This is a guest post written by Tim Groot from Grip
You’ve probably heard it already — Artificial Intelligence is the event technology of the moment. As a result, event professionals are increasingly expected to offer it as part of their event technology solution, keeping up with an events industry that continues to thrive on innovative new ideas.
Plenty has been written about its promise. After all, this is the year that Artificial Intelligence is coming into its own. But it’s important to know what you’re getting into because you want a solution that works for your company and changes your game. You want to be able to trust that the system will do the right thing for your clients and your brand.
The best AI enhances business processes that can build and customise customer engagement, and subsequently increase revenue. In terms of organising and managing events, this means enhanced attendee experiences through degrees of personalisation and more meaningful interaction with AI-enhanced systems that will delight attendees, exhibitors and sponsors.
On the development side, the management and stewardship of data will be key to AI systems in the events industry. At this stage, great AI needs good data to deliver on its promises, and for us at Grip, recognising the challenges of using meaningful data enables our AI to stay ahead.
1. Personalisation / Recommendations:
The biggest change AI is bringing to the game this year is personalising recommendations for event attendees, exhibitors and products on a scale that was previously unheard of.
Let’s say you’re an attendee at a 30,000-strong event. What typically happens now is that you would be matched, probably manually, according to some form you had filled in or interests you had indicated, and you would schedule your meetings from there. It can be tedious and expensive for event planners to manage.
An AI matchmaking engine can interpret data from social media profiles like LinkedIn and Facebook that attendees would have already populated and recommend people to meet, conference sessions to attend, or even products that would most suit their business interests. Attendees can schedule meetings before the event starts, or indicate they are not interested in the recommendations from the system, which helps improve the next set of recommendations. It’s a virtuous cycle.
We’ve found that 55% of people surveyed say they made a connection using our AI matchmaking engine that they wouldn’t have made otherwise. That’s simply because, working with real-time recommendations, that AI learns from your behaviour as you interact with it, and you’ll have better recommendations the more you use it.
With exhibitors, it’s all about time, space and staffing levels. Knowing who their potential customers are giving them great visibility. Knowing what their potential buyers are interested in before meeting them helps them to personalise their offerings and maximise the limited personnel, space and time they have during the event.
But – caveat emptor. In this field, not all ‘smart’ business matchmaking systems are equal; so it’s good to get a grip on the issues before you commit to any particular one.
2. Interface-less experiences:
Chatbots are becoming increasingly sophisticated. Yes, we’ve sniggered at the bloopers – like what happened when Microsoft’s “Tay” AI system learnt racism and hate speech from internet trolls last year – but things are changing and we’re seeing an increasing degree of sophistication in the kind of AI assistance we’re going to encounter at events.
With an easier-to-access conversation interface compared to an app (that has to be downloaded) or a website (that has to be logged into), AI-enabled chatbots have the technological capability to learn from previous interactions and personalise conversations.
In the future, the technology could potentially enable events to move away from having a dedicated event app, having, instead, all event content delivered through a Facebook Messenger chat bot. That could make it easier for events to get adoption for their technology.
3. Anticipatory computing
No discussion about Artificial Intelligence is complete without some mention of Deep Learning. It’s a form of machine learning based on layered representations of variables, and whose algorithms can be applied to various applications that rely on pattern recognition. These are complex systems that take plenty of time and expertise to build and run.
In practical terms, this simply means that the AI system takes sensory input, like data, and adds a component of reasoning to form new actions based on that reasoning.
In real terms, this could translate to a system reading footfall and registration data at an event, and anticipating what logistical requirements are needed at the venue in terms of beverages, food, and crowd control, as the event progresses in real time.
It would make these judgments based on data input from previous events of similar sizes and requirements, as well as on-site feedback of demand for the services provided.
4. Data protection and integrity
With all the talk of data input, comes concerns about data protection and integrity. This is an issue not only for AI, but for event technology in general, so it’s important to recognise this as one of the social impacts of technology on the industry.
While increasingly sophisticated analysis is applied to data, a balance has to be struck between data protection compliance while also encouraging creativity, innovation, and helping to ensure data quality. It’s a question of public policy that is being addressed on several fronts; the UK’s Information Commissioner’s Office has some useful principles to follow, and certainly, different companies will handle data differently.
Our AI system, for example, uses data to look for networking intent, and how well that was satisfied. Users are anonymous to each other until and unless they indicate they are both ‘Interested’ to meet. And private messages are private. When we provide insights — at an aggregated level — to event organisers and sponsors, it enables them to know which parts of their programme were the most effective, and where they got the best return on their investment from. It’s an important balance to strike.
Data integrity is not the most exciting part of AI development, but it’s a key component – high quality data in, good quality intelligence out, after all. So making sure data is maintained at an appropriate level will have big consequences for how it can be used.
How can event professionals take advantage of AI?
The events industry is very competitive. Every event tries to position itself a little differently and focus on a specific kind of market; some work with corporates, others with tradeshows, and some with associations and conferences. So every event app provider has its own best use case, and there is no ‘one-size-fits-all’ AI solution.
Given the complexity of AI systems, most event providers would not have the capacity to design and develop a correct AI experience, so the quickest way to get up to speed is to use an event app, with a convenient AI plug-in. Grip’s API, for example, is set-up to enable our matchmaking engine to easily integrate with most systems.
It may be a brave new world of Artificial Intelligence out there. But we’ve got a steady grip on the issues at hand.