Large companies in the United States and the United Kingdom are spending an average of 28% of their software budgets on vendor-driven upgrades, migrations, and licensing changes they would not have chosen independently, adding to technology costs and diverting resources from innovation as businesses race to adopt artificial intelligence.
The findings, published on Tuesday by software maintenance provider Origina, highlight how corporate technology spending can be constrained by decisions made by software vendors rather than by the needs of the organizations paying for their products. The report, based on a survey of more than 2,000 companies, describes these recurring expenses and operational disruptions as a “software tax”.
The burden extends beyond the direct cost of purchasing new licenses or migrating systems. Vendor-imposed changes can require engineering teams to redirect their time, force businesses to replace functioning hardware, and expose organizations to operational risks when critical systems must be modified to meet support deadlines.
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“When the alternative to an unwanted upgrade is losing support on systems the business runs on, saying yes is often a rational response,” Origina Chief Executive Tomas O’Leary said.
This statement points to a structural imbalance in the relationship between large software vendors and their customers. Companies may technically retain the option to reject an upgrade, but the prospect of losing support for essential business systems can make that choice commercially impractical.
For organizations operating complex technology environments, the decision to upgrade is not always driven by a desire for better functionality. It can instead be a requirement imposed by changing vendor policies, licensing terms, or support arrangements.
The survey found that 95% of respondents had paid for a vendor-driven upgrade they expected to worsen outcomes, while 80% said leaving a major software vendor would significantly disrupt their business.
These findings illustrate the extent to which established software relationships can limit corporate flexibility. Large organizations often build critical operations around interconnected systems, including enterprise resource planning, databases, cybersecurity tools, and other applications that support day-to-day business processes.
Replacing one major vendor can require more than purchasing an alternative product. Businesses may need to migrate data, redesign workflows, retrain employees, test integrations, and ensure that essential services continue operating throughout the transition. The complexity and cost of such changes can discourage organizations from switching providers, even when they are dissatisfied with the existing arrangement.
That dependence gives vendors considerable influence over customers’ technology spending. When a supplier changes its licensing structure, ends support for an older product, or requires migration to a newer platform, customers may have limited practical alternatives.
The result is a recurring expense that can be difficult to avoid through conventional procurement measures. Companies may negotiate favorable prices when they first purchase software, only to face additional costs later as the vendor changes its products, support policies, or commercial terms.
The problem also raises questions about how businesses evaluate the total cost of ownership of enterprise software. The initial purchase price may represent only part of the long-term financial commitment. Migration, compatibility work, staff training, hardware replacement, and recurring license expenses can substantially increase the cost of maintaining a system.
For technology executives, this means vendor selection cannot be based solely on functionality and upfront pricing. The flexibility to maintain existing systems, the duration of support commitments, and the cost of moving to alternative products can be equally important considerations.
Engineering Teams Lose Time Needed for Innovation
The consequences extend into product development and technology investment. According to Origina’s survey, 84% of respondents said senior engineering staff always or often spent time on vendor-driven software changes instead of innovation or business-focused development.
That diversion can impose an indirect cost on companies already under pressure to improve productivity and accelerate digital transformation. Experienced engineers are typically responsible for complex technical work, including system architecture, reliability, security, and the development of new capabilities. When their time is consumed by mandatory migrations and upgrades, fewer resources remain available for projects that could improve products, reduce operating costs, or create new revenue opportunities.
This comes as businesses seek to incorporate AI into their operations. Deploying AI systems often requires organizations to integrate new tools with existing software, manage data access and security, and adapt established workflows. Engineering capacity diverted to vendor-driven maintenance can make these initiatives more difficult to execute.
The survey does not establish how much AI investment has been delayed by these obligations. However, the reported diversion of engineering resources points to a broader challenge: companies may increase their technology budgets without gaining a corresponding increase in the capacity available for innovation.
Technology spending is not automatically productive spending. A company can spend more on software while allocating a growing share of its resources to maintaining vendor relationships and complying with changes that deliver limited additional business value.
In that environment, the cost of an upgrade includes not only the money spent on licenses and implementation but also the opportunities lost when skilled employees are unable to work on higher-value projects.
Vendor support deadlines are also contributing to hardware waste and additional capital expenditure. The survey found that 91% of respondents had retired fully functional hardware during the previous three years to comply with vendors’ support deadlines, sacrificing an average of 1.65 years of remaining useful life.
The finding highlights a connection between software support policies and physical infrastructure spending. A business may have equipment that continues to perform adequately, but compatibility requirements or the end of support for associated software can force a replacement decision before the hardware reaches the end of its practical life.
Such decisions can increase capital expenditure and create additional costs associated with equipment procurement, installation, data migration, and disposal. They may also complicate technology budgeting because replacement schedules become partly dependent on vendor decisions rather than the condition or operational needs of the equipment itself.
There can be legitimate reasons for replacing older hardware, including security vulnerabilities, performance limitations, and compatibility requirements. Unsupported systems can expose organizations to security and reliability risks, making continued use inappropriate in some circumstances.
The issue raised by Origina’s findings is whether replacement decisions are consistently aligned with those operational needs or whether support deadlines are accelerating spending that businesses would otherwise defer.
Premature retirement also raises questions about resource efficiency. When functional equipment is replaced before its useful life ends, organizations lose some of the value of their original investment and may incur additional costs from manufacturing, transporting, and disposing of replacement devices.
For large businesses managing extensive technology estates, the cumulative effect can be substantial.
$12.87m Average Annual Cost Highlights the Financial Burden
Origina reported that the most recent vendor-driven software change cost surveyed organizations an average of $12.87 million annually.
The figure underpins the potential scale of the financial exposure, although it should be interpreted in the context of the survey population and the company’s methodology. The supplied findings do not specify how the cost was calculated or how it varies by company size, industry or type of software change.
Nevertheless, the combination of direct expenditure, engineering time and premature hardware replacement suggests that the financial burden cannot be assessed through software invoices alone.
Companies may need to account for implementation costs, operational disruption, employee time, changes to infrastructure and the consequences of being unable to maintain an existing system on commercially acceptable terms. These expenses can be spread across multiple departments, making them harder to identify as a single category in corporate budgets.
O’Leary said the problem was largely universal and also applied to other regions, with older companies that have more entrenched technology stacks facing the greatest challenges.
Businesses with long-established systems can be particularly exposed because their operations may depend on software and hardware acquired over many years. Replacing these systems can be expensive and disruptive, while retaining them may leave the organization vulnerable to changes in vendor support and licensing arrangements.
The findings suggest that technology leaders need to assess software contracts and infrastructure plans as long-term financial commitments, rather than treating upgrades as isolated technical projects. Greater visibility into lifecycle costs, clearer support arrangements and more flexible system architectures could help companies reduce their dependence on individual vendors.
Ultimately, the reported software tax presents a challenge for businesses attempting to extract greater value from technology investment. As AI becomes a larger part of corporate spending, the ability to direct budgets and engineering resources towards productive uses will become increasingly important. If vendor-driven changes continue absorbing a significant share of those resources, companies risk spending more on maintaining their existing technology environments while limiting the capacity available to build new ones.