AI task assignment that suggests, while a person decides

How assignment works

Every TaskLoop task has an owner, a priority, a deadline and instructions. On the admin dashboard, reception or a supervisor sees each department’s workload in real time. AI-assisted assignment adds a suggestion to that view: who is best placed to take the new task, and how urgent it is. The supervisor accepts the suggestion or overrides it.

The aim is to save the desk a few seconds on every routine assignment during a busy check-out, not to take decisions away from the people who know the team.

The workflow, step by step

1. A request arrives

A guest scans the room QR code, a resident scans the code in the lift lobby, or reception registers a call. See guest and tenant requests.

2. TaskLoop suggests

Instead of an empty “assign to” field, the dashboard shows a suggested owner and priority, for example “Housekeeping, Maria, normal priority”. The suggestion is based on current workload, skills, location and how similar tasks went before.

3. The supervisor decides

The supervisor reads the suggestion and either accepts it or changes it. That keeps a person responsible for every assignment, which matters when a request is sensitive, the guest is a VIP or the obvious choice is about to go off shift.

4. The outcome feeds back

Once the task is completed and rated, its response time, completion time and rating join the history that later suggestions draw on. The same data feeds the reports.

Who it is for

• Front desk / reception at peak times, when ten requests arrive at once.
• Duty managers covering several departments on a night shift.
• Supervisors in larger teams, where it is harder to keep track of who has spare capacity.

Small teams, where the supervisor knows everyone’s workload at a glance, may override suggestions more often. That works fine, because the supervisor always has the final say.

Facility management companies with crews across several sites are a strong fit, because the dispatcher cannot see every technician’s day at once and location is one of the signals. Even there, the suggestion is a starting point and the dispatcher makes the final call.

What the screen shows

On the dashboard, a new task shows a suggested owner and priority next to the usual assignment fields, with a clear option to accept the suggestion or choose someone else.

Principles we hold it to

• Assistive, not autonomous. A supervisor can always override a suggestion.
• Grounded in your own data. Suggestions come from the workload, skills, location and history recorded in TaskLoop.

Getting good suggestions

Suggestions are only as good as the information behind them, and most of that comes from how your team already works on the admin dashboard. Assigning to a department rather than a person lets whoever is free pick the job up from the staff app. Deadlines and escalation make sure a poor assignment is corrected quickly rather than discovered at the end of the shift.

A few practical habits help:

• Assign routine requests to departments. Towels, amenities and simple fixes rarely need a named person.
• Assign skilled jobs to named people. Chiller faults, VIP rooms and anything with a history should go to someone specific.
• Review late tasks weekly. The reports show where assignments regularly go wrong, which is the same history the suggestions learn from.

What it doesn’t do

• Replace the supervisor. The AI suggests, and the supervisor can always override it.
• Rosters. TaskLoop does not build staff schedules or rosters.