When to Use the A.I. Special Sauce in Your Experiential Marketing

Finding effective and meaningful applications

As experiential marketers, it is our job to anticipate trending technologies and determine how they can be applied to our clients' activations. 

We've seen a lot of technology rise (and fall), including projection mapping, Microsoft Kinect, VR, AR and drones. For the past couple of years, artificial intelligence and machine learning have become the latest buzzwords — and the hype seems to be hitting a new high.

A.I. and machine learning are vast concepts that are touching nearly every other technology these days — voice assistants, chatbots, recommendation engines, self-driving cars and your everyday run-of the-mill Killbot 5000. 

The challenge we face as an experiential industry is finding ways A.I. can be used effectively and meaningfully in the type of work we do. As A.I. tools become more accessible and the underlying concepts are more digestible, we will see more and more requests to basically "Just put some A.I. on it!" like it is a delicious sauce to be slathered on everything.

However, we still have a lot of work to do to get A.I. to a point where it's really contributing meaningfully. It's not a flash-in-the-pan technology. It is here to stay. Here is how to decide whether A.I. is the right thing to use within your activation. 

Three methods/questions to ask yourself when considering whether to apply A.I. to your project: 

Does applying A.I. enhance your story in a compelling way? 

A.I. can require a lot of work to get to something interesting, so make sure your project is benefiting from something more compelling than novelty. If the most interesting part of the project is that it is using A.I., you are headed down the wrong path. 

If your idea requires a large amount of consumer data, do you have access to that data and are there security concerns about using it? 

Getting out ahead of requests like this help smooth out the development process once you have buy-in from other teams. 

Do you have a lot of time? 

The initial investment can take some time to determine if a problem is easily solvable. Also, once you roll out a solution, you may find it's not landing the way you expected. Giving yourself a chance to iterate on the idea can help lead to a more meaningful outcome. 

Once you do decide to use A.I., how can you set up for success? 

• Gather as much information as possible about data you have available to you.

• Be up front about how your data can be supplied to vendors. Coming up with protocols ahead of time will streamline the production process later on.

• Talk to your internal teams about interesting conclusions that could be drawn from the data and decide how it can be used.

• Finding bigger budgets and approaching projects well ahead of time will dramatically improve the quality of work. Huge payoffs in the end require risk, risk requires experimentation, and experimentation requires time. 

• Support and get to know artists and research institutions that are doing interesting work. New directions may come from somewhere outside of our industry. 

• Analyze what worked and what didn't so you have a good platform for improvement. 

A.I. has a lot of potential in nearly every business sector. Self-driving cars, content recommendation engines, smart devices, medical applications— these are just a few cases that are driving research into various areas of A.I.. Experiential as an industry will benefit from big movements and will certainly make use of the technology as it becomes more and more digestible for common use. 

The good news is that working with A.I. is getting easier in 2019. There are more off-the-shelf tools emerging that allow us to quickly try out ideas without requiring a PhD in mathematics. As these tools become more accessible and digestible, we will be able to find even more impactful ways to apply them to new experiences. 

Profile picture for user Blair Neal
Blair Neal
Blair Neal is director of creative technology at Fake Love.

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