Meet the 50 Facilities Leaders to Watch in 2025
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For multi-site operators, inefficient work orders and incomplete data create costly downtime and repeated vendor visits in retail, hospitality, and food service.
New conversational and embedded AI tools solve this by automatically translating vague requests from plain language into complete, actionable work orders.
Now, with FexaAI Work Order Agent, facilities teams can move from reactive firefighting to proactive maintenance, strategic planning, and other high-value work.
Brands like Bath & Body Works are already seeing tangible benefits, including faster fixes, fewer callbacks, more accurate data, and smoother operations overall.
From rigid, on-premise systems to flexible, cloud-based platforms, facilities management technology has evolved significantly in just a few years. Until recently, AI relied on dashboards and predictive models full of messy, incomplete data. Perhaps unsurprisingly, these tools often failed. Now, with generative AI, facilities management is turning a new page in playbooks and history books alike.
For leaders, the moment presents a unique opportunity to blend automation with intelligence and domain expertise. Because it reduces reactive firefighting, AI can free managers to implement more proactive maintenance strategies moving forward. But the journey to get here won't be easy for most.
More than anything, progress in this era depends on the basics: consistent intake, current asset records, and clear handoffs across partners. But in multi-site operations, details tend to get lost in translation. Here, restoring service faster means turning vague requests into structured, actionable work orders. To do so successfully, each step between request, schedule, and closeout must be reliable first.
Downtime usually tops the list of stressors for facilities management leaders. Every hour a freezer, POS system, or HVAC unit is offline, financial and customer risks multiply. In 2025, the average cost of downtime in the retail industry is $1.1 million per hour. Here, even saving one hour per incident across hundreds or thousands of sites can yield measurable results.
Taking it personally: Today, the impact of proactive maintenance strategies stretches far beyond the facilities manager. For example, in healthcare, some experts say maintaining ventilation, power, and cleanliness is part of the healing process itself. Clayton Smith, Senior Vice President of Facilities Management at Children's Health, a pediatric hospital in Texas, witnesses this phenomenon firsthand every day. "Somebody's child is plugged into the building, and that building is keeping them alive. Every day, my team does their job like it's a survey because they know it's impacting somebody's kid."
Vendor rework is next on the list of facilities frustrations. Often attributed to poor performance, it usually originates with incomplete or inaccurate work orders. A vague request like “The AC is broken” triggers labor-intensive follow-up, repeated vendor visits, and extended downtime. AI can solve this by embedding intelligence in work order creation, prompting for details like noise, temperature, or error codes, appending critical location, asset history, and warranty data, and delivering vendor-ready orders.
This is the core function of the FexaAI Work Order Agent, which is designed to be the sidekick that stretched-thin facilities teams need. By allowing any store employee to submit issues in plain English, the system automatically prompts for missing details, applies location-specific context, and routes each ticket to the right vendor the first time. This eliminates the manual, error-prone processes of legacy CMMS platforms and ensures every work order is clean from the start.
Culture meets AI: For Nicholas Woollen, Marriott International’s Vice President of Engineering & Facilities Operations – US & Canada, pairing the speed of AI with a culture of confidence is paramount for maintaining high standards across multi-site operations. "We have a platform that tracks all the work across our managed portfolio: who does it, when, and how long it takes. But technology is only half the story. We promote a culture of confidence by making it clear that accuracy matters more than appearances. That means reporting honestly, even if a task wasn't completed. Otherwise, you end up with 'pencil whipping,' or falsified documents. Our standard is simple: do the right thing, every time."
Unsurprisingly, managing hundreds or thousands of sites can be complex. Here, leaders face unstructured, inconsistent data that makes it nearly impossible to answer basic questions, like "Which assets fail most often? Which vendors deliver the best? And where should capital be allocated?" By translating plain text into structured, standardized data, confirming the completeness of each record, and enforcing consistency across locations, AI provides a single source of truth.
Tech team: A solid data foundation is what lets leaders like Matthew Rodriguez, Corporate Facilities Supervisor for KFC US in Texas, have their boots on the ground in several locations at once. "I have to have major balance and trust in my team, but I can coach from wherever I want. I hop on Teams if need be. If a specialist needs help, they can call me on FaceTime. We dive in together at that same point. That's how I can be in three positions at once."
Other facilities leaders already see tangible outcomes, too, like cleaner data, faster fixes, and more time for high-value initiatives. With intelligent, embedded AI now part of daily operations, multi-site operators can manage smarter at scale. By eliminating forms and manual entry, it can help teams focus on operational impact instead of administrative busywork.
Unlike bolt-on dashboards or experimental pilots, FexaAI is integrated into the core workflow engine. Purpose-built for operators in retail, grocery, and restaurant industries, it delivers ROI at scale without requiring additional tools or training. By turning plain language into structured data, it builds the reliable foundation needed for smarter management.
AI in the works: Brian Diehl, Project Manager for Bath & Body Works, also feels the impact of a more proactive approach to work orders in his daily operations. “The built-in intelligence reduces the back-and-forth of triaging tickets. It’s an ideal solution for cutting downtime, reducing rework, and helping both our field and corporate teams focus on higher-value work.”
So far in the evolution of facilities technology, one pattern is clear: fix data intake to unlock operational and strategic gains. While valuable today, this capability will likely be a baseline expectation soon. What comes next is a closed-loop workflow where intake stays conversational, triage is standardized, and dispatch is guided by real-time context.
Near term, AI validates and completes work orders, reads error codes from photos and device logs, checks warranties and SLAs, and routes to the best vendor based on skills, coverage, and availability. It stages parts and suggests low-impact windows, shortening the repair cycle. Meanwhile, each ticket improves the next by updating templates and playbooks.
Looking ahead, connected assets publish health data continuously. Systems forecast failure windows and open service requests before downtime, while an up-to-date virtual model of each critical asset, called a "digital twin," tests fixes and schedules the least disruptive plan. On-site technicians use AR instructions for rare or complex tasks, contracts shift toward uptime outcomes, and compliance evidence is recorded as work happens.
Throughout it all, the work for leaders remains concrete: at intake, make every work order structured, consistent, and complete. Now, with new tools embedding AI directly into daily workflows, this future is already taking shape. Teams can submit work orders in plain language, automatically populate missing details, add location-specific context, and route tickets to the right vendor on the first try. Ultimately, the result is fewer callbacks, less downtime, and smoother operations for staff.
