How manufacturers are using AI to improve facility performance

Recent survey data shows that manufacturing facilities teams are under pressure to manage equipment uptime, energy costs and more streamlined workflows. In a sector where equipment health directly influences an organization’s bottom line, these teams are turning to new technologies to mitigate risks and control costs.

The 2026 AI & Digitalization in Manufacturing Facilities Management Report surveyed business leaders and facility managers in the manufacturing sector about their current and planned investments in building technology, as well as the barriers to adoption. The results show that manufacturers have embraced workplace management and smart building technologies to address these challenges, with early investments focusing on workplace analytics, energy management, and space management and planning.

Explore some of the key findings from the report.

1: Maintenance strategies are shifting from reactive to proactive

Equipment reliability and uptime are critical in manufacturing environments, where unexpected failures can disrupt production, reduce productivity, and increase costs and liability. Our survey found that manufacturers are increasingly turning to AI to get ahead of equipment problems before they occur. Among those using AI to improve facility performance, 53% of manufacturing leaders and 44% of facility managers use it to enable predictive maintenance.

Nonetheless, survey responses suggest that manufacturing organizations are looking for even greater operational visibility and support in shifting from reactive to proactive maintenance approaches.

• Equipment health is the number one area where manufacturing FMs would like to have more data and insights
• 58% of manufacturing sector leaders and 55% of FMs who are planning AI deployments to improve facility performance are implementing AI-driven predictive maintenance tools – the top planned use case for both groups

Predictive maintenance is emerging as one of the clearest examples of how manufacturers are moving beyond foundational digital capabilities and using AI to anticipate operational issues before they affect productivity.

2: Energy optimization is a growing priority amid rising costs

Manufacturing facilities are among the most energy-intensive buildings, making energy management both an operational and financial priority.

• 83% of manufacturing FMs using workplace management or smart building technology say they use it to track, optimize and control energy use.
• Optimizing energy performance is currently the top use case for AI among manufacturing FM respondents.

Despite high levels of technology adoption, rising costs and limited budgets continue to make energy performance optimization a top investment priority. In fact, 71% of manufacturing FMs who plan to roll out an AI solution in the next year are implementing tools to optimize energy performance.

3: Automation is expanding across manufacturing operations

Manufacturing facilities rely on complex processes and highly coordinated operations, making efficiency and consistency essential to performance. AI-powered automation allows teams to reduce manual work and respond faster to operational demands.

• 54% of manufacturing leaders using AI to improve facilities performance say they use it to enable workflow automation – the top current use case
• Half of manufacturing FMs that are using AI use it to automate workflows
• Nearly a third (31%) of manufacturing sector FMs cite “enhanced building automation” as the capability that would have the greatest impact on facility resilience and efficiency
• Manufacturing leaders see workflow automation as the area where AI has the greatest long-term potential to improve workplace performance

As manufacturers expand their use of AI, automation appears to be evolving from a productivity tool into a broader operational capability that supports more consistent and efficient facilities management.

What these findings mean for manufacturing facilities management

These findings reveal a manufacturing sector that has built a strong digital foundation and is now accelerating its use of AI to move from monitoring and analysis toward proactive, automated operations. Predictive maintenance, energy optimization and automation stand out as the clearest priorities for manufacturers who are looking to strengthen uptime, control costs and improve resilience.

FAQs

How are manufacturers using AI to improve facility performance?

Manufacturers are applying AI across a range of facilities management functions including predictive maintenance, energy optimization, workflow automation and operational analytics. These technologies help facility teams identify issues earlier, streamline routine processes and make more informed operational decisions.

Why is predictive maintenance important in manufacturing facilities?

Manufacturing operations depend on reliable equipment and minimal downtime. Predictive maintenance uses AI and data from connected buildings to identify potential equipment issues before failures occur. This helps organizations reduce unplanned outages, improve asset performance and optimize maintenance resources.

Why is energy optimization a priority for manufacturing organizations?

Manufacturing facilities are among the most energy-intensive buildings. AI-powered energy management helps organizations to identify inefficiencies, reduce energy consumption, lower operating costs and support sustainability goals, while maintaining production performance.

What does the future of AI in manufacturing facilities management look like?

Survey responses suggest manufacturers are moving beyond foundational digital technologies and investing in AI-powered capabilities that enable more proactive, automated operations. Future priorities include predictive maintenance, energy optimization, workflow automation and greater operational visibility across facilities.