The 5 FinOps Challenges Holding Organizations Back

Cloud, AI and data are transforming how organizations operate. But they're also creating a new challenge: understanding where technology spend is going, who owns it, and whether it's delivering value.

Costs are now spread across multiple cloud providers, data platforms and AI services. New AI pricing models, token consumption and usage-based billing are making technology spend harder to predict and govern.

Recent research in Flexera's State of ITAM 2026 report highlights the scale of the issue. Only 31% of organizations have visibility into AI software, while 59% report increasing levels of wasted AI spend. At the same time, 84% say tracking and adopting AI applications is now a major challenge.

Limited Visibility Across Technology Spend

Many organizations lack a complete view of cloud, AI and data costs across the business. When spend is fragmented across teams, platforms and budgets, understanding what's driving costs becomes increasingly difficult.

The challenge is even greater with AI, where visibility remains low across many organizations.

Rising Costs, Unclear Value

Technology spending continues to grow, but proving business value is often harder.

The goal isn't simply to cut costs. It's to ensure investments in cloud, AI and data are delivering measurable outcomes and supporting business priorities.

Software Waste Remains a Hidden Cost

Unused subscriptions, duplicate applications and underutilized licenses continue to drive unnecessary spend.

While organizations focus on cloud costs, software optimization often presents one of the largest opportunities for savings and efficiency.

AI Costs Are Growing Faster Than Governance

AI introduces new cost models and new risks.

Without clear ownership, organizations can struggle to manage AI consumption, control spending and demonstrate value. With 59% of organizations reporting increased wasted AI spend, stronger governance is becoming essential.

Effective AI Cost Management helps organizations:

• Understand where AI spend is occurring
• Identify waste and optimization opportunities
• Improve accountability
• Forecast costs more accurately
• Ensure AI investments deliver business value

FinOps Is Still Too Reactive

Many teams spend their time analysing last month's bill rather than preventing next month's overspend.

The most mature organizations are moving from reactive reporting to proactive optimization, using data and insights to forecast costs, identify risks and make better investment decisions.

From Visibility to Value

As cloud, AI and data investments continue to grow, visibility alone is no longer enough.

Organizations need the ability to understand costs, improve accountability and connect technology spending to measurable business outcomes.

Those that can successfully combine FinOps, AI Cost Management and technology governance will be best positioned to control costs, optimise investments and maximise the value of their cloud and AI strategies.