MaintainX aims to find out. As part of its State of Industrial Maintenance report, the maintenance and asset management platform recently surveyed 1,320 professionals across the U.S. and Canada with the goal of understanding the obstacles they face in 2025 and beyond.

Cofounder Nick Haase, who recently discussed SOP generation on The Food Engineering Podcast, notes organizations want to move to a predictive maintenance approach, but that’s often easier said than done.

“They’re struggling to break free from firefighting,” Haase writes. “Preventive maintenance is a goal for most teams — 71% say it’s their primary strategy — but reality often falls short. Less than 35% actually spend most of their time on planned tasks. This isn’t laziness or lack of ambition. It’s because their best intentions keep colliding with challenges like aging equipment and talent shortages.”

Specifically, 13% of survey respondents note they spend 60% or more of their time conducting planned maintenance activities. Just over a fifth (22%) say they spend 41-60% of their time on planned maintenance, while 26% spend 21-40% of their time on scheduled maintenance. The majority of surveyed professionals — 32% — say they spend less than 21% of their time on planned maintenance.

Unplanned downtime is a major concern, but MaintainX has good news to report there: 74% of surveyed respondents reported stabilization or a decrease in unplanned downtime over the last year.

However, 31% of survey respondents note their downtime costs had increased, while 49% say their downtime costs remained the same. Just one in five survey respondents say their downtime costs decreased despite experiencing a drop in unplanned downtime. MaintainX points to three main drivers for increasing downtime costs: machine wear and tear, rising costs of parts and shipping, and labor costs.

What can organizations do to make the most of their maintenance time and decrease downtime costs? MaintainX recommends embracing artificial intelligence (AI). For example, AI can help with work order management and scheduling, maintenance cost tracking and optimization, and predicting equipment failures before they happen.

Organizations are already exploring the use of AI in their operations — 14% of survey respondents report evaluating AI options, 7% plan to implement it within the next 12 months and 12% are in pilot program testing. Meanwhile, some manufacturers have more experience with AI, as 15% use AI in specific areas, while 17% use it across multiple maintenance processes.

Those who utilize AI are experiencing benefits. Nearly 40% cite knowledge capture and sharing as the top advantage, but they also point to reduced unexpected equipment failures, improved maintenance scheduling, more efficient work order completion, improved safety compliance and making data-driven decisions as other benefits.

Certainly there are barriers to implementing AI — budget constraints, lack of technical expertise and cybersecurity concerns — but as organizations seek to optimize their maintenance operations, AI appears to be a critical option to consider.