As spending on cloud technologies grows, so does waste. The Flexera 2026 State of the Cloud Report found that 27% of organizations expect to spend more on cloud this year, with 17% already exceeding their budgets over the previous 12 months. The estimated share of wasted cloud spend has already crept up to 29%, undoing several years of progress, undoing several years of progress.
Companies are rapidly investing in cloud technology, but often understand less about how to use it fully and efficiently. That is not a coincidence, and it is exactly the gap FinOps is meant to close. It is also why the practice is moving out of the finance department and into the strategy conversation.
What is FinOps?
FinOps is a blended operational framework that maximizes technology value by uniting engineering (DevOps), finance, and business teams. It involves close collaboration to break down silos between tech and finance, with shared ownership of cloud spend across engineering, finance, and business teams.
What distinguishes FinOps is real-time visibility into what is being spent and why. It also treats optimization as continuous work rather than an annual cleanup exercise.
FinOps is important because cloud spending isn’t like a typical budget line. It’s more variable and usage-based, so relying on an annual review doesn’t work. Engineers can quickly create infrastructure, scale it, and tear it back down in a day, making forecasting more challenging than in the past.
What FinOps does is change who sees what. Engineers have more insight into the actual cost of a build. Finance gets numbers it can trust. Business leaders can tie spending directly to business outcomes. It removes much of the guesswork and turns cost data into a shared language rather than a monthly surprise.
As Siarhei Sukhadolski, Chief Delivery Officer & Head of Competence Center at Innowise, puts it, “For a long time, FinOps meant only cutting the bill: find the unused stuff, resize a few instances, and report the savings. That still matters, but it’s not what separates companies today. The ones pulling ahead are using FinOps to make faster, smarter calls about where their tech spend actually pays off. That’s a different job, and it shows up directly in how fast a company can move.”
How FinOps spending has changed
Only a few years ago, FinOps was mostly focused on cloud infrastructure spending. Today, that focus increasingly includes AI-specific investment. The FinOps Foundation 2026 State of FinOps Report found that 98% of organizations now manage AI spend specifically. FinOps has also expanded well beyond cloud infrastructure. It’s more common now to see FinOps coverage extend to licensing (64%), private cloud (57%), and data centers (48%). Around 90% also manage SaaS spend or plan to do so within the next year.
It’s also worth noting that the same FinOps Foundation report found that 78% of teams report directly to the CTO or CIO rather than operating solely within finance departments. To us, that reporting line says a lot. It suggests that companies increasingly see technology spending as a strategic lever rather than simply a line item to reconcile.
How AI and cloud spending are moving in the same direction
The trend toward bringing AI and a broader range of technology spending into FinOps is backed up by a Gartner report, which estimates that global IT spending will hit $6.31 trillion by the end of 2026. That’s up 13.5% from the previous year. Data center systems spending is expected to grow 55.8%, with generative AI model spending more than doubling over the same timeframe. Gartner, in a separate forecast, expects public cloud services to grow by 21.3% in 2026, with the market reaching $1.48 trillion in value by the end of 2029.
We see these figures as two sides of the same shift. AI workloads are also usage-based, which makes them more unpredictable, partly because some teams haven’t had to consider unit economics before. A fine-tuning run or a forgotten inference endpoint can quickly become one of the biggest items on a cloud bill. Most teams don’t have the tagging, forecasting, or accountability needed to catch those costs before they get out of control.
“AI spend just behaves differently from a normal application workload. It spikes, it’s hard to pin on one team or feature, and you often don’t know the real cost per outcome until the invoice lands. Companies that already had solid FinOps habits before AI adoption took off are adjusting faster because visibility and ownership were already part of how they worked. Companies that treated FinOps as an annual cleanup are the ones getting caught out.”
Siarhei Sukhadolski, Chief Delivery Officer & Head of Competence Center at Innowise
Why visibility and shared spend ownership create an advantage
Flexera numbers on discount usage point to the same issue: fewer than 50% of organizations are using the most basic cost optimization tools. The adoption of tools like reserved instances or savings plans is slow, with only 48% of companies using Google Committed Use Discounts and 45% using AWS Reserved Instances. Too many others are leaving low-risk savings on the table.
In many cases, the real problem is a lack of ownership and visibility. If no team owns the cost of a workload, no one has enough reason or enough information to choose the right pricing model. That is where the competitive gap starts to open: some companies can explain and act on their spend quickly, while others cannot.
“A mistake we still see a lot is trying to optimize the bill instead of the system behind it. Deleting unused resources saves money once. Redesigning how workloads scale, how environments get spun up, and who’s on the hook for what keeps costs under control for good. That’s the difference that turns into a real competitive edge later.”
Siarhei Sukhadolski, Chief Delivery Officer & Head of Competence Center at Innowise
What visibility and shared ownership look like
FinOps operates well when at least three structures are in place.
- Every workload or inference endpoint has a clear owner tied to its cost.
- Cost and usage data are shared and available to everyone who needs them before they have to ask.
- There is an ongoing review cadence designed around continuous optimization.
Teams that jump into dashboards before assigning ownership and establishing the data flow often end up with visibility but no accountability. Teams that start with ownership, even with basic tooling, get a different result. They tend to see savings stick instead of resetting every few months. That proper order is the single biggest predictor we have seen across cloud and AI cost engagements.
What business leaders need to know
There is a simple test a CEO or CFO should apply to FinOps. It’s whether the company can clearly state what a workload costs and whether it is worth that cost right now. Does it take finance three weeks to answer? Can the company provide an answer in real time? Are there live numbers and clear ownership behind every workload? That is what will enable leaders to make confident calls on where to invest and where to pull back.
FinOps is becoming a proxy for how well a company manages technology. With shared ownership comes high visibility. Add in continuous optimization and companies gain an advantage. These are not just cost-saving tactics. They represent operational discipline, separating those who can move quickly on AI from those who spend heavily only to find themselves still behind the rest of the pack.