In an environment of connected, distributed systems and AI capabilities, other factors carry more weight than the purchase price.
By: Dave Dimlich
President of SD3IT
When organizations are making technology investments, it’s natural to look first at the initial price. After all, budgets are tight, procurement teams may feel pressure to demonstrate savings and most vendors are ready to make price a central part of their pitch. But that first look shouldn’t be your last.
A purchase order will tell you the acquisition cost, but it doesn’t tell you what it will cost to operate, integrate, maintain and eventually replace. There are also other important factors to consider, including mission fit, the interoperability of the technology with current systems and a solid estimate of what the lifecycle costs will be.
Take, for example, a seemingly straightforward hardware purchase. Gartner estimates that hardware acquisition accounts for only about 20% of implementing a technology, with the other 80% spread out among factors such as management, maintenance, support, energy consumption, downtime, training and ongoing expenses. And that’s for a routine expenditure that basically goes as planned. What happens when more complex investments with more moving parts go awry?
A lower-priced product can become the more expensive option when it requires additional infrastructure, creates integration challenges or fails to deliver the capabilities an organization actually needs. Conversely, of course, a solution that costs more upfront can produce substantial savings over its useful life. The challenge is in weighing all the factors that go into total cost of ownership (TCO) before making a decision.
Penny-wise and pound-foolish is a trope about as old as the English language, but it still applies in a lot of situations, not least when it involves IT projects where the second half of that phrase can add up to millions.
AI Shows the Importance of Calculating TCO
Artificial intelligence, an increasingly common feature in almost every enterprise, provides a couple of useful examples of why organizations need to look beyond an upfront price.
For one thing, many AI pilots typically never make it into production, according to a host of studies that found varying failure rates—all of them high. A 2025 report by MIT NANDA found 95% of generative AI pilots failed to achieve measurable impact. An IDC study found that 88% of AI proofs-of-concept don’t reach production. And a RAND Corp. analysis found a failure rate for AI projects of 80%, double that of non-AI projects.
In many cases, these projects could be viewed as educational investments in the future, since AI is a new technology with a lot of unknowns and pilots are intended to see what works and what doesn’t. But it also underscores the importance of ensuring that technology investments fit the mission, whether they involve AI or not. Choosing a lower-cost model without evaluating its capabilities, security characteristics and operational requirements can create a false economy. A model that performs poorly on a critical task may require additional processing, more human intervention or costly rework.
AI, particularly agentic AI, also offers another example of how costs can unexpectedly get out of hand.
The way AI works can quickly outstrip a traditional, predictable model of budgeting for a software implementation, such as SaaS. AI interacts with other systems and data stores, often on its own in the case of AI agents. The costs of data preparation, training and system integration need to be accounted for because they can grow quickly. And AI can also introduce escalating token costs that organizations may not see coming, especially if they are new to AI.
Initial costs for agentic software range from zero for free open-source models to enterprise prices for monthly subscriptions costing several thousand dollars to one-time fees of more than a million. But those fixed costs can be deceptive because they don’t account for the inference costs that result from token fees. Input tokens generally range from about 15 cents to $5 per million, and output tokens, which require more processing, can run about 60 cents to $25 per million. With AI agents, which work autonomously at machine speed and of their own volition, inference costs can quickly go through the roof, accounting for 90% of lifecycle costs and forcing organizations to exceed their IT budgets.
In cases like these, initial costs are essentially meaningless. How a new tool or technology is used and the impact it has on the rest of the enterprise is the most important consideration.
Integration Can Make or Break an Investment
A frequently underestimated cost for new projects is integration. Especially in today’s environments, almost no technology operates in a vacuum. Hardware must work with existing infrastructure, and software must exchange information with other applications. Cloud services need to connect with on-premises systems, networks and security controls. And AI applications need access to the right data and operational workflows. Each connection introduces requirements that affect cost, performance and reliability.
In some cases, integration may require additional software, specialized engineering or infrastructure upgrades. In others, incompatible systems might require manual workarounds that persist long after deployment. Employees may end up moving information between applications or maintaining separate processes because the systems were never designed to work together. Those workarounds carry costs, consume staff time and introduce opportunities for error. It also makes any future changes more difficult to implement.
SD3IT, which counts integration among its strong points, can help organizations integrate new tech effectively and affordably, starting with guidance on the products and services that would best fit their needs. We continuously evaluate commercial technologies and bring together the right mix of products and capabilities to address customer challenges. Working with a broad ecosystem of technology partners, including industry leaders in enterprise IT, our role as a solution aggregator is to help government and commercial organizations identify, integrate and implement technology that supports their missions and delivers lasting value.
SD3IT has saved customers money by helping them understand what they need to achieve their mission, whether that involved avoiding a low-initial-cost trap or, in some cases, by showing them the advantages of buying a less expensive technology rather than a pricier option with bells and whistles they wouldn’t need. It can work both ways. The key is understanding the project.
Play the Long Game on Acquisitions
Getting long-term value from any investment rather than being lured into a cheaper option that proves ineffective or expensive to fix is an obvious goal. But a lack of familiarity with a technology or its impact on the enterprise can lead to unforeseen consequences. Preparation by an organization, including seeking good advice from experienced providers, can make all the difference. Hidden costs may be unknown at the early stages of a procurement, but that doesn’t mean they are unknowable.
A sound TCO assessment will look beyond acquisition and even integration, projecting the investment through its operational life. That can include accounting for recurring licenses and subscriptions, maintenance, technical support, energy consumption, staff training, security updates and eventual replacement.
Organizations should also evaluate how well vendors support their products, whether pricing could change as usage grows and whether the technology can accommodate future requirements without a major redesign. It’s also wise to avoid being locked into a proprietary platform. No forecast will capture every eventuality. But a reasonable lifecycle assessment makes assumptions visible and gives decision-makers a more realistic basis for comparing their options.
The lowest upfront price can be a useful starting point. It should never be the deciding factor.
About SD3IT
SD3IT (Solution Driven, Designed and Delivered Technology) helps government and commercial organizations modernize mission-critical IT through integrated infrastructure, cybersecurity, cloud and edge solutions. We work closely with leading technology partners to design, deploy and support secure, resilient environments that align with operational requirements, compliance mandates and long-term business objectives.