The IFS Invisible Revolution Study 2025, which surveyed over 1,700 senior decisionmakers at industrial enterprises globally, found that while organisations are adopting AI at speed, they are not fully prepared for implementation at scale. This has created what IFS has dubbed the AI Execution Gap.

This gap is driven by companies moving faster into AI adoption than their staff are able to upskill. In the next 12 months, the number of companies still in early AI experimentation is predicted to collapse from 24 % to just 7 %, yet 52 % of senior leaders admit their management teams don’ t fully understand AI. Meanwhile, 99 % of global workforces will require major reskilling to harness the positive impacts of adoption on the industrial world.

“ AI is a core driver of business performance, it’ s time to plug the AI Execution Gap – bring people, process and product together to deliver tangible outcomes,” said Kriti Sharma, Chief Executive Officer, IFS Nexus Black.“ The pace of adoption is inspiring, but the next big unlock will come from scaling trust, strategy and talent. Industrial AI is a powerful force for good and we’ re in a moment of opportunity: those who move fast will lead the next decade of industry.”

Growing AI value, but readiness lags

The research reveals a striking contrast at the heart of the surge. While AI is already delivering impressive returns, most organisations remain unprepared to scale its impact. More than half of business leaders( 53 %) admit their organisation still lacks a clear AI strategy.

Yet opportunities are clear. 70 % of businesses report better-than-expected ROI from AI investments and on average 88 % say AI has already improved profitability – rising to 92 % in the US and 94 % in Germany.

Training and upskilling will be essential to ensure industrial companies remain competitive. Over half of leaders estimate that up to 60 % of their employees will need new skills, with a third suggesting it could be as high as 100 %.

Despite confidence in AI’ s potential to boost growth, trust remains a major hurdle. Only 29 % of global leaders are comfortable allowing AI to make strategic decisions autonomously, while 68 % insist a human must still confirm AI-generated outputs. Concerns about bias also persist – particularly in the US, where 63 % cite it as a top concern compared with 40 % in the Nordics. Encouragingly, 65 % of global leaders support the creation of an independent, international AI regulatory body to help close the trust gap.

Industrial AI reshapes business models

While much attention has been given to AI’ s role in white-collar productivity, it is industrial AI that is fundamentally reshaping industrial enterprises. It is being embedded deep within operations, automating maintenance, predicting disruptions, optimising supply chains and orchestrating intelligent decision-making across field service, asset management and manufacturing.

More than half of global organisations( 54 %) are using automation AI, while 45 % are deploying predictive AI. Already, 35 % are experimenting with agentic AI, capable of autonomously executing decisions across workflows.

Traditional business models are also evolving. Seventy-seven percent of global leaders say AI is accelerating servitisation – the shift from product sales to outcomebased services, where businesses deliver uptime, performance and continuous value instead of only physical goods.

Sharma continued:“ This is a bold new era where AI is redefining how industries create and deliver value. Industrial AI is moving into real-time, decision-grade intelligence embedded across the

enterprise. It’ s already securely automating the complex, predicting the unexpected and powering new service-led business models. This is about shifting from tasks to transformation and the organisations who embrace that shift will lead the next industrial chapter.” x www. intelligentcxo. com

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