AI in Manufacturing The Hype is Over—but Scaling Remains a Challenge

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The experimental phase is over: 60 percent of manufacturing companies are already using artificial intelligence extensively in their day-to-day operations. However, a new study by the software provider Revalize warns that there are major shortcomings when it comes to scalability and measurability. 

Manufacturing companies around the world are rapidly scaling up AI pilot projects for widespread use. But the enthusiasm masks a structural problem: The fundamental prerequisites in the areas of data, skilled personnel, and process integration are not keeping pace with this rapid expansion. This is the conclusion of the latest report “Good Will Isn’t Enough to Scale AI” by Revalize, a provider of PLM, CAD, and CPQ software solutions.For the study, 500 executives from selected manufacturing sectors in the DACH region, the U.S., and the United Kingdom were surveyed. The key finding: Executive-level ambitions are increasingly out of step with operational reality.

An Overview of the Study's Key Findings

1. From Hype to Everyday Use
   The AI boom, in the sense of mere hype, is over—the AI era has begun. In the first quarter of 2026, only 36% of the manufacturing companies surveyed had achieved broad or advanced AI adoption. Just six months later, that figure shot up to 60%. AI is now integrated into numerous business processes. Only 8% of companies are still in the purely exploratory phase.
2. Flying Blind When It Comes to Measuring Success (ROI)
   While the impact of AI is widely assumed, it is rarely quantified. 72% of companies report that they can attribute positive business results to AI. But the data foundation is shaky: 50% of manufacturers worldwide track AI results only informally or inconsistently. Only 49% rigorously and data-drivenly measure the return on investment (ROI) of their AI initiatives. This results in a dangerous gap between perceived and proven success.
3. The Gap Between the Executive Suite and the Shop Floor
   Top management’s AI strategy is outpacing reality. C-level executives report “advanced AI implementation” more than twice as often as senior managers from operations. This suggests that strategic expectations are growing faster than teams can realistically integrate them into their daily work and operate them sustainably.
4. AI as a Buffer Against Geopolitical Risks
   Economic conditions remain a driver for AI: While declining customs and compliance costs point to a slight easing of geopolitical tensions, Nevertheless, 44% of global manufacturing companies continue to explicitly accelerate AI adoption in order to specifically offset margin pressure caused by tariffs and costs.

“The adoption of AI in the manufacturing sector is nearly universal. Now, companies need measurable goals to demonstrate that their investments are delivering results,” explains Mike Sabin, CEO of Revalize. “Too many executives are attributing success excessively to AI without data to back it up. This gap between perception and operational reality won’t close on its own. Without robust processes and alignment from the C-suite all the way down to the shop floor, manufacturing companies cannot successfully scale AI.”
In the long term, the study’s authors conclude, only those companies that invest disciplinedly and tie the benefits of their AI solutions to hard, real-world challenges will reap the rewards.

In the long run, only those companies that invest strategically and link the benefits of their AI solutions to concrete, real-world challenges will benefit.

Methodology

On behalf of Revalize, a total of 500 decision-makers for PLM, CPQ, and engineering software in manufacturing companies (with 100 or more employees) were surveyed from July 7 to 17, 2026. The sample included 225 respondents in the DACH region (Germany, Austria, Switzerland), 50 in the United Kingdom, and 225 in the United States. The participants were recruited by the market research panel OpinionRoute.

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