powerful financial insight with agile ways of working, IT leaders and their teams can finally close the confidence-capability gap and take definitive control over their decisions.

The path forward for technology leaders is clear: those who cling to spreadsheets and rigid annual plans will fall behind and become paralyzed when it comes to proving business value. The leaders who will thrive in 2026 and beyond will be those that focus their priorities on building ITFM resilience, shift towards a product-centric mindset, and leverage AI to transform data into strategic insights. By making these changes, IT leaders can close the gap between budget and value, reclaim their role as essential drivers of business innovation, and gain their confidence back for good. 

Eugene Khvostov is Chief Product Officer at Apptio

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This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

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The IT Investment Paradox: Why Bigger Budgets Are Creating Slower Decisions

Eugene Khvostov
Apptio

It's the paradox at the heart of enterprise IT in 2026: teams secure a record-level budget, but instead of immediately innovating and evolving with new tools and seeing results, decision-making has slowed to a crawl. They're flying blind, unable to connect massive investments in areas like AI and cloud to the one thing the business actually cares about: value.

For technology leaders, 2026 is the year to bring business context and value back into the IT conversation. Apptio just released its 2026 Technology Investment Management Report, which revealed 74% of organizations are increasing their IT budgets, yet there is a staggering disconnect. While priorities are clear — with 94% of leaders focusing on cybersecurity and 91% on AI — nearly half (49%) struggle with cloud cost volatility and 43% are concerned about the costs of AI/ML. As budgets scale, the sheer complexity of the IT landscape is outpacing the tools to manage it, making it difficult for leaders to obtain the forecasting needed to make confident decisions and translate investments into results. This isn't just a temporary challenge; it's a sign of a much deeper evolution.

By building IT Financial Management (ITFM) resilience, shifting from project-based to product-based operating models, and incorporating AI-powered financial intelligence, an agile, outcome-driven approach is possible, helping teams work efficiently and eliminate ROI uncertainty. The old playbook for managing technology is outdated, and a new one is taking its place, defined by three seismic shifts that are already separating the leaders from the laggards.

The Confidence-Capability Gap

Reliance on outdated tools is directly impacting leader confidence and slowing down critical decisions, presenting a significant, untapped opportunity for organizations. The report found that 90% of leaders say uncertainty about ROI has a moderate to major impact on their investment decisions — an increase from 85% in 2025. This doubt is fueled by a disconnect between perception and reality. While nearly 59% of ITFM professionals believe their forecasts are highly accurate, only 35% use purpose-built ITFM tools. Nearly 47% still rely on generic ERP systems, with others still dependent on manual spreadsheets.

Disconnected systems and unclear metrics compound the confidence problem. Distrust in data (84%) and persistent data silos (80%) make it even harder to find the insights necessary to justify spend. These manual and generic tools introduce delays and inaccuracies that limit scalability, making it difficult for leaders to achieve the transparency and agility stakeholders now expect. When nearly every leader questions ROI, investment decisions stall, and the gap between what leaders think they know and what they can prove continues to widen. By integrating IT Services Management (ITSM) anchored in Technology Business Management (TBM) practices, enterprises can increase visibility and understand the true ROI across labor, licenses and infrastructure.

Building ITFM Resilience

Many teams continue to struggle with visibility, alignment and forecasting, creating not only operational and confidence gaps but also major business risks, including runaway cloud spend, stalled innovation, and diminished stakeholder confidence. Closing the confidence gap requires more than just optimism; it requires building ITFM resilience through deliberate, strategic action.

First, start with the basics. Establish foundational capabilities like complete cost transparency and accurate forecasting. Second, modernize the toolkit to automate data integration and finally reduce the risky reliance on spreadsheets, as they create delays and impact decision-making capabilities. From there, adopt dynamic planning, moving beyond rigid annual cycles to an agile, iterative model that can keep pace with the business and evolve alongside it. Finally, build stakeholder alignment by engaging finance, IT, and business leaders with a common, data-driven language for IT spend.

ITFM maturity isn't about perfection — it's about progress. Taking these steps creates a single source of truth that can shift IT from operating as a siloed cost center to becoming a strategic and connected business asset driving innovation and growth.

The Shift from Projects to Products

The data reveals why a fundamental shift from project-based to product-based operating models is no longer optional — it's critical. The pressures forcing this change are already clear. With FinOps teams growing in both size and cross-functional diversity (61% are now over six people) and AI funding becoming more dynamic (67% of organizations are reallocating internal capital), the rigidity of static, annual project plans has become a primary roadblock to innovation. Without strong FinOps fundamentals — visibility, forecasting, and accountability — organizations risk runaway cloud spend, delayed innovation and diminished stakeholder confidence.

To manage this new reality, teams must operate like product development engines, with defined sprints, clear OKRs, and intense scrutiny on business performance to unlock more agile ways of working and allow funding and resources to track product success in real time. This is where integrating ITSM with TBM becomes critical. The integrated framework provides the real-time visibility needed to track product performance, understand ROI across labor, licenses and infrastructure, and ultimately unlock a more accountable, outcome-driven way of working that closes the gap between strategy and execution.

AI as the Enabler for Real-Time Intelligence

This agile, product-centric model is impossible without an equally agile approach to financial data — one powered by AI. The AI era requires near real-time, integrated financial and operational information to make sound decisions at high speed. AI-powered financial intelligence is the key that eliminates data silos, connecting disparate costs to direct business value and democratizing insight for every user. By pairing this powerful financial insight with agile ways of working, IT leaders and their teams can finally close the confidence-capability gap and take definitive control over their decisions.

The path forward for technology leaders is clear: those who cling to spreadsheets and rigid annual plans will fall behind and become paralyzed when it comes to proving business value. The leaders who will thrive in 2026 and beyond will be those that focus their priorities on building ITFM resilience, shift towards a product-centric mindset, and leverage AI to transform data into strategic insights. By making these changes, IT leaders can close the gap between budget and value, reclaim their role as essential drivers of business innovation, and gain their confidence back for good. 

Eugene Khvostov is Chief Product Officer at Apptio

Hot Topics

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...