Keeping track of and controlling access passes, visitor registration and key management can partly be left to AI, but not as a fully autonomous process. Registering, linking and administering access rights can largely be automated with robotic process automation (RPA). Determining who gets access to what and handling exceptions remains work for humans, or work with human oversight that approves or rejects with reason.
The task scores high on structuredness: a request for an access pass follows fixed steps, a visitor registers via a fixed form, key issuance follows a fixed schedule. That is exactly the kind of work RPA connects well with: the system recognises the pattern, carries out the registration, links the correct fields and logs the result. Volume is also relevant here. At a company with many changing visitors, suppliers and temporary staff, automating registration frees up more hours than at a company where the building mainly houses permanent employees.
An example: a receptionist who manually registers dozens of visitors daily, issues a pass and withdraws it again after departure, carries out work that an access control system with a linked workflow can largely handle itself. The visitor registers digitally, the system checks the appointment, generates temporary access and automatically closes it off once the validity period expires.
Two axes hold this back: compliance and cost of error. Who gets access to what is not just an administrative question. It touches on security policy, fire safety, and sometimes legal requirements around shielding certain spaces. An error here is not neutral: an external party gaining access to a space they should not have had access to, or an employee who still has a working pass after leaving employment, is a risk that is not expressed in money but in exposure. That is why assessing a request, and certainly deviating from standard rules, remains with a human who can explain why something is or is not granted.
Room for judgement also plays a role here. A permanent employee who loses a pass, a contractor who needs access outside working hours, a visitor without a valid appointment: these are situations in which someone has to judge what is appropriate, not only what the protocol says. AI can apply the protocol; recognising the exception and deviating from it responsibly is something else.
The shift already underway here is not that the facility employee or receptionist becomes redundant, but that the share of routine registration in that role decreases. The work that remains shifts towards oversight: assessing exceptions, checking whether the system has acted correctly, and intervening in case of deviations. That is a different kind of work than the current one, with less repetition and more judgement.
The extent to which this already works this way today differs strongly per company. An organisation with a digital access control system and a written-out authorisation policy can automate a large part of the registration directly. A company that still works with paper visitor logs and physical key boxes must first set up those preconditions before there is anything to automate. The task itself does not change; the degree of readiness of the systems behind it does.
This task rarely stands on its own. In a building where machinery, hazardous substances or sensitive information are also present, the cost-of-error axis is higher than described here, and the whole shifts further towards human work with oversight. Compare this with how energy and utility consumption of a location is monitored: there too, registration can be strongly automated, but without the compliance weight that access management does have. Companies looking at several of this kind of facility tasks at once often see that the pattern is recognisable from other corners of the organisation, such as with receiving and logging incoming goods: structured, high volume, but with a checkpoint where a human assesses the exception.
The sector also makes a difference. In the installation sector, where personnel and subcontractors work at different locations on a daily changing basis, the volume of access registrations is often higher than in an office environment with a fixed workforce; those who want to see this more broadly can look at the findings on what AI takes over in the installation sector.
This page describes one task based on a fixed assessment framework. Whether this also holds true for a specific building, with a specific security level and a specific workforce, is something that differs per situation. For those who want to know how this plays out within their own organisation, there is a free quickscan: twelve questions, no account required, with an indication of what part of the hours in that profile can be taken over by AI today. The full work scan, which breaks down the work of an entire company task by task, is still under construction.
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Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.