The most expensive technology cost is rarely the one you know about. It is the software, cloud infrastructure, AI tools, and vendor contracts quietly renewing in the background, eroding margins and compressing returns without anyone noticing.
Every month, organisations pay invoices for software nobody opens, cloud infrastructure nobody uses, and vendor contracts that have not been reviewed in years. The payments clear. The costs fold into broad technology line items. And the executives responsible for financial performance move on to problems that feel more urgent.
This is not a technology problem. It is a visibility problem. Across the 80-plus organisations we work with on the SaaSrooms platform, representing over $790 million in annual software spend, recoverable IT waste consistently accounts for 15% to 25% of total annual technology expenditure. That figure does not come from a market survey. It comes from what we find, engagement after engagement, when someone finally looks at the data properly.
For private equity deal teams and C-suite executives responsible for technology budgets, that gap has a specific and measurable cost. The question is not whether it exists in your organization. It does. The question is whether anyone has the visibility to find it.
What Enterprise Software Spend Looks Like When You Actually Examine It
Certain patterns emerge when you sit across enough technology budgets. IT and Infrastructure consistently carries the largest share of spend, exceeding $180 million across our portfolio of mid-market organisations. Productivity and Collaboration follows at $118 million and is the only category where license utilization reliably tracks above 80%, making it the benchmark against which every other category should be measured.
The gap below that benchmark is significant. Security and Compliance tools carry substantial annual spend at an average utilization rate of just 46%, meaning organisations are actively using roughly half the security coverage they are paying for. The AI and Automation category, the fastest-growing in enterprise technology today, sits at formal utilization rates below 40%. What employees are actually doing with AI tools, which the browser-level data tells a very different story about, makes that number even more revealing.
Why So Many PE Deal Teams Enter Close Without a Full IT Spend Picture
In private equity due diligence, the IT spend gap is rarely the result of carelessness. It is a structural limitation of how financial diligence is scoped. Deal teams bring considerable rigor to historical financials, forward modelling, and customer concentration risk. Technology expenditure appears in these processes as a cost input reviewed for reasonableness, not as a subject of dedicated software asset management scrutiny.
What a standard infrastructure review does not produce is a contract-level, usage-validated picture of what the target company is paying for versus what it is consuming. Recoverable technology waste routinely enters the holding period undetected, compressing the returns the acquisition was underwritten to deliver. It is a solvable problem that is consistently left unsolved because nobody applied the right lens to the data at the right time.
Annual IT Budget | Estimated Recoverable Waste (15% to 25%) | Nature of Recovery |
$80,000 | $12,000 to $20,000 | Immediate cash improvement |
$500,000 | $75,000 to $125,000 | Margin or reinvestment |
$5,000,000 | $750,000 to $1,250,000 | Meaningful EBITDA improvement |
$10,000,000+ | $1.5M to $2.5M+ | Material deal value impact |
Five Structural Reasons IT Waste Accumulates Inside Every Growing Organization
Recoverable IT spend waste is not the result of poor decisions. It is the predictable outcome of how technology purchasing compounds inside organisations over time. Across every engagement, the same five structural dynamics appear.
- Decentralized SaaS purchasing without central visibility.
Technology purchases are made at the team and department level with no single function maintaining a consolidated view of the full stack. The average organization carries active applications across eight to twelve separate budget owners, none of whom sees the complete picture. Software license redundancy builds silently and by the time it surfaces, it has been compounding for years.
- SaaS sprawl has outpaced technology governance frameworks.
The Productivity and Collaboration category alone typically carries more than ten distinct application entries per organization, each adopted independently by different teams at different points in time. Many duplicate capabilities the organization already holds under a different subscription. Nobody noticed because no governance framework required anyone to look across all of them simultaneously.
- Auto-renewal as the default contract structure.
Across the organisations we work with, the ratio of auto-renewing contracts to actively managed ones runs at roughly 1 to 94. For every contract moving through a structured renewal process, 94 others roll over automatically. Vendor business models are built around this inertia. Without active SaaS spend management, organisations fund vendor revenue growth on autopilot while their own margins absorb the cost.
- Cloud infrastructure provisioned for peak demand and never right-sized.
Cloud environments are built to handle peak load and rarely scaled back when demand normalizes. Cloud cost optimization assessments consistently surface the highest average savings per engagement of any workstream we conduct, with individual opportunities regularly exceeding $150,000 in recoverable infrastructure spend per review.
- Vendor contracts benchmarked at signing and never revisited.
Enterprise software pricing evolves continuously. A contract at fair market value three years ago may now sit 30% to 40% above what a new buyer would pay for an equivalent solution today. Without ongoing vendor contract benchmarking, organisations renew at disadvantaged rates by default, with no visibility into how far above market they have drifted.
Where Recoverable IT Waste Concentrates: What the Data Actually Shows
IT spend waste does not distribute evenly across a technology budget. It concentrates in five well-defined categories, and the financial scale of each is consistent enough across engagements to be predictive for any organization that has not yet conducted a structured review.
- Software license redundancy and stack consolidation.
The most common finding is not extravagant spending on any single platform. It is the quiet accumulation of overlapping tools across departments that were independently adopted and never rationalized against the broader stack. Jason Stern, CRO at SaaSrooms with 25 years of enterprise software experience, makes an observation that holds across virtually every engagement: the issue is rarely reckless spending. It is well-intentioned decisions made at different times by different teams that were never revisited in aggregate. Rationalization is not about cutting capability. It is about creating the operational clarity that lets an organization act with intention rather than inertia. Consolidation to the best-fit tool per category consistently produces savings of 20% to 35% on licensing expenditure in that category.
- Unused and underutilized software licenses.
Seat-based software contracts are rarely adjusted to reflect changes in headcount, role, or organizational structure. Across the organisations we track, 603,590 software licenses are currently purchased against 352,753 active users. That is 42% of all licensed seats generating cost with no corresponding business value. Not an estimate. The current state of what the data shows.
42% of all licensed seats are inactive603,590 licenses purchased. 352,753 active users. 250,000 seats generating zero business value. Source: SaaSrooms platform data, aggregated across 80+ organisations. |
- The shadow AI problem: where formal IT budgets and real employee behavior diverge.
Nowhere is the license utilization gap more striking than in AI tools. Looking at the formal IT stacks across the organisations we work with, OpenAI appears in 10 organisations with a combined 150 licenses and just 11 active users. That is a 93% dormancy rate on formally purchased AI capability.
The browser-level usage data tells a completely different story. AI adoption is not dormant. It is extensive, unmanaged, and sitting entirely outside the formal IT budget. The following is observed across organisations where browser-level tracking is enabled, over a 90-day period:
AI Tool | Orgs Observed | Unique Users | Logins (90 days) | In IT Budget? |
ChatGPT | 6 | 93 | 184,753 | No |
Microsoft Copilot | 4 | 27 | 10,061 | Partial |
Claude | 5 | 38 | 2,799 | No |
Perplexity | 2 | 13 | 3,843 | No |
Google Gemini | 4 | 23 | 2,197 | No |
Grok | 2 | 12 | 1,253 | No |
ChatGPT alone generated 184,753 browser sessions across 93 unique users in 6 organisations over 90 days. Not one of those organisations had ChatGPT in their formal software budget. The formal IT stack records AI adoption at 7%. The usage data places it at the center of daily workflows. That distance between the two represents both a significant financial governance gap and a data security and compliance exposure that most organisations have not yet quantified.
- Above-market vendor contracts and renegotiation opportunity.
Contract term renegotiation is consistently the single largest savings category we identify across engagements. Across 24 organisations, we have surfaced over $875,000 in recoverable spend from this workstream at an average of $5,151 per renegotiated contract. Individual vendor contract benchmarking exercises have uncovered opportunities exceeding $90,000 on a single vendor relationship, without changing the vendor.
- Shadow IT and untracked technology subscriptions.
The AI usage data above illustrates precisely what shadow IT management looks like in 2026. Tools accessed at significant volume, sometimes ranking among the most-used applications in an organization, that appear nowhere in the formal IT budget. The direct financial exposure is measurable. The data security and compliance exposure, particularly where AI tools are handling sensitive business information, is in many cases more urgent.
The EBITDA Case for Treating IT Spend Optimization as a Deal Variable
For private equity professionals and operating executives, IT spend optimization is a value creation matter with direct implications for deal economics and hold-period return generation. A business acquired at a 10x EBITDA multiple carrying $2 million in recoverable IT waste represents an implied valuation impact of $20 million. Surfacing and recovering it during PE due diligence is not an incremental operational improvement. It is a material investment decision that changes the economic foundation of the transaction.
Across active engagements, the savings opportunities identified through structured assessment consistently total more than $3.6 million in recoverable spend. The breakdown by category is stable enough to serve as a reliable forward benchmark:
Savings Category | Orgs | Total Identified | Avg per Opportunity |
Contract Term Renegotiation | 24 | $875,000+ | $5,151 |
License Level Optimization | 14 | $571,000+ | $8,665 |
Right-Sizing and Infrastructure | Multiple | $932,000+ | $155,438 |
Vendor Switch and Bundling | 14 | $315,000+ | $7,674 |
Total Across Engagements | 80+ Orgs | $3.6M+ | Varies by category |
Philip Allouche, Founder of SaaSrooms and a procurement professional with over 20 years of experience across Microsoft and global supply chain environments, points to a consistent gap in how organisations approach this: the data required to identify and recover this waste is always present inside the organization. What is typically missing is the process to examine it with the same discipline applied to every other material cost category. When that process is introduced before close, the conversation shifts entirely, covering valuation, the integration plan, and where value creation actually begins. That shift, from reactive cost management to proactive technology governance, is the difference between deals that perform within their underwriting and those that spend the first year correcting what diligence missed.
When IT spend analysis is integrated into the PE due diligence workstream, deal teams gain three compounding advantages: substantiated grounds for purchase price negotiation, a fully costed post-close integration savings roadmap already scoped and assigned, and the technology governance discipline that supports systematic value creation throughout the hold period.
What a Structured IT Spend Assessment Covers and How Long It Takes
A structured IT spend assessment follows a consistent methodology across five workstreams: a full software asset inventory mapped to verified usage data; vendor contract review and benchmarking against current market pricing; cloud infrastructure cost analysis with right-sizing recommendations; shadow IT identification and classification across all departments; and a prioritized IT waste recovery roadmap organized across three time horizons, 90 days, 90 to 180 days, 6 to 18 months, and 18 – 36 months.
With structured data access, a full assessment can be completed within two to three weeks. That sits well within standard PE due diligence timelines and is entirely feasible as a standalone technology cost management review at any point in the business cycle, independent of a transaction.
The Blind Spot Is a Choice. So Is Closing It.
The gap between what is purchased and what is used is not a theory. It is consistent across every engagement, every sector, and every size of organization. It becomes visible the moment the right analysis is applied to data that already exists inside the business.
For PE deal teams, that analysis belongs before close. For operating executives managing a technology budget at any scale, it belongs in the quarterly review cycle. The 42% license dormancy rate, the $875,000 in contract renegotiation savings, and the 184,753 ChatGPT sessions that never appeared in any IT budget are not edge cases. They are the pattern. The only question is what the equivalent numbers look like inside your organization, and what it costs to leave them unexamined for another quarter.
