Can AI Actually Fix the Work Order Workflow?

You can’t manage a facility without a solid approach to work orders. An argument can even be made that work orders are the backbone of facilities management, yet many facilities teams are forced to work with a broken system. 

From incomplete information to missed deadlines and inefficient communication with vendors, today’s work order workflows are a mess. They are riddled with inefficiencies that cost the organization time, money, and operational efficiency. This is especially true if you are dealing with an outdated CMMS. 

With the growing popularity of AI, many facilities managers find themselves asking the question: Can artificial intelligence transform this critical process from a source of frustration into a competitive advantage? In other words, can AI fix bad work order workflows? 

Work order systems need improvement, we all know that. But facilities professionals are not sure how AI can deliver the solutions they need to make those improvements. The promise of AI-powered work order management is exciting. However, it’s important to separate realistic capabilities from marketing hype. To do so, you’ll need a strong understanding of both the current challenges of work order management and the practical applications of artificial intelligence in facilities management. 

What Does the Current Work Order Flow Look Like?

Broken work order processes cost organizations far more than they might realize, as the costs are often hidden. Yet every day, poor work order workflows cause headaches, bottlenecks, delays, and unnecessary costs. 

Here are some examples: 

• If a store manager submits an incomplete work order, the facilities manager may end up spending valuable time chasing down the missing information before they can dispatch the right technicians/vendors 
• If organizations are limited to manual processes, it’s easier to make mistakes that slow down maintenance workflows 

• If invoices are handled manually, the workload is time-consuming and error-prone 
• If lost tickets are commonplace within an organization, it leads to miscommunication between teams, departments, and contractors–and more delays

The real problem isn’t just inconvenience. The problem is that these delays add up to a serious financial impact. Organizations lose money when their work order management systems aren’t set up for success, even if they have highly skilled technicians doing the work. 

These losses stem from:

• Manual tracking and data entry processes
• Extended equipment downtime
• Poor dispatch processes that delay repairs
• Difficulty validating vendor compliance and insurance
• An inability to prioritize work orders effectively

How  a Workflow Breaks Down 

Traditional work order workflows follow a predictable timeline of inefficiency: 

1. A manager submits a vague work order with the description: “AC isn’t working.” 
2. The facilities manager has to chase down missing information before dispatching a vendor
3. The technician arrives unprepared, with the wrong equipment
4. Multiple visits are required to address the problem; this increases the total cost of repairs 
5. Customers leave because it’s too hot to shop; this is lost revenue

Unfortunately, this scenario plays out thousands of times every day across multi-site organizations.   Poor work order management can take a process that should be finished in a few hours and turn it into a days-long ordeal. 

How Manual Processes Compound Problems 

Countless organizations nationwide still rely on manual processes for some or all of their work order management. These manual processes often lead to:

• Lost tickets
• Incomplete tickets 
• Inaccurate information on tickets 
• Miscommunication between teams
• Ineffective vendor performance tracking 
• Delayed invoice payouts 
• Incomplete maintenance history records 
• Increased potential for compliance-related fines 

What you can see in this list is that these pain points affect everyone: Facilities managers, store managers, team members, third-party vendors, finance teams, and even customers. 

Could Smart Systems Take the Guesswork Out of Maintenance?

Proponents of AI are making a lot of big promises about everything it can do–or will be able to do soon. Smart systems equipped with AI capabilities offer a new, exciting approach to work order management. 

Replacing manual processes with AI-powered platforms allows companies to analyze patterns, predict needs, and automate routine decisions that have historically required extensive human oversight. 

Simple task automation is one thing, but AI has the potential to go much farther than that. AI can handle multiple variables at the same time, and it can process vast amounts of data that would overwhelm any human operator. 

Some of the things that machine learning can analyze simultaneously include: 

• Historical work order data
• Equipment performance patterns
• Vendor reliability and performance metrics
• Seasonal trends

Taking the guesswork out of maintenance is all about making data-informed decisions. All of this means that AI can provide more informed recommendations about maintenance priorities and resource allocation.

Predictive Capabilities vs. Reactive Responses

One of the drawbacks of traditional work order management is the fact that it often operates in a reactive mode. After all, the chain of events is typical: a problem occurs, a work order is created, and repairs are scheduled. 

Smart systems, powered by AI, support a shift toward preventive maintenance strategies. Instead of waiting for problems to arise, facilities managers can anticipate potential issues before they occur. They can also prevent equipment failures and operational disruptions. 

This early fault detection capability reduces downtime and minimizes the impact on facility operations. It also optimizes your maintenance schedules based on equipment condition. 

The Role of Automated Decision-Making in Complex Scenarios

Smart automation systems can make more sophisticated decisions, even in truly complex scenarios. (And if anyone knows how complex things can get, just ask a facilities manager!) 

Smart automation systems can: 

• Tap into huge data systems
• Implement business logic in decision-making
• Automatically dispatch vendors based on a variety of factors 
• Customize solutions to your unique business operations 
• Ensure proper documentation of complicated work 

How Can AI Help Bridge the Gap? What Are Some Other Use Cases for AI in Facilities Management?

Let’s consider some other ways that AI can be used in facilities management to improve operations and reduce downtime by improving workflow management.

1. AI can streamline work order creation and processing 

The initial work order creation process can be messy, but it doesn’t have to be. AI can transform this first step by guiding users through structured inputs that capture all necessary information from the outside. 

AI’s language processing capabilities make it possible for an AI platform to interpret conversational descriptions of problems, then categorize those descriptions appropriately. They can be prioritized based on urgency, vendor availability, cost, compliance requirements, and available resources. 

These same systems can also eliminate duplicate work orders, which are surprisingly common in facilities management–especially for organizations with multiple locations. AI can cross-reference existing tickets and identify similar issues reported across multiple locations. 

2. AI can optimize your vendor selection process

One of the most valuable applications of AI in work order management involves intelligent vendor selection and automatic dispatch. 

AI systems can analyze multiple factors simultaneously–including vendor performance history, current availability, geographic proximity, trade specialization, and cost considerations. This means you can instantaneously identify the optimal service provider for each specific situation. 

3. AI can reduce your energy consumption and help you cut costs

Beyond work order optimization, artificial intelligence offers numerous applications that enhance overall facilities management effectiveness. Sentiment analysis capabilities can monitor post-work completion reviews and alert facilities teams to areas where user dissatisfaction is particularly high, enabling quick intervention to address systemic issues. 

Energy management represents another significant opportunity for AI implementation. Data analytics and machine learning can analyze energy consumption patterns, identify inefficiencies, and suggest optimal energy usage strategies. These capabilities help organizations optimize resource allocation while supporting sustainability initiatives and compliance requirements. 

Everyone loves the idea of reducing energy consumption. Facilities managers get to reduce their budget spending, which will give your CFO something to celebrate. Consumers like it, too, as they have a strong preference for energy-conscious companies. 

4. AI can support smart building integration and IoT connectivity 

Facilities managers who are helping with the transition to smart buildings are excited about AI-powered sensors, as they can continuously monitor both equipment performance and environmental conditions. 

These AI sensors can detect performance anomalies in real time, then inform managers of potential issues. The integration of Internet of Things (IoT) devices with AI platforms creates opportunities for sophisticated asset management of high-dollar equipment. 

AI algorithms can process data from multiple sensors to predict maintenance needs, optimize operational efficiency, and extend asset lifecycles through better-informed maintenance scheduling. 

5. AI improves documentation and compliance 

Compliance with state and federal refrigerant management rules is paramount for every modern organization. If you have an HVAC/R system, you’re probably responsible for some pretty strict compliance rules. (Check our guide to the AIM Act to learn more.)

AI systems can automate the documentation and compliance processes that traditionally require significant manual effort. 

Ready to Transform Your Work Order Management? Fexa is Ready to Help 

The potential for AI to revolutionize work order workflows is clear, but effective implementation requires the right foundation. Modern CMMS platforms that incorporate intelligent automation capabilities offer immediate benefits, all while providing the infrastructure necessary for future AI enhancements.

Effective work order management starts with robust systems that eliminate those frustrating manual bottlenecks. Your work order technology should provide real-time visibility into your maintenance operations and enable data-driven decision-making. 

Organizations that establish these fundamentals position themselves to take full advantage of AI capabilities as they continue to evolve.

Ready to see how modern work order management can transform your operations? Book a demo with Fexa today to discover how automated workflows, intelligent dispatching, and comprehensive reporting can reduce costs, minimize downtime, and optimize your maintenance operations across all locations.