SaaS spending is rapidly increasing due to market expansion and evolving pricing models
The software world has changed fast, faster than most companies can keep up with. New categories of SaaS (Software-as-a-Service) solutions are now flooding enterprise systems. It’s not just IT departments deploying enterprise resource planning software anymore. It’s tools for niche use cases across every vertical: data cloud platforms like Databricks and Snowflake, observability tools like Datadog, New Relic, and Splunk. These platforms didn’t exist a few years ago. Now, they’re embedded in core operations.
The shift to subscription and consumption-based pricing has added fuel to the fire. There’s no upfront capital expenditure anymore, it’s pay-as-you-go. That sounds efficient. But it also means that software is far easier to acquire… and much harder to manage. The result: bloated software environments. You get overlaps, duplication, and a lot of shelfware, products paid for but barely used. Procurement teams are chasing renewals across different platforms. Tracking who’s using what, and at what rate, has become a real problem.
For leaders, the challenge right now is less about stopping innovation and more about simplifying it. A fragmented SaaS ecosystem can’t scale efficiently. You need better visibility into usage and ROI. Because what’s creeping up on companies isn’t the cost of a single app, it’s the total weight of too many tools doing the same job, charging high monthly premiums with unchecked growth.
According to a recent survey by West Monroe (June 2023), nearly 50% of organizations saw their software licensing and subscription costs increase by more than 10% over the past year, just from contract renewals and new implementations. That’s a sharp rise, and most companies weren’t planning for it.
CIOs and CFOs need to be aligned. This isn’t only IT’s problem. The expanding SaaS stack affects the operating model. It impacts budgets, resource allocation, and long-term stability. Expecting that tool sprawl will regulate itself doesn’t work. Executives have to own this issue before it compounds.
Bhave, an expert referenced in the report, put it clearly, none of these complex, high-spend categories existed just a few years ago. The landscape is expanding, and the rules aren’t keeping up. Let’s not pretend it’s under control. It requires deliberate structure. Strategic governance. And a focus on real outcomes, not just shiny new software.
Generative AI integration is inflating software and infrastructure costs
Generative AI is moving fast, and enterprise adoption isn’t far behind. Software vendors have rushed to embed AI capabilities into their platforms: coding assistants, smart search, knowledge tools, and autonomous agents for routine tasks. The positioning is clear, these features promise efficiency and competitive edge. But they also come with a price tag that most teams still don’t fully understand.
Integrating Gen AI into software isn’t just a simple plug-in. It demands serious computing power. It increases the amount of storage needed. It raises the frequency of API calls. That pushes infrastructure spending up quickly. More importantly, it makes overall costs harder to project. Many procurement teams go in expecting manageable increases. What they’re seeing instead is outpacing initial budgets by a wide margin.
According to Flexential, a leading IT services firm, organizations running generative AI workloads in the cloud are facing costs five to 10 times higher than anticipated. That’s coming from Brian Anderson, Senior Director of Product Management, Hybrid Cloud at Flexential. And he’s not calling them one-off cases, he’s calling them the pattern. These overruns are routine and widespread.
The problem is that they’re entering the AI space without fully accounting for the operational impact it has on cloud-controlled costs. It’s not just the software licenses you’re paying more for. You’re also absorbing heavier infrastructure usage, data transfer fees, and compliance configurations that weren’t priced in at the start. These things add up, and they do it fast.
BCG’s research confirms this. Their report shows that boosting the scalability and performance of AI-powered systems results in higher cloud bills straight across the board. Even companies practicing solid cloud governance through FinOps frameworks are seeing their cost models break under the weight of emerging AI workloads.
As adoption spreads, C-suite leaders must revisit cost assumptions. You can’t build AI capability on top of an unmanaged infrastructure baseline. Smart executives will demand real accountability from vendors, not just performance metrics, but clarity in pricing, and transparency about consumption impact. Without that, AI’s long-term ROI becomes questionable.
The opportunity is real. But so is the unintended complexity. Leaders who understand both will have the edge. Those that don’t will underestimate the financial drag buried inside the promise of AI.
Tracking and managing SaaS procurement has become increasingly challenging, hindering cost control efforts
Buying software has become too easy. That sounds like progress, but it comes with serious consequences. With cloud marketplaces and SaaS licensing models that activate with a click, organizations are onboarding tools without proper controls. The early phase of procurement feels frictionless, but clarity fades fast as systems and stakeholders multiply.
Most companies today are dealing with dozens, sometimes hundreds, of different SaaS vendors. Many of them have completely independent pricing schemes, usage terms, and renewal cycles. According to Bhave, procurement complexity stems from this fragmented ecosystem, where managing 30, 40, or even 50 different software relationships becomes the norm. None of these providers operate under standardized models, and few are transparent about how consumption is measured or billed.
That creates an administrative problem. Teams can’t keep up with licensing, renewals, or usage audits. Software overlap becomes common. Redundant purchases go unnoticed. Products bought for one department end up shelved by another. The cost of unmanaged sprawl starts to show up in audit findings and budget reviews, but it’s often too late to make smart course corrections.
The deeper issue is the structural gap between procurement policy and actual SaaS operations. Finance and IT may think software is under control because of approval workflows or quarterly reviews. But the reality is that decentralized procurement and decentralized usage don’t map well together. A license may be bought by one team but remain unused by others. That disconnect makes optimization nearly impossible unless leaders intervene directly.
This is not a software adoption problem, it’s an oversight problem. And if you’re in the C-suite, it’s your responsibility to clarify ownership. Whether through better procurement governance, integrated tooling for license tracking, or consolidating vendors under managed agreements, the priority now must be clear operational visibility.
There’s no value in ease of purchase if it leads to loss of control. SaaS has evolved faster than most enterprise processes. That gap is where money leaks out, often unnoticed. Executives willing to close that gap will strengthen both operational discipline and cost efficiency. The rest will keep overspending without realizing it until quarterly costs spike, and by then, it’s just damage control.
Organizations must implement strategic solutions to rein in rising SaaS spending
Software costs aren’t going to self-correct. The complexity now baked into most SaaS environments needs intentional strategies, ones that start at the executive level. Right now, too many companies are reacting to cost spikes instead of managing them with discipline. There’s no shortage of tools. The problem is how they’re used, evaluated, and aligned with real business value.
A clear first step is vendor rationalization. Not every software provider should be on your approved list. The saturated market offers high-functioning alternatives beyond the dominant players, tier-two providers with more flexible pricing and better partnership models. If you’re only buying from the biggest names, you’re likely overpaying and under-leveraging. Smart CIOs will prioritize long-term partners who deliver value without locking the business into unnecessarily complex or high-cost ecosystems.
Oversight is also critical. That means actively cutting redundant tools, consolidating overlapping functionalities, and ensuring underused platforms are decommissioned. Relying on outdated legacy systems drives up compute and storage costs, especially when those systems weren’t built for cloud-scale demand. BCG recommends refactoring or modernizing these legacy stacks to lower mainframe consumption and reduce dependency on expensive infrastructure.
Another major opportunity: rethink infrastructure. Many companies are paying premium rates for cloud storage tiers they don’t actually need. Shifting workloads to lower-cost tiers, where possible, improves performance-to-cost ratios immediately. Pair that with a stronger commitment to open-source solutions where enterprise-grade options exist, and the savings accelerate without compromising capability.
This is about building a foundation that can actually support growth. BCG lays it out in a three-pronged approach: partner smarter, reduce waste, and optimize performance. That’s how you get control back.
The FinOps Foundation is also pushing for industry standards in SaaS billing, with early support from large providers. But as Bhave notes, that effort still has a long runway ahead. Most organizations are dealing with dozens of vendors, each with unique pricing models. No internal team is resourced to track that manually. Automation, strong internal frameworks, and vendor accountability are essential going forward.
Executives who recognize SaaS as a priority category for financial governance have an opportunity to lead cost management from the top. Waiting for software markets to become manageable on their own isn’t a solution. Doing nothing guarantees inefficiency. Taking ownership drives clarity, accountability, and long-term savings.
Key takeaways for leaders
- SaaS complexity is driving unsustainable spend: The rapid growth of specialized tools and pay-as-you-go pricing is causing uncontrolled software proliferation, redundancies, and underused licenses. Leaders should audit software usage and cut shelfware to protect budgets.
- AI features are inflating infrastructure costs: Gen AI add-ons are pushing cloud usage far beyond expectations, raising storage, compute, and compliance costs. Executives must factor AI-related infrastructure impact into procurement decisions to avoid budget shocks.
- Poor procurement visibility leads to waste: With decentralized purchasing and dozens of vendors using different billing models, software oversight is slipping. Leaders should improve transparency across licensing and vendor relationships to regain financial control.
- Strategic changes are needed to curb SaaS spend: BCG recommends forming partnerships with cost-effective vendors, eliminating duplicate tools, and optimizing infrastructure. Executives should embed these practices into FinOps and IT operations for long-term savings.
