Industrial AI adoption is accelerating, says IFS, but enterprises face a critical execution gap: lacking skills, strategy, and trust, even as AI embeds deeply into operations, driving efficiency and profitability.
In sum – what to know:
Execution gap – enterprises are adopting AI faster than they can upskill staff
Trust issues – just 29% trust AI with key decisions, despite use in core operations.
Profit gains – 88% already see profitability gains, but over half lack a clear AI strategy.
AI is being adopted by industrial enterprises at rapid pace, behind-the-scenes and under-the-hood, which is driving an “invisible revolution”, declares a new study by Sweden-based industrial software outfit IFS. At the same time, their jacked-up Industry 4.0 ambitions, reflected in their accelerating AI adoption, are outrunning their means. “Organizations are adopting AI [but] they are not fully prepared for its implementation,” says IFS.
The firm perceives an AI “execution gap” between what enterprises are buying and what they are using. Many don’t have the right staff or skills, and many don’t have the right strategy (or even just a strategy). As industry surveys go (and there are plenty), this feels like a stark one. “As with all revolutions, significant challenges are emerging,” writes IFS. Maybe the starkest finding: that, despite piling in on AI, just 29 percent trust AI to make “strategic decisions”.
In other words: the Industry 4.0 market doesn’t really think AI should be anywhere near critical operations, and yet enterprises are putting industrial AI solutions to work as “embedded, operational AI across core business processes”. The findings of the survey, which polled 1,700 “senior decision makers” at industrial enterprises globally in May, reveal a “rapid but under-recognized shift” away from “consumer productivity AI experimentation”, says IFS.
The sense, then, is that AI is no longer just a knock-about everyday work tool for white-collar workers, but a critical one for blue-collar staff in charge of industrial machines and production lines in the world’s economic engine rooms. “While AI has captured attention for revolutionizing productivity and creative tasks for predominantly white-collar workers, it’s industrial AI that is fundamentally reshaping the way industrial enterprises run,” says IFS.
“It is being embedded deep within core operations, automating maintenance, predicting disruptions, optimizing supply chains, and orchestrating intelligent decision-making across field service, asset management, and manufacturing. This isn’t a future ambition, it’s already happening.” Its poll says 77 percent of industrial firms are using AI to move from selling just physical goods to also sell business services (“outcome-based services”).
This is a part of the broader “servitization” trend, it writes. Fifty-four percent are using AI for automation, and 45 percent are using it for some kind of predictive maintenance or operations. Most remarkably, perhaps, 35 percent are already experimenting with agentic AI to execute decisions autonomously across workflows. Most are also seeing good returns: 88 percent “already” report profitability gains, rising to 92 percent in the US and 94 percent in Germany.
Seventy percent claim “better-than-expected” returns from their AI investments. But there is a degree of blind faith about it; more than half (53 percent) still lack a clear AI strategy, and, as above, only 29 percent trust AI to make decisions. More seriously, IFS says most organizations are “unprepared to scale its impact”. They just don’t have the staff, it seems. The job over the next 12 months, if any proper competitive advantage is to be achieved, is to train.
And then train some more. “Companies [are] moving faster than their staff are able to upskill. In the next 12 months, the number of companies still in early AI experimentation will collapse from 24 percent to just seven percent moving up in the maturity curve.” Which is an awkwardly-worded sentence – which presumably means the AI conversion rate, from experimentation to production, is set to slip by about two thirds in the near-term. Whatever, it looks bad.
IFS writes: “Fifty-two percent of senior leaders say their management teams don’t fully understand AI, and 99 percent of global workforces will require major reskilling to harness the positive impacts of AI adoption on the industrial world”. It also says: “The study found that over half of the business leaders interviewed estimated that up to 60 percent of their employees will need new skills, with a third saying it could be as high as 100 percent.”
Kriti Sharma, chief executive at IFS Nexus Black, said: “The pace of adoption is inspiring, but the next big unlock will come from scaling trust, strategy, and talent… 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.”
He added: “This is a bold new era… Organizations who embrace that shift will lead the next industrial chapter… Those who move fast will lead the next decade of industry. We’re experiencing one of the most profound and underestimated shifts in global business. Industrial AI is here and already reshaping how entire industries run, compete, and grow. The time is now.”
As a footnote, and an addendum to the trust statistic, the study says 68 percent of industrial enterprises want a human must to confirm or approve AI outputs. Concerns about bias persist – particularly in the US, where 63 percent of respondents cite it as a top concern (compared to just 40 percent in the Nordics, it turns out). Notably, 65 percent of global leaders support the creation of an independent, international AI regulatory body to help close the trust gap.
The report is available here.
