Decision-makers at the world’s most progressive industrial enterprises reveal a market at an inflection point – where competitive advantage belongs to organizations applying AI to the specific demands of their industry, and who are preparing to scale fast.
New data from IFS, the leading Industrial AI software provider, reveals Industrial AI is entering a decisive new phase – the organizations pulling ahead are those applying AI to the specific, complex demands of their sector, not deploying generic AI solutions across the enterprise.
A survey of global industrial enterprise leaders* finds AI priorities diverge sharply by sector:
- 48% of Energy & Utilities firms prioritize predictive maintenance as their priority AI use case
- 41% of Manufacturers identify supply chain optimization as their highest-value AI application
- 28% of Construction organizations focus on applying AI to financial planning and forecasting for complex build projects
- In Aerospace & Defense, supply chain and predictive maintenance together account for more than half of AI value expectations.
The findings show AI adoption is being driven by core industrial priorities the foundational areas for performance where improved efficiency, resilience, and data visibility can directly impact both cost and service levels.
60 percent of organizations across Manufacturing, Energy & Utilities, Transportation, Aerospace & Defense, Construction, and Telecommunications are already deploying industry-specific AI within operations.
Organizations are already seeing tangible benefits. Nearly six in ten respondents report AI is already saving their teams between one and seven hours per week, with 11 percent reporting over seven hours per week saved – a signal that returns are materializing well before full deployment.
Scaling AI becomes the next phase of competition
As organizations build on early deployments, attention is shifting from initial use cases to scaling industrial AI across the enterprise.
The path to scale has clear obstacles. Across all industries, data quality and accessibility top the list at 24 percent, followed by the need for clearly defined industry use cases (17 percent), with skills gaps, security concerns and systems integration each cited by 16 percent.
These factors are shaping the next phase of AI adoption, where success will depend on how effectively organizations embed AI into existing processes.
Confidence builds, but pace will define outcomes
The data indicates growing confidence – around half of respondents say they are confident in their ability to execute on AI fast enough to remain competitive. But that still leaves half who are not. The window for advantage is open, but it is closing.
Competitive advantage is increasingly tied to execution speed, with organizations that can scale AI effectively across their operations gaining a meaningful edge.
The findings reflect challenges common to industrial organizations worldwide, from data readiness to the need for use cases built around how specific sectors actually operate.
Industry is making steady progress in turning AI from concept into operational reality. What stands out is the shift towards applying AI in the systems that run the business, particularly across supply chain and asset performance. The next step is scaling that impact more consistently across operations.
That is where competitive advantage will be created. Organizations that move faster to connect the data, define the right use cases, and embed AI designed specifically for industry into everyday workflows will be best positioned to stay ahead.
Looking ahead
As industrial enterprises move into this next phase, the question is no longer whether to adopt AI, but how quickly value can be scaled across the organization.
SOURCE: Andre Robberts (2026 June 25) World’s leading industrialists speak: industry-specific applications will unlock the next wave of AI value. IFS Blog. https://blog.ifs.com/worlds-leading-industrialists-speak-industry-specific-applications-will-unlock-the-next-wave-of-ai-value
