Introduction
An AI operating model defines how information becomes a decision, how that decision becomes work, and how the result improves the next decision. For facilities teams, it starts with the daily operating record: a service request, an asset history, an approved scope, a technician update, and evidence that the issue was resolved.
An Autonomous Enterprise is an operating ambition: routine work moves through clear policies, people handle exceptions, and each completed job strengthens the information available for the next one. The degree of autonomy should depend on the task and the consequences of a mistake.
This guide explains how to choose a first workflow, prepare its data, assign decision rights, and evaluate a controlled rollout. The examples describe an operating approach; the capabilities available in any implementation depend on its systems, integrations, and configuration.
Build a complete operating loop
Consider a recurring refrigeration fault across several locations. A useful process connects the incoming report to the correct equipment, checks earlier repairs, establishes urgency, assigns an authorized response, and records whether the repair held. A recommendation without that context leaves the coordinator to rebuild the story.
- Signal: Capture the request, alarm, inspection finding, or planned maintenance event with its location and asset.
- Understand: Review operating history, symptoms, access requirements, warranty information, and open work.
- Decide: Apply the organization’s priority, spending, and authorization rules. Identify missing information before proceeding.
- Execute: Send the approved work to an accountable person or provider with the required scope and evidence standards.
- Learn: Record the diagnosis, actual work, cost, completion evidence, and any repeat failure.
The loop needs an owner at every handoff. A missed acknowledgement, an unavailable provider, or an unapproved scope change should create a visible exception with a next action.
Choose a first workflow with a clear boundary
Begin with work that already has a recognizable start and finish. Intake classification, a draft service summary, or checking whether required closeout fields are present can provide a manageable starting point. Define the decision you want to improve before choosing the technology.
For an intake pilot, the input might be a requester’s description and photos; the output might be a suggested trade and priority. A coordinator reviews the suggestion before dispatch. Compare the suggestion with the final classification and record why the reviewer changed it.
- Define the eligible locations, trades, and request types.
- List the actions the system may suggest and the actions it may take.
- Specify which missing fields stop the workflow.
- Name the reviewer and the fallback process when the system is unavailable.
Keep emergency response, hazardous work, and commitments outside the pilot unless the responsible operating leaders have explicitly designed and approved the controls for them.
Prepare the operational record
Use stable identifiers for locations, assets, work orders, and providers. A location nickname in one system and a store number in another should resolve to the same place. Separate a reported symptom from a confirmed diagnosis so later analysis does not treat a guess as a fact.
Agree on what each status means. Completed work, accepted work, an approved invoice, and a paid invoice describe different events. Preserve the event times and the person or system responsible for each change.
- Request context: site, asset, symptoms, priority, access, and requested service.
- Decision context: approved scope, spending limit, approver, and exception reason.
- Execution context: assigned provider, visits, parts, work performed, and delays.
- Outcome context: evidence, acceptance, repeat visits, final charges, and unresolved issues.
Give users a simple way to correct a record. Keep the correction and its reason visible, particularly when a later decision relied on the original information. Access should follow the role and scope of the work.
Set decision rights and exception handling
Write down who may recommend, approve, and execute each action. A generated service summary can be reviewed by a coordinator; a revised spending commitment may require an authorized approver. Those responsibilities should remain clear when a workflow includes AI.
Use a practical escalation record: what happened, what information is missing, who owns the decision, when a response is needed, and what is permitted while waiting. A confidence score alone does not explain whether the proposed action is appropriate for the site.
For example, a suggested repeat repair may conflict with a recent replacement approval. The workflow should surface that conflict and pause the commitment for review. Record the resolution so the next request sees the updated asset history.
Keep a usable record of the inputs, recommendation, approval, and resulting action. Give operators a way to stop automation and return to the established manual workflow.
Run a pilot and measure the whole job
Start by observing the existing process. Record how long requests wait for classification, how often they are reassigned, and how much information coordinators must chase. Define the sample and measurement period so the comparison is meaningful.
Run the proposed workflow alongside the current process, then allow reviewed suggestions for a limited group. Check both routine cases and exceptions before extending its authority.
- Operational result: time to a correct assignment, missed handoffs, and repeat visits.
- Quality: incomplete records, incorrect suggestions, and reviewer corrections.
- Human effort: time spent preparing, checking, and repairing outputs.
- Cost: implementation, integration, ongoing operation, and review effort.
A faster first response is useful only if it leads to the right work. Review results with site teams, providers, operations, and finance. Expand when the process performs consistently and the team can explain failures, recover from them, and support the next group of locations.
How myWork can help
myWork brings the work order, provider activity, approvals, and completion evidence into a connected operating record. That shared context gives teams a place to standardize workflows and identify where better information or controlled automation can help.
Start with one operating problem and the people responsible for resolving it. Map the record they need, the decisions they make, and the evidence that confirms a successful outcome. Then discuss the integrations and configuration required for your rollout.
Explore myWork Enterprise or talk with our team about your operating model.