GÖPPINGEN, Germany — November 4, 2026 — Most manufacturing IT decision-makers (68%) already use proactive or partially autonomous approaches to resolving technology issues. Yet they are twice as likely as technology-sector peers to cite uncertainty about AI’s value as a barrier to adoption, according to research from TeamViewer, a leading provider of digital workplace solutions.

43% say their organization already resolves issues proactively, while another 25% report partially autonomous handling, in which AI predicts and prevents issues with some human oversight. Both figures exceed those for the technology sector—35% for proactive handling and 21% for partially autonomous handling—as well as the cross-industry figures of 41% and 17%, respectively.

That proactive stance also shows up in how respondents want IT to work. Among respondents in manufacturing, 28% would prefer IT to use AI to detect issues early and keep them informed, compared with 25% across industries. Just 19% in manufacturing would rather report issues themselves and wait for a fix, well below the 25% average.

Even so, uncertainty about AI’s value or business impact remains a barrier to adoption for 32% of manufacturing IT decision-makers, compared with 16% in technology and 21% across all industries. Together with security, privacy, and risk concerns (47%) and a lack of skills or training (34%), it is one of manufacturing’s three most-cited barriers.

“When people talk about AI in manufacturing, they often imagine fully autonomous environments. In reality, many manufacturers run on systems built over decades that they can’t simply replace, so the biggest advances come from thousands of smaller decisions: identifying issues earlier and removing everyday friction. Because that work happens quietly in the background, its impact is easy to overlook. The organizations creating the most value are often those solving these small problems at scale and consistently demonstrating the results in specific use cases,” said Mei Dent, Chief Product and Technology Officer at TeamViewer.

Personal productivity gains provide another part of the picture: 44% of respondents in manufacturing say AI already makes them more productive, compared with 39% across industries. Manufacturing respondents who verify AI outputs spend an average of 1.6 hours a week doing so, compared with 1.9 hours across industries and 2.7 hours in technology. Looking ahead, 35% of manufacturing respondents expect to delegate more tasks to AI by 2030 and focus on higher-value work, compared with 28% across industries. Taken together with lingering doubts about business impact, these findings suggest the value may be real but harder to measure at the organization level.

Day-to-day prompting is typical: respondents in manufacturing prompt AI an average of 3.08 times a day, against 3.28 across industries and 4.72 in technology. What stands out is how they want AI to act. Only 23% say a human should be involved before any action is taken, compared with 31% across industries, while 46% in manufacturing want a human involved when security, data, or business operations could be affected, compared with 40% across industries.

Across the research, comfort with AI is consistently higher for visible, assistive tasks like monitoring systems, flagging issues, and transcribing than for AI making decisions on its own or handling sensitive data unsupervised. That gap is widest among onsite and hybrid employees, who are less comfortable with autonomous AI than remote employees.

About the report

The study was conducted by Sapio Research on behalf of TeamViewer in April and May 2026, among 4,200 respondents across 9 markets: the U.S., the U.K., Australia, France, Germany, Italy, Japan, Singapore, and Brazil. The full report is available here: https://www.teamviewer.com/en/resources/reports/autonomous-digital-workplace/