AI, Digital Twins Transform Enterprise Asset Management

Emerging technologies such as AI, machine learning, and digital twins are reshaping enterprise asset management (EAM), yet human expertise remains essential, according to Ultimo’s latest Maintenance Trend Report.

The report, based on a survey of more than 200 maintenance professionals worldwide, shows a notable rise in interest in next-generation technologies since Ultimo’s 2023 EAM Trend Report. Respondents highlighted contextual intelligence, up from 8% last year, as having the most positive impact on maintenance and business practices. Automation and robotics and machine learning followed, while interest in digital twins more than doubled to 40%.

Despite these technological gains, workforce challenges continue to dominate concerns. Sixty-three percent of respondents identified an aging workforce as the most critical trend affecting maintenance strategy, underscoring the need for knowledge transfer and workforce planning. Recruiting experienced staff was cited by half of the respondents as the main source of disruption over the past year.

“From global instability to changing regulations, socio-economic and political shifts are creating uncertainty across industries. In this environment, agility is critical,” says Berend Booms, Head, EAM Insights, Ultimo. 

Real-time insights derived from IoT data and predictive modeling, whose perceived impact has tripled since 2023, are unlocking EAM’s full potential. Yet nearly half of respondents cited a lack of internal expertise as a barrier to adopting these advanced tools.

Modern EAM systems now operate as engines of foresight rather than static log repositories. By leveraging AI and maintenance data, teams can shift from reactive problem-solving to proactive strategies, optimizing workflows, preventing downtime, and maximizing maintenance investments. Ultimo’s AI-powered EAM features are designed to deliver immediate operational gains without requiring in-house model training or heavy infrastructure.

The report emphasizes that technology alone is not sufficient. Success will depend on a combination of intelligent systems and skilled personnel.