SaaS vendors are sharply raising subscription prices, putting CIO budgets under pressure
SaaS pricing is going up, fast, and it’s pushing IT budgets to the edge. We’re not talking about subtle changes either. According to Gartner’s Mike Tucciarone, subscription costs from major SaaS vendors jumped between 10% and 20% this year alone. That compares to an IT budget growth projection of just 2.8%. And in some extreme cases, especially with vendors owned by private equity firms, the increases have hit an almost absurd 900%. That’s not a pricing adjustment. That’s a total reset.
This shift isn’t driven by inflation anymore. Inflation’s calmed down. What we’re looking at now are structural changes in the way SaaS is packaged, priced, and sold. Vendors are moving aggressively. They’re switching to consumption-based pricing models, tweaking regional price points, and defending it all under the banner of “innovation and generative AI investment.” Which is partially true, AI isn’t cheap. Compute-heavy workloads, particularly those driven by GPUs, are squeezing vendor margins. But the impact this has on end customers is undeniable: less predictability, more cost, and a lot more budget friction.
If you’re a CIO or CFO reading this, you’re already familiar with the balancing act. You’re building for the future, investing in AI, modernizing infrastructure, but the tools meant to support that growth are pulling hard on the same budget you’re trying to innovate with. This isn’t a temporary issue. It’s a new market dynamic. Knowing how to respond, especially in negotiation and procurement, is now a competitive advantage.
Mike Tucciarone, Vice President and Analyst at Gartner, puts it clearly: “We are seeing significant and broad-based cost increases across the enterprise SaaS market. This is creating notable budgetary pressure for many organizations.” Also worth noting: private equity software acquisitions jumped 28% in 2024. That’s a major signal for where SaaS ownership, and pricing, might be heading next.
If you’re not revisiting your SaaS strategy this year, you’re already behind.
Mission-critical SaaS products, including ERP, CRM, and data platforms, are experiencing disproportionately steep price hikes
It’s one thing when productivity tools get more expensive. It’s something else when your mission-critical services, like ERP and CRM platforms, start hitting you with aggressive pricing. That’s what’s happening now across the board. The systems your business can’t function without are getting the steepest price increases. And migration? That’s the kicker. Switching to a new system is expensive, time, money, complexity, so vendors know you’ll stay.
Guillaume Aymé, CEO of Lenses.io, highlights the problem clearly: SaaS consolidation is driving this trend. Big tech firms and private equity players acquire smaller, specialized SaaS providers, then raise prices, knowing full well that migrating off those platforms would be costly and disruptive. And they’re right. Most businesses don’t have the resources, time, or headspace to manage a seamless transition while also scaling AI projects and managing operations.
This is pricing power at play. Vendors are betting that you’ll take the hit because the alternative is worse. With AI rollouts, data modernization efforts, and other transformation strategies already in progress, CIOs are in a corner. You can’t stop momentum, but your foundational costs are escalating.
For C-suite leaders, this is a critical moment to rethink vendor lock-in, procurement timelines, and how modular your systems really are. If the cost of switching is too high, the cost of staying becomes a slow bleed. Now’s the time to figure out what’s non-negotiable in your stack, and what can be swapped out or re-architected for greater resilience.
Guillaume Aymé lays it out plainly: “Businesses are just trying to figure out their AI strategy… asking them to do a migration is going to be very difficult.” That pressure compounds when budget is split between innovation and operations. The vendors know this. That’s why they’re raising prices when you can least afford disruption.
You don’t fix this with Band-Aid negotiations. You fix it with architecture-level optionality and long-term roadmap thinking.
Data infrastructure costs are surging due to complex, consumption-based billing models and increased AI workload demands
Data workloads are scaling fast. That’s expected, especially with AI pushing deeper into enterprise tech stacks. But what’s catching CIOs off guard is the pricing structure behind the platforms supporting that scale. We’re seeing a shift away from predictable, seat-based SaaS pricing toward more fluid, consumption-based models. The result? Data infrastructure costs for platforms like cloud data warehouses, lakehouses, and analytics tools have surged between 30% and 50% in the past year alone.
Kunal Agarwal, CEO and Co-founder of Unravel Data, points out two key drivers behind this rise. First, compute-heavy AI workloads require more infrastructure, especially GPUs, which increases vendor operating costs. Second, many organizations still lack clear visibility into actual usage. Without strong cost observability, companies end up paying for unused resources, inefficient queries, and duplicated processes. For enterprises operating at scale, this creates massive waste.
Consumption-based pricing seems flexible, but it often creates budget unpredictability. One month, costs appear under control. The next, a spike in data processing, influenced by AI model training or pipeline extensions, sends your bill skyrocketing. On top of that, some vendors are quietly moving previously standard features into premium tiers, effectively increasing the base subscription price without improving core functionality.
For business leaders, this is a visibility and control issue. Controlling infrastructure cost isn’t just a finance problem, it’s an operational one. The organizations that come out ahead in this environment are the ones treating data infrastructure not as a passive utility, but as a product that requires active, continuous oversight. This includes baseline spend analysis, workload shaping, and consumption monitoring in real time.
Kunal Agarwal says it directly: “Unlike traditional SaaS, where you’re paying for seats, these platforms bill based on consumption, making costs highly variable and difficult to predict.” As AI becomes more central to how companies operate, these unpredictable infrastructure costs will only become more sensitive to poor management.
Broader SaaS inflation, fueled by evolving AI and cloud infrastructure needs, is affecting organizations of all sizes
SaaS inflation isn’t targeting any one sector. It’s spanning industries and company sizes, from startups to global enterprises. At the heart of the issue are rising costs related to AI adoption, GPU demands, cloud service pricing changes, and adjustments from hyperscale vendors (like AWS, Google Cloud, and Azure). It’s all connected. And SaaS vendors aren’t absorbing these pressures, they’re passing them through to customers.
Ed Barrow, CEO and Co-founder of Cloud Capital, puts it simply: “SaaS inflation is real and broad. It’s hitting startups, midmarket, and enterprises alike.” That’s not an isolated observation, it’s a pattern. As vendors bake in AI-powered enhancements to their products, from copilots to automated workflows, the backend processing requirements increase. These need powerful hardware and specialized infrastructure, leading to tighter margins that vendors offset through higher prices.
At the same time, cloud infrastructure providers have made their own policy and pricing adjustments. That includes changes to data egress fees, minimum usage commitments, and reserved compute terms. For SaaS providers, these changes tighten their cost structures, which again trickles down to end users as price increases or newly segmented SKUs.
CIOs and CFOs should be tracking how AI adoption, both internally and within the SaaS tools they use, is impacting their overall tech spend. This isn’t just a function of volume or headcount. It’s about understanding what portions of your bill are tied to new value, and what portion is just inflated cost passed through supply chains.
You don’t need to slow down adoption, but you do need to know where inflation is hiding in your software contracts. The companies equipped with that visibility protect their margins, even as everyone else’s costs keep rising.
Ed Barrow’s message is clear. If you’re scaling modern capabilities, especially AI-powered tools, you have to assume the operational costs underneath are changing quickly. And they are.
CIOs must adopt proactive, multi-faceted strategies to manage and mitigate rising SaaS expenses
SaaS costs are rising, and they’re not going back down anytime soon. But this isn’t a situation where enterprises are powerless. There are defined, controllable actions CIOs can take to reduce exposed risk and regain financial flexibility. It starts with treating IT infrastructure, especially data platforms, as something you actively manage, not something you set and forget.
Kunal Agarwal, CEO and Co-founder of Unravel Data, says many enterprises are still leaking money through poorly managed infrastructure. In his assessment, anywhere from 20% to 40% of typical data infrastructure spend is wasted, from idle resources to inefficient queries and unnecessary job duplication. That’s not just dead weight. It’s budget that could be redirected toward AI initiatives or real innovation. Identifying and reclaiming that waste is a fundamental step toward cost control, and more importantly, cost optimization.
But this goes beyond usage audits. CIOs also need procurement discipline. Gartner’s Mike Tucciarone emphasizes the importance of locking in long-term agreements before pricing resets or product tier shifts take effect. With market volatility high and SaaS vendors holding the stronger negotiation position, renewal timing and deal strategy matter more than ever. Being reactive costs you leverage, planning ahead restores it.
Guillaume Aymé, CEO of Lenses.io, offers another perspective: avoid single-vendor lock-in wherever possible, especially in mission-critical environments. Larger vendors position all-in-one solutions as attractive simplifications. But that consolidation often leads to rigid contracts, higher switching costs, and fewer options down the line. Modular platforms, where you maintain integration flexibility, are a smarter hedge against unpredictable pricing shifts. Emerging AI agent infrastructure and standardized protocols make this kind of distributed architecture increasingly viable without undermining the user experience.
There’s also a growing shift in mindset among forward-leaning C-level executives. The goal isn’t just cost savings, it’s strategic spend. Budget optimization that opens up space to move faster on AI, data intelligence, and user productivity. You maintain operational stability while driving transformation.
Mike Tucciarone underscores this shift: “CIOs must rigorously assess their IT negotiation intelligence, demonstrate they’re informed buyers, and leverage market data to secure better outcomes.” And those better outcomes come when you manage SaaS, contracts, utilization, configuration, as a living asset, not a sunk cost.
Right now, action beats analysis. Those who move deliberately, who secure long-term price stability, diversify risk, and cut waste, are the ones who’ll keep momentum while everyone else contends with complexity.
Key highlights
- SaaS pricing is accelerating past IT budgets: Major SaaS vendors have raised prices between 10% and 20%, with private equity-backed providers spiking costs up to 900%. Leaders should reassess procurement leverage and prioritize smarter contract negotiations to counter market imbalance.
- Mission-critical systems face the steepest hikes: ERP, CRM, and data platforms, essential systems with high switching costs, are being targeted with aggressive pricing. Decision-makers should evaluate modular alternatives and avoid overdependence on single-vendor ecosystems.
- Data infrastructure spending is increasingly unpredictable: Consumption-based pricing combined with AI workloads has driven data platform costs up by 30% to 50%. CIOs should invest in usage transparency and workload optimization to identify waste and reduce volatility.
- SaaS inflation is market-wide and AI-driven: Rising cloud costs, hyperscaler policy changes, and GPU-heavy AI features are inflating prices across all company sizes. Executives need to monitor cost drivers behind core tools and adjust budgeting models to account for vendor-side AI investments.
- Proactive cost strategies are now a must: Identifying waste, locking in long-term contracts, and diversifying vendors can protect against runaway expenses. Leaders should treat IT infrastructure and SaaS spend as active, managed assets aligned with growth priorities.
