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The Joint Commission (TJC) accredits 22,000+ organizations including 4,000+ hospitals. For many, the survey remains one of the most demanding operational challenges in healthcare. It’s difficult to maintain continuous readiness across clinical operations, facilities management, life safety, and emergency preparedness. The standards are rigorous, expectations are high, and consequences of noncompliance are significant. But the real challenge is the operational complexity required to meet them consistently.
Many organizations find themselves drowning in data but starved for insight, with no unified view across dozens of systems. Even with stringent policies in place, there can be limited real-time visibility into whether those policies are being followed. There may be dedicated teams, but those teams are often stretched thin and forced to operate reactively.
This is where Operational AI, powered by Willow and its AI companion Willow Copilot, becomes transformative. Going beyond task automation, it helps interpret standards, monitor the environment, predict risks, guide staff, and ensure that compliance is embedded into daily operations. Willow’s rich ontology defines key systems like fire prevention for life safety, and the Knowledge Graph breaks down silos across the BMS, CMMS and other sources of real-time data. In support of continuous preparedness, Skills enable ongoing monitoring and Insights help identify anomalies. Willow Copilot taps into customer documents, data in the Knowledge Graph and domain knowledge around codes and standards, giving hospitals a new way to achieve and sustain Joint Commission readiness.
Let’s dig into the top five challenges hospitals face in preparing for TJC surveys, and how Operational AI with Willow enables ongoing readiness.
Joint Commission standards are comprehensive, detailed, and often difficult to translate into daily operational behaviors. Facilities teams, clinical staff, and administrators must be able to quickly access, contextualize and interpret hundreds of requirements in codes. These range across Environment of Care (EOC), Life Safety (LS), Emergency Management (EM), equipment and utility systems, infection prevention, and documentation and evidence requirements.
How Operational AI Helps
Imagine a scenario where a sprinkler head got painted over during a repair. In the next inspection, a photo is taken and uploaded in Willow. As part of generating a document twin, an AI-generated summary captures that this is in violation of NFPA standards.
Willow Copilot taps into document summaries as well as NFPA standards. This makes it easy to ask in a conversation about requirements as well as relevant codes.
In context of the inspection document, Willow Copilot explains details of why this is a problem. It elaborates on the compromised functionality of the asset and what action should be taken.
Operational AI can interpret standards, map them to operational workflows, and automatically identify which assets, spaces, and processes are affected. This makes it simple to generate and track compliance checklists, inspection routines, and even preventive maintenance schedules. Willow Copilot becomes the conversational layer that explains standards in plain language, answers staff questions, and guides them through compliance tasks in real time. It’s like having a Joint Commission expert available 24/7.
Documentation is one of the most common pain points during surveys. Surveyors expect real-time, accurate, and complete evidence of compliance. On the CMMS side, this includes Preventive Maintenance (PM) logs, and work order completion data. In addition, LS inspections, emergency drill documentation, and asset histories may be scattered across paper binders and department-specific tools.
Operational AI can automatically extract, normalize, and structure documentation from multiple systems and store it as part of the Knowledge Graph with relationships to relevant assets and spaces.
Work orders including PM tasks sync with CMMS systems and are associated with twins in the Knowledge Graph. It’s easy to track which tasks were completed, which ones are in progress or even overdue. This work order history can be reviewed by applying filters in the UX, or via a conversation with Willow Copilot.
Willow Copilot supports filtering on various combinations of fields to get to the information required in context of any ask during the Joint Commission survey. This includes Status, Job Type, e.g. Preventive vs Corrective, CMMS Source, Created Date, Due Date, name of the Assignee, related Asset, related Location and more.
This ensures that evidence is always ready and instantly retrievable through natural conversation.
Hospitals rely on dozens of systems to manage operations, but these systems often operate in silos. The BMS may refer to an Air Handling Unit as AHU AC-10-1 but the CMMS may refer to the same asset at AHU 10-1. This may result in real-time telemetry collected from the BMS to be completely disjointed from work orders on the AHU.
Willow unifies data across CMMS, BMS, IoT sensors and more, creating a single normalized operational layer. The Knowledge Graph maintains a digital representation that references identifiers for both the BMS and CMMS systems. Over time, as other systems are added to track occupancy or indoor air quality, each of their identifiers get added to Willow’s unique asset for the physical equipment. All this becomes a part of the larger digital twin that combines spatial, static and live data with 3D visualization of open work orders and insights in context of assets and their physical locations.
Willow’s digital twin is built on spatial context from the architectural drawings, and LS objects are visible on the floor plan. When problems occur, work orders can be autogenerated, strengthening the organization’s ability to maintain a single pane of glass.
Typically, TJC surveys are unannounced, and hospitals must maintain a constant state of readiness but operational realities make this a challenge. For facility teams, deferred maintenance, aging infrastructure and limited visibility into compliance gaps make TJC survey readiness a reactive scramble.
Operational AI continuously monitors operational data and alerts teams when compliance drifts with Skills and Insights.
Willow integrates data from various building systems in the Knowledge Graph and Skills enable conversion of this data into action. Willow’s Skills library is a large set of rules that continuously monitor telemetry and data from connected assets and systems. Skills define the logic and conditions for recognizing anomalies, faults, and opportunities for improvement. Skills are associated with models of assets like Fire Detectors, Air Quality Sensors, Air Handling Units or Refrigeration Equipment. All these models are defined in DTDL as part of Willow’s ontology and can be instantiated as twins with properties in Willow’s Knowledge Graph.
As a result, rules get applied to relevant telemetry points. Skills continuously evaluate telemetry data to check if rules’ conditions are met. When a rule detects a condition, e.g. a temperature out of range, high energy use, or abnormal vibrations, the Skill automatically generates an Insight. The Insight records the issue, its duration, any associated metrics/impact scores, and references the affected asset. Related insights get bundled together so the underlying root cause can be actioned. Work Orders can be auto-generated and assigned to relevant teams, creating an audit trail to action the insights and keep systems continuously ready.
Willow Copilot understands Skills and Insights, making it easy to ask conversationally if a PM is overdue, if a temperature sensor shows a deviation, whether an egress route is blocked, or if a life safety asset is past the expiration date. If a situation requires expanding the default library of Skills, customized use cases can be realized with Activate Studio. Notifications can inform facility teams when “A fire extinguisher in Zone 3 is overdue for inspection,” or “Humidity in OR4 is outside the acceptable range,” or “Three emergency lights failed their last test.” Continuous readiness becomes a natural byproduct of continuous intelligence.
TJC standards require that staff understand safety protocols, emergency procedures, and equipment operation. However, hospitals experience high turnover and inconsistent training reinforcement.
Willow Copilot can deliver contextual, role-specific guidance directly within an operational task. Compliance task lists and relevant documents can be uploaded as files related to assets. Users can ask questions with prompts and Willow Copilot responds by leveraging contents of upload docs combined with data in the Knowledge Graph and domain knowledge. As an example, teams can ask Willow, “How do I inspect this eyewash station?” and it does the heavy lift by finding the relevant information. As a result, training becomes embedded in the workflow.
Willow enables a shift from reactive to proactive TJC preparedness. Facilities can achieve continuous compliance by turning data into operational intelligence, embedding standards into workflows and predicting risks before they occur. Documentation burden is reduced with conversational access to operational knowledge. Willow’s Knowledge Graph gives hospitals visibility by weaving together data across systems. Skills enable actionable Insights. Willow Copilot adds accessibility. Together, they create a paradigm where daily operations become a predictable, data-driven continuously managed discipline.