Almost everywhere we look, artificial intelligence is causing a fundamental shift in the way people work.

As AI begins to automate those mundane, repetitive tasks, employees’ focuses will transfer to what truly needs human judgement. As part of our 2020 Events Disruptor Report, I explored how these changes enable workers to become more empathetic, focusing on tasks that need high EQ and relationship building skills.
Building great AI processes is predicted to deliver huge business value, with a McKinsey report predicting the AI economy to be worth $13 trillion by 2030, with 70% of businesses adopting AI.
These impressive predictions belie the challenge of successfully integrating artificial intelligence into a business’ processes, requiring focus on the most nuanced corners of decision making and user experience to deliver value to customers in a way that is better, faster or smarter.
Switching to this approach can be a minefield, but there are many examples of companies who do it well whom we can learn from. These companies range in industry from fashion to music streaming, but all share a deep-level understanding of both their in-house and customer processes as well as the technological understanding to apply the correct solution to a user problem.

Decision-Making Processes

In the fashion industry, the clothing delivery subscription service Stitch Fix is a brilliant example of designing core processes around the inclusion and guidance of data science and artificial intelligence. It’s clear from their brilliant data storytelling, that they have considered every inch of their business proposition to highlight key areas where they can give customers more value than their competitors.
This has allowed them to algorithmically improve the efficiency of clothing recommendation and supply, even down to making the most agreeable pairing of a customer with an expert stylist.
 A central part of building a strong AI process for Stitch Fix is the modelling of a customer’s decision to keep or return the clothing that they are sent. There are many factors in this decision, including the customer’s stylistic preferences, the individual fit of the clothing and the future opportunities to wear such an item.
This combination of stylistic and practical considerations in a user’s choice is something which we see a lot of in HeadBox’s customers. The decision-making process will include stating a preference for style and form of venue as well as requiring key metrics such as price, location and capacity. Together, these emotive and logistical factors will combine to represent the user’s ‘dream event’.

1. Auto-pilot: Taking on tasks that are repetitive and repeatable, enabling workers to do work that is more productive, more effective, and that makes best use of all of those billions of neurons in our brains.
2. Co-pilot: Enhancing and augmenting our ability to make decisions, providing focus on the next most important action to work on, all allowing workers to spend time on more human face-to-face high EQ activities – the things that computers won’t be able to do for a very long time.

At HeadBox we are already utilising AI to make venue recommendation more powerful. This includes using computer vision technology to develop a deeper understanding of venue styles and sub-styles which have informed our user’s decisions in the past. When applied to our industry-leading venue image database this gives us a great advantage in making more intelligent recommendations.
This insight can be combined with more accurate event cost prediction and factors such as location and event history. All of this enables us to turn our event teams and search users into superheroes, delivering a faster, more effective and more empathetic service to our customers.

Content Delivery and User Guidance

Modern technology users are increasingly coming to expect a curated and personalised experience from their everyday software. This has been driven by tech giants such as Netflix and Amazon using enormous datasets to predict what a user wants before they have even visited their site. In recent years, companies such as Airbnb have gone beyond making simple personalised suggestions, instead of striving to understand the broader intent of a user.
In 2020, we will continue to develop our understanding of our customers’ needs to allow us to deliver personalised content in real-time, designed to ensure HeadBox users get the most out of the platform. This may be in the form of AI-driven cost predictions to give Guests advice on setting a date for a major event to maximise cost savings and venue availability.
It will also enable us to create ‘Super-Hosts’ who understand their Guests far better, through industry-wide insights, tone-of-voice recommendation and auto-suggested responses to enquiries.
Our 2020 Events Disruptor Report is a collection of articles that explore how and when the emerging trends in technology impact the events industry. To read the full report click here.

Read the latest edition of CEO Corner – My 2020s prediction: AI will transform the events industry.