How organisations can manage cloud spend as AI drives costs up

Australia is hitting a new wave of accelerated cloud adoption as businesses embrace AI en masse. This is leading to a flurry of investment. In fact, Australian cloud and IT infrastructure leaders anticipate the rise of AI will lead to a 15% increase in computing needs for the 2024–2025 financial year and a 17% increase for 2025–2026.

For most business leaders, AI adoption is no longer a question of if, but when. However, many are apprehensive about making large investments in this rapidly evolving technology. When the surge in cloud adoption happened over a decade ago, many businesses embraced the ‘move now, deal with it later’ approach. For some, this strategy paid off, positioning them as first to market or giving them a competitive advantage through faster innovation. But for others, the costs quickly spiralled out of control, leaving them burned by big cloud investments that failed to deliver return on investment.

Amid this new wave of AI investments and global economic uncertainty, managing costs is an absolute imperative. So, how can we learn from our past mistakes to deliver better outcomes in the race to adopt AI?

Visibility into your spending is key to delivering value

The reality is that for most organisations, there is often a gap between what businesses believe they are spending money on and what they are actually spending money on. According to IDC, back-office inefficiencies, like those within IT, cost companies anywhere from 20 to 30% of their revenue each year.

The move to cloud is often one of the largest contributors to these inefficiencies. Today, any developer can log in and spin up new services or applications with just a few clicks: no lengthy procurement process required. But with that convenience comes a growing risk of waste. As organisations shift from experimenting with AI to fully implementing it, many pilot programs and trial systems are left running in the background, forgotten but still consuming resources. This is especially costly with AI, which relies on GPU-heavy infrastructure that is both powerful and expensive.

Often, users aren’t aware of the true cost of the resources they’re using. What starts as a short-term test can unintentionally run for weeks or months, creating massive waste and blowing out budgets. Without visibility and control, these hidden costs can quickly spiral, slowing down innovation rather than accelerating it.

These soaring costs of AI and cloud adoption are exacerbated by a lack of governance and visibility into what organisations spend in the cloud. For many business leaders, the real challenge is knowing where to start in managing costs.

Using FinOps to manage costs

Fortunately, there is good news. FinOps, the industry-standard operating model for the cloud, contains a set of best practices to help companies shift their traditionally wired IT cost centre to a critical value driver with novel transparency. How do we know this? By adopting these standards, recent research shows organisations can reduce cloud costs by as much as 20–30%, transforming IT operations from a burden to a significant business asset.

These cost savings don’t just benefit the bottom line — can be reinvested to drive innovation and accelerate the delivery of key business priorities, including AI initiatives. FinOps empowers teams to optimise their use of cloud resources by providing greater visibility into cloud spend across the business, eliminating wasteful spending.

Fuelling AI initiatives through financial clarity

Through FinOps, organisations gain a structured framework to align resources in support of AI efforts, helping them understand the true cost of enabling and scaling emerging technologies. With FinOps, IT leaders can confidently justify investments, clearly demonstrating how software licences and labour contribute to operational outcomes. This not only strengthens business resilience but also boosts customer satisfaction. It enables responsible spending and supports maintaining appropriate funding levels by providing their direct impact on business performance.

In addition, FinOps helps ensure the optimisation of resources supporting AI initiatives, helping reduce waste and improve efficiency across teams. Using unit economics, IT leaders can identify which AI platforms and projects are delivering real value and adjust investments accordingly.

Building a culture of accountability and collaboration

This enhanced transparency also helps break down barriers between teams and foster a common language across the organisation. A successful FinOps implementation requires collaboration between finance, engineering and business teams to create financial accountability and maximise the value of cloud services across the business. The goal is to build a culture where everyone takes ownership of their cloud and AI usage, supported by a central group focused on best practices.

This collaborative model ensures AI investments are not only supported but continuously evaluated for performance and value alignment across the business.

Act now or risk falling behind

Change is always challenging, but failing to act could be far more costly. As AI adoption accelerates and cloud costs rise, businesses that don’t implement strong financial governance risk losing their competitive edge.

FinOps isn’t just about managing costs. It’s about ensuring that every dollar spent on AI and cloud delivers real business value. For leaders looking to adopt emerging technologies sustainably and successfully, now is the time to embed FinOps into their strategy.

*Matt Pinter is APAC Field CTO at Apptio.

Image credit: iStock.com/Verigo3d