Most organizations can tell you how much they spend on IT projects—but few can tell you how much it truly costs to run them afterward.
Add in pressure to keep the IT budget flat, and it’s a recipe for stalled innovation. Budgets get tighter. Funding for new projects becomes scarce, leading to missed opportunities to invest in projects that drive new revenue.
Build to Run (or B2R) is an often overlooked cost driver that sits at the center of this problem, and provides a powerful way to quantify and communicate the full impact of IT investments.
The problem is that few companies track Build to Run effectively, setting themselves on a trajectory that can take years to reverse.
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What Is Build to Run?
Build to Run is a metric based on a simple concept: whenever you build something in IT, you also commit to the cost of running it, which is often more than anyone accounts for. While similar to Gartner’s Run-Grow-Transform framework for assessing IT spend, Run to Build sharpens the focus, grouping grow and transform into a single bucket (build).
The key takeaway: Every build project has a run tail, and it’s not static.
Let’s say, for instance, your company has $100M to spend on IT projects this year. Even light enhancements could add a 6% increase in annual run costs. With larger projects, that number can spike to 20% or more.
How Untracked Run Costs Squeeze IT Budgets
Going a step further in the example above, let’s imagine year one projects add $10M in run costs. In year two, your budget for new work decreases to $90M. By year three, it’s lower still, particularly if your IT budget must remain flat.
What’s more, run costs go up every year. Contractor rates rise, as do labor costs overall. Applications age and require increased maintenance to manage tech debt, while inflation also adds to rising costs.
As costs climb silently in the background, your innovation portfolio keeps shrinking, until you’re unable to fund anything new. Once Build to Run consumes your budget, turning the ship around can take years—all while your competitors take advantage of innovation opportunities your company can’t afford.
So what are some warning signs you might be headed towards a Build to Run cliff?
- You’re not tracking run costs, or not tracking them effectively
- Your IT budget must remain flat
- Your new project pipeline is shrinking
Why AI Investments Make Build to Run Critical in 2025
AI has become one of the most aggressively funded areas in enterprise IT. Worldwide generative AI (GenAI) spend alone is expected to total $644 billion in 2025, an increase of 76.4% from 2024, according to a forecast by Gartner, Inc. Deloitte predicts that in 2025, 25% of companies that use gen AI will launch agentic AI pilots or proofs of concept, growing to 50% in 2027. In 2025 alone, organizations are accelerating deployment of AI initiatives across use cases like customer support, financial analysis, IT operations, and software development.
But here’s the problem: while AI promises massive value, most of that value is assumed up front—and few organizations truly model the ongoing cost of running AI systems.
Running AI isn’t cheap. Model retraining, fine-tuning, prompt engineering, licensing fees, cloud compute for inferencing, and additional governance requirements all add to ongoing cost. Worse, these costs often fall squarely on IT, while operational savings appear in other departments’ budgets. Without a Build to Run approach, organizations risk deploying AI initiatives that look like a win on paper, but silently cannibalize future IT budgets—and ultimately deliver negative ROI at scale.
Core Elements of Managing Build to Run
The only way to keep your innovation budget from being squeezed is to build run costs into the conversation during the scoping phase, before you make a decision. The biggest barrier for most organizations: they can’t effectively measure Build to Run, and you can’t manage what you can’t measure.
To get it right, companies must be able to:
- Communicate back to the business where run costs will sit throughout the organization, including applications and services that new projects will impact
- Accurately identify one-time vs. recurring costs associated with proposed projects
- Forecast run costs across multiple years, not just the current fiscal cycle, to understand how projects will affect your cost footprint down the line
- Translate project impact into unit costs such as cost per claim, per transaction, per resolved support ticket with and without AI etc. to communicate the project’s overall impact on the business
For example, if an insurance company builds a new system comprised of AI agents to process customer claims that increases IT costs by $3 per claim but reduces processing time and labor costs by $5, the net benefit is $2 per claim. At scale, that’s hundreds of millions in savings —but only if run costs are visible and managed.
But the opposite can also be true. If the AI project increases your cost per claim by $1 but delivers no measurable improvement in throughput or quality, is it still worth it? That’s a conversation you want to have before the build begins.
Achieving Build to Run Clarity Across the Enterprise
Communicating this level of insight at the speed of business isn’t possible if you’re trying to track run costs using spreadsheets, corporate planning tools or legacy ITFM software. These tools simply weren’t built to contend with the complexity or nuance of modern IT spend and how it translates into business outcomes.
Instead, it requires an ITFM solution like Nicus that:
- Integrates operational data with finance-approved general ledger data (not black-box aggregate data) for more granular visibility and control
- Uses a decision-driven cost model aligned to how you deliver technology to your organization and allows you to more accurately model future run costs
- Provides rapid 24/7 forecasting and scenario modeling, rather than taking hours or days to update
- Includes support for governance views such as Build to Run, and Run/Grow/Transform
There’s an unspoken challenge that IT lives with all the time. The business sees automation savings reflected in its own cost centers, while IT absorbs the costs required to maintain the new solution.
The result is that business leaders reap the benefits of cost optimization, while IT is stuck defending rising run costs. Build to Run helps surface these tradeoffs early across the organization, arming leaders up front with the cost impacts so they can actively manage them before innovation funds dry up.
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