Digital Twin Technology Gains Traction Among Finance Chiefs Despite Thin Evidence of ROI

The corporate world's latest buzzword—"digital twinning"—is making its way into 2026 budget conversations, though finance leaders may want to scrutinize the business case before committing capital.

Digital twins, virtual replicas of physical assets or processes that update in real-time, are "relatively new but are already showing positive results," according to a December analysis in Information Age. The problem? The article doesn't specify what those results are, who's achieving them, or how much they cost to implement.

This is the pattern finance executives have learned to recognize: a technology gets declared essential ("every business needs to start" using it, per the headline) before anyone's published audited financials proving the return. It's not that digital twins are snake oil—the concept is sound enough. You build a virtual model of your factory floor or supply chain, feed it real-time data, and theoretically you can test scenarios without expensive real-world experiments. Sounds great in the demo.

But here's what a CFO actually needs to know: What's the implementation cost? What's the payback period? Which use cases have documented ROI, and which are still in the "wouldn't it be cool if" phase?

The Information Age piece, authored by someone named Danielle Jaffit, doesn't answer these questions. It's a pattern that's become familiar in enterprise technology coverage—the breathless "you need this now" declaration that skips straight past the part where someone shows their work.

This matters because finance teams are already drowning in AI/ML project requests. Every department wants budget for something that promises to "transform" their function. Digital twins are entering an already-crowded field of technologies competing for the same capital allocation dollars.

The timing is particularly interesting. We're in February 2026, and the article published in December 2025—right when vendors are making their final push for current-year budget and early-year planning is underway. (Coincidence? Maybe. But finance leaders didn't get where they are by ignoring sales cycles.)

Here's the thing everyone's missing: digital twins aren't a single technology. They're a concept that can mean anything from "we have a 3D model of our warehouse in a database" to "we've built a real-time simulation of our entire manufacturing process with predictive analytics." The cost and complexity difference between those two scenarios is roughly the difference between buying a calculator and building a data center.

Smart finance leaders will ask the obvious questions: Which specific business process are we twinning? What decisions will this enable that we can't make today? What's the expected impact on working capital, throughput, or cost of goods sold? And—this is the important one—can we start with a pilot that costs five figures instead of seven?

The broader pattern here is worth noting. Every few years, a new technology gets positioned as table-stakes for competitiveness. Sometimes it's true (cloud computing, for instance, really did become essential). Sometimes it's not (remember when every company needed a blockchain strategy?).

Digital twins might end up in either category. The technology itself is legitimate—aerospace and automotive manufacturers have used versions of this for years. The question is whether the use cases have matured enough to justify the investment for companies outside those capital-intensive industries.

For now, finance leaders should probably file this under "interesting, worth monitoring, not yet proven at scale." If a vendor shows up claiming every business needs to start digital twinning immediately, the appropriate response is: "Show me the audited financials from three customers who've achieved documented ROI."

That's not skepticism. That's just finance.