Ticketing and AI

Fundamentally, after the robots have taken all the jobs, there will be nothing left for humans to do but create and consume culture. Live people will still buy tickets to see live people perform on stage, so this is a good business to be in. 

It doesn't matter how good the machines get at predicting the next word in a sentence or the next note in a tune, there will still be an audience for live performances. 

So if everyone can just calm down a bit...

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The first potential use we investigated for AI in ticketing was integration with personal voice assistants - Sira, Cortana, Alexa, etc. We imagined saying "Hey Siri, book me two tickets for the panto next week". 

I was quite excited about this in 2019:

 

We eventually decided this was not worth, because the information about which performances are available and which seats are available is not easily conveyed by voice, and a web page is actually more convenient. From a customer's point of view, phoning the box office to book tickets is less good than being able to see all the available performances and the seating plan on the website. Automated phone booking lines for cinema tickets are a thing I remember using and hating; having better speech recognition and natural language processing wouldn't help much there. Also, you would still need box office staff answering the phone to deal with exchanges and customer services and refunds, so we couldn't envisage either extra tickets being sold or money being saved by the venue as a result of this facility being available. And that at the end of the day means there's no reason to do it.
 

Another area we quickly dismissed was using LLMs to automate the text generation part of event setup. We don't think this is a good idea at all. Ticketing requires accuracy, and the risk that an LLM would hallucinate blurb containing incorrect prices or dates is unacceptable.

Dynamic pricing and predictive analysis tools are a good fit - but then they already exist, already use AI, at least they already use machine learning to crunch vast piles of data. And whilst we are happy to integrate with them on request, we have no plans to develop our own.