EY’s 2025 study points to a gap between enterprise investment in emerging technologies and the ability to put them into active use. The findings cover multiple industries—not manufacturing alone—and suggest that scaling and integration, alongside security, data governance, skills and supplier coordination, remain reported challenges.
What EY’s study measured—and what it did not
EY’s Reimagining Industry Futures Study 2025 was based on an online survey of 1,635 enterprise respondents fielded in November 2024. Respondents had to describe themselves as at least moderately knowledgeable about their organization’s emerging-technology initiatives. The survey covered multiple industries and geographies, including sustainability, enterprise spending and adoption, AI and 5G-IoT use cases, supplier capabilities and supplier ecosystems. Manufacturing accounted for 12% of respondents.
That makes the findings a cross-industry snapshot with industrial representation, not a census or audit of industrial companies worldwide. They reflect respondents’ reports at the time of the survey and cannot establish why a particular company’s project stalled or prove that any one obstacle caused slow deployment. The detailed figures below were reported by Computer Weekly from EY’s study; they are survey responses, not independently audited deployment data. Computer Weekly’s February 18, 2025 coverage and EY’s official study page provide the source context.
Investment figures exceed active deployment figures
EY’s survey, as reported by Computer Weekly, shows why investment should not be read as proof that a technology is in routine production use. The figures describe different adoption stages: whether respondents reported investing in a technology, and whether they reported active deployments.
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| Technology | Reported investment | Reported active deployment |
|---|---|---|
| Generative AI | 47% in EY’s November 2024 survey, versus 43% in the prior survey year | 1% in EY’s November 2024 survey |
| Internet of Things (IoT) | 43% in EY’s November 2024 survey | 16% in EY’s November 2024 survey, compared with 19% in the 2024 survey |
| 5G | 33% in EY’s November 2024 survey | Not stated in the cited Computer Weekly coverage |
| Edge computing | Not stated in the cited Computer Weekly coverage | 22% in EY’s November 2024 survey, flat year-on-year |
Investment can include spending or intent to invest; an active deployment is a later stage. Neither figure alone says whether a technology is used broadly across operations, integrated with other systems, or delivering a particular business outcome. The especially large gap between reported GenAI investment and active deployment is consistent with interest outpacing implementation, but the survey does not establish the status of individual projects.
Why moving from trial to production is difficult
Scaling and integration
EY’s coverage describes difficulty scaling use cases and integrating new systems into existing environments. A successful trial may work in a limited setting without being ready for production across sites, teams or workflows. Connecting new tools to established systems can also demand coordination beyond the technology team.
Security and data governance for GenAI
Among respondents discussing GenAI impediments, 50% cited cybersecurity and data protection as a leading concern, while 46% cited improving data governance. These reported concerns point to questions companies need to resolve before broader use—such as how data is protected and governed—but do not prove that security or governance was the cause of any particular deployment delay.
Skills and organizational change
Adoption also depends on employees being able to use new systems and on teams across business functions working together. EY’s discussion emphasizes upskilling and collaboration, as well as leadership involvement. A technical pilot can therefore remain isolated if the organization has not made the operational changes needed to use it at scale.
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Emerging technology projects may involve multiple vendors and partners. In EY’s survey, as reported by Computer Weekly, 73% said they needed a better understanding of the changing supplier landscape, and 56% reported limited awareness of their technology suppliers’ partners. Those responses suggest that navigating the ecosystem is itself a challenge for some enterprises.
Why combining technologies matters
Companies may miss value when technologies remain isolated experiments rather than working together in operations. Rob Atkinson, EY area managing partner for UK and Ireland TMT, told Computer Weekly: “As well as posing a challenge to unlocking long-term value, a failure to progress beyond the trial phase means businesses risk missing out on the combined impact of different technologies deployed together, an area where four in five (79%) organisations are looking to achieve more.” The 79% figure is attributed to the article’s account of the study, not to a manufacturing-only result.
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For example, IoT data, connectivity and analytics may need to fit into existing workflows and systems before they can support an operational use case. The study’s findings do not prescribe specific equipment or establish that a particular combination will succeed; they underline the distinction between testing a component and embedding connected technologies in business processes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the findings mean for industrial companies
The survey does not diagnose any one firm, but its reported barriers suggest practical questions for organizations trying to move beyond pilots:
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- Define the deployment stage. Separate budget or investment plans from pilots, active deployments and scaled operational use.
- Plan integration early. Identify how a new system will connect to existing infrastructure and workflows, and which teams own those connections.
- Set governance and security requirements. For GenAI, clarify data protection and governance expectations before expanding use.
- Prepare people and processes. Include employee training, cross-functional collaboration and leadership in rollout planning.
- Map the supplier ecosystem. Know which vendors and partners contribute capabilities, and how responsibilities fit together.
- Evaluate combined use cases. Consider whether technologies need to work together to deliver the intended operational value, rather than treating each pilot as an isolated endpoint.
An industrial IoT gateway is one possible connectivity component in an IoT or edge architecture, but EY’s study neither evaluates gateways nor recommends particular hardware. The survey is evidence about reported enterprise adoption and challenges, not equipment-buying guidance.
How to read the headline carefully
“Stunted” describes the reported difficulty of progressing emerging technologies into deployment; it should not be read as a measured verdict on every industrial firm. The study’s respondents came from varied sectors and geographies, only 12% were in manufacturing, and fieldwork took place in November 2024. Its results are useful for understanding the reported gap between investment and deployment at that point in time, not as a measure of adoption in 2026 or a forecast of what every company will do.
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