Somewhere in Britain, right now, someone is on hold. They have heard the same four bars of Vivaldi seventeen times. They have been told their call is important. They have been told, in a tone of very mild regret, that due to unprecedented demand wait times are longer than usual. They are, to a first approximation, furious.
And yet, if you asked them exactly what had upset them, they might struggle to say. Was it the time? Was it the music, the voice, the word ‘unprecedented’? Or was it the creeping suspicion that nobody was coming, that the queue they had joined might not, in any meaningful sense, be a queue at all?
This is the odd thing about queuing. It is almost never about the queue.
For about sixty years, every time a technology has promised to fix the problem of waiting, customers have found fresh and imaginative ways to remain annoyed. Which brings us to the moment we are in now.
The question, after the viral chatbot disasters and the quiet chatbot triumphs of the last two years, is whether AI, with its convincingly human voices and its three billion interactions a month, can finally solve a problem that has baffled industrial engineers, airport planners, theme park designers and contact center managers since roughly the Eisenhower administration.
The short answer is: probably not in the way you think.
Why the Psychology of Queues is Almost Never About the Queue
Some years ago, Houston airport had a problem. Passengers kept complaining about how long they waited at baggage claim. The airport, being sensible, did the sensible thing. It hired more baggage handlers. Wait times fell to an industry-best eight minutes. Complaints continued.
The analysis was eventually conducted by Richard Larson, the MIT professor known, charmingly, as Dr Queue. It turned out passengers were walking a minute from the gate to the carousel and then standing for seven. So, the airport moved the arrival gates further away. Passengers now walked six minutes and waited two. Total time unchanged. Complaints vanished.
The lesson is almost banal and almost always forgotten. What we experience as waiting is not a number of minutes. It is a number of emotions.
As Larson put it:
"Often the psychology of queuing is more important than the statistics of the wait itself."
We have built an entire multi-billion-dollar queue management industry on the assumption that queues are fundamentally an engineering problem, when in truth they are fundamentally a humanities problem.
David Maister and the Eight Rules That Still Govern How We Wait
The person who did the most to formalize all of this was a former Harvard Business School professor called David Maister, who in 1985 published a paper titled The Psychology of Waiting Lines. Four decades on, it remains the most stolen-from piece of writing in customer experience.
Maister began with what he called the first law of service: satisfaction equals perception minus expectation. If the sign says twenty minutes and you wait fifteen, you are delighted. If the sign says five and you wait seven, you are livid. The wait is the same. The sign did the work.
His eight principles explain everything that follows. Occupied time feels shorter than unoccupied time. Pre-process waits feel longer than in-process waits. Uncertain waits feel longer than known ones. Unexplained waits feel longer than explained ones. And unfair waits feel longest of all.
That last one is the killer. Research by Harvard's Ryan Buell found customers at the back of a line are 3.5 times more likely, per second, to abandon it than those with even one person behind them. When he removed the cues of being last, abandonment fell by 43.5 percent. Customers aren't bailing because the queue is too long. They're bailing because they can't see anyone worse off than themselves.
Fairness, not speed, is the thing we are actually measuring when we stand in line. We will wait a very long time if we feel the system is playing straight with us. We will leave quite quickly if we feel it is not.
Waiting Is No Longer Just a Phone Problem
There is a further complication. The waiting room has moved. Or rather, it has multiplied.
For most of the twentieth century, the queue was a single channel: you stood in a line, or you stayed on hold. The psychology Maister described was essentially linear. Today, a customer's wait might begin in an app, migrate to a chatbot, pause in an asynchronous messaging thread, resume in a callback, and conclude - if they are patient enough - with a human agent on a video call. Each transition is its own small act of abandonment. Each new interface resets the customer's sense of where they are in the process.
The research on omnichannel waiting is younger than Maister's principles, but its findings rhyme with them. Customers tolerate asynchronous waits - the held email, the 'we'll get back to you' message - significantly better than synchronous ones, provided they believe someone has actually received their query. The uncertainty principle remains. What has changed is the scale of the uncertainty: in an omnichannel environment, customers can be unsure not just about when they will be helped, but about whether the different parts of the system know they exist at all.
The Great AI Queue Disasters of 2024
In late February 2024, Klarna's CEO Sebastian Siemiatkowski announced, with some fanfare, that his company's new OpenAI-powered assistant had handled 2.3 million customer conversations in its first month. This, he said, was the equivalent work of 700 full-time agents. Teleperformance, a large, outsourced contact center company, saw its shares drop 29 percent on the news.
The pattern repeated across the industry. A Canadian tribunal ruled Air Canada liable after its chatbot wrongly promised a bereavement discount - the airline had argued the chatbot was a "separate legal entity" responsible for its own actions.
In each case, the technology answered the call. It just failed at the human part. The maths won, and the psychology broke.
