By Enterprise Technology Insights
Published: October 2026
Main Facts
The modern industrial landscape is undergoing a silent revolution, anchored entirely by the explosive growth and reliance on 3D engineering data. Long gone are the days when computer-aided design (CAD) files and simulation models were siloed exclusively within the engineering department. Today, 3D engineering data serves as the foundational language of the entire enterprise, bridging the gap between initial conceptualization, manufacturing, aftermarket service, and cutting-edge digital twin or artificial intelligence (AI) initiatives.
Recent research conducted across 15 large-scale manufacturing organizations highlights a stark reality: the demand for applications that create, access, and share 3D engineering data is surging. Over two-thirds of surveyed enterprise leaders report that their internal need for 3D data accessibility is actively expanding, while the remaining third note that demand has stabilized at a historically high level. Crucially, not a single organization reported a decrease in demand.
To meet this relentless enterprise appetite, IT and engineering leaders face a classic strategic dilemma: Should they build customized internal applications from scratch, or should they purchase commercial off-the-shelf (COTS) solutions? However, fresh insights from the industry reveal that the debate is rarely a black-and-white, "all-or-nothing" proposition. Instead, modern manufacturers are adopting a nuanced, hybrid "build and buy" strategy, leaning heavily on commercial tools for standardized needs while strategically developing custom applications where unique operational advantages are required.
Chronology
The trajectory of how manufacturers source and deploy 3D engineering software has shifted dramatically over the past decade, influenced heavily by software availability, shifting enterprise requirements, and the recent democratization of development tools.
- The Early Era of Custom Development: Historically, many large manufacturing enterprises relied heavily on bespoke software. A decade ago, it was common for internal IT departments to custom-build up to 75% of their 3D data-sharing and viewing tools, tailoring them strictly to legacy workflows. Only 25% of applications were procured commercially.
- The Commercial Pivot: As the commercial software market matured, companies realized the high ongoing maintenance costs of proprietary code. The pendulum swung decisively toward commercial off-the-shelf (COTS) software. Across the recent 15-company study, the average ratio inverted dramatically, with organizations purchasing roughly 78% of their 3D solutions and building only 22% in-house.
- The Recent Hybrid Realignment: While COTS remains the dominant default preference—with 100% of surveyed companies preferring to buy when viable solutions exist—the pendulum has not settled permanently. Some forward-thinking enterprises report a counter-trend: as commercial software fails to meet highly specialized, modern operational demands, their internal custom development has ticked back up (in some cases climbing to 30% or 40%).
- The Dawn of the AI-Accelerated Future: Today, the integration of artificial intelligence and low-code/no-code capabilities (including AI-driven "vibe coding") is once again altering the calculus. Development barriers are lowering, prompting engineering and IT leaders to re-evaluate how they balance custom builds against commercial acquisitions in an era of rapid technological acceleration.
Supporting Data
The empirical data gathered from the cross-industry research underscores just how pervasive 3D engineering data has become, along with the specific economic and operational dynamics governing software acquisition strategies.
- 100% Preference for Commercial Procurement: When a viable commercial product exists that fits an organization’s workflow, every single enterprise surveyed prefers to buy rather than build.
- The 80/20 Rule of Software Sourcing: Across the 15 large manufacturing companies investigated, the average software procurement distribution sits at 78% bought and 22% built. The median metric mirrors this closely at 80%, indicating a tight industry clustering where the vast majority of firms maintain a roughly four-to-one ratio favoring commercial acquisition.
- Outliers in the Ecosystem: While most organizations hover around a 20% to 25% internal build rate, specific enterprise strategies vary wildly. A handful of firms push custom development up to 40% to protect proprietary workflows, whereas others view internal building as "very rare," keeping non-commercial software near the 10% threshold.
- Universal Growth Metrics:
- >66% of enterprise respondents report that their internal demand for 3D data sharing and cross-functional access is actively growing.
- 33% report that demand remains consistently high.
- 0% report any contraction in the need for 3D engineering applications.
Official Responses and Expert Insights
Industry leaders and enterprise engineering directors who participated in the research provided candid perspectives on how their sourcing strategies have evolved under pressure.
One manufacturing executive highlighted the dramatic shift from historical internal development toward commercial dominance:
"Originally I would say probably 75 percent was built and 25 percent bought, and now it’s opposite."
Conversely, another enterprise participant emphasized that commercial software cannot always keep pace with niche, rapidly evolving industrial requirements, driving a localized resurgence in custom programming:
"Commercial software does not meet our needs, and those needs have increased in the last three or four years. We were maybe 10% non-commercial software, and now we have around 30%. Whether that will continue to grow or stabilize or go down, I don’t know, but right now the trend is up."
Experts analyzing the data note that managing 3D data requires specialized competencies. Because engineering files—ranging from complex CAD geometries to intricate metadata and simulation parameters—are mathematically dense, organizations are repeatedly warned against "reinventing the wheel." Industry analysts suggest that whether a company builds or buys, success relies on avoiding foundational code-writing from scratch, advocating instead for pre-built software development kits (SDKs), APIs, and trusted third-party components.
Implications
The widespread democratization and increasing reliance on 3D engineering data carry profound strategic, financial, and technological implications for modern enterprises.
1. The Total Cost of Ownership (TCO) Beyond Initial Development
When deciding whether to build a custom application or purchase a commercial solution, companies frequently calculate initial speed and upfront capital expenditures. However, the research stresses that leadership teams must heavily weigh the long-term cost of scaling. Internal applications require continuous maintenance, security patching, and updates to keep pace with evolving CAD formats and operating systems. If an internally built tool breaks down, the enterprise absorbs the productivity loss.
2. Intellectual Property (IP) and Data Sensitivity
As 3D engineering data flows deeper into the extended supply chain, manufacturing partners, and third-party contractors, the risk of data leakage grows. Applications that ingest, render, or analyze sensitive CAD files must be tightly secured. Companies must carefully evaluate whether building a custom application offers superior data sovereignty or if enterprise-grade commercial tools provide more robust, audited security protocols.
3. The Disruptive Impact of Artificial Intelligence
Artificial intelligence is fundamentally reshaping software development. With the rise of AI-assisted coding tools, even developers with limited domain experience can rapidly scaffold applications designed to access and share data. This lower barrier to entry may make internal building more attractive and financially viable, potentially disrupting the current COTS-heavy equilibrium. However, while AI can assist in reading and routing data, generating accurate 3D geometry remains an intensely complex engineering challenge, meaning AI’s near-term impact will be felt more strongly in data access rather than data creation.
4. Moving Away from "Reinventing the Wheel"
A critical takeaway for IT and engineering executives is the danger of starting from scratch. Specialized components, proven APIs, and commercial building blocks exist to handle multiformat CAD and simulation data. Organizations that attempt to write native geometry-handling code from the ground up risk significant delays, budget overruns, and subpar data fidelity. The path forward requires identifying strategic technology partners who can supply robust APIs—allowing internal development teams to focus on unique business logic rather than foundational data translation.
Conclusion
The demand for 3D engineering data is not a temporary trend; it is the permanent operational backbone of modern manufacturing, digital twins, and AI-driven enterprises. By abandoning the false dichotomy of an "all-or-nothing" build-versus-buy mindset, forward-thinking organizations are embracing a flexible, hybrid approach. By choosing commercial solutions where standards apply, utilizing pre-built SDKs for custom applications, and remaining adaptable in the face of rapid AI acceleration, engineering leaders can successfully meet the ever-expanding demand for enterprise-wide 3D data.
