There was no shortage of future-gazing at strategy‘s Marketing Evolution: C-Suite Summit last week as technologists and trend-watchers pored over the possibilities that AI and AR will offer brands in the next few years. But all agreed that there are steps brand leaders must take now to make sure they’re not left behind when technology inevitably changes consumers’ expectations of brands.

Much of that preparation involves data, a topic that Steve Irvine, founder and CEO of Integrate.AI, understands is starting to overwhelm marketers. Interviewed on-stage by Mirum president Mitch Joel, Irvine said that big data is “the most abused term of all time” in business.

However, when asked why brands should care about their “big data” resources, Irvine said AI provides insights that have so far only been dreamed of among existing analytics offerings. “There’s a hierarchy” when it comes to getting a return on data investments, he said. “Prediction is something that AI can do a really good job at, a much better job than traditional analytics,” provided it has solid data to work from.

Craig Atkinson (right), PHD’s chief investment officer, told attendees that owned data is the key to future AI development. While he too conceded that marketers may feel as though they’re drowning in big data now, “we never had computers that were sophisticated enough to do anything with it… The data was never for us. It’s too complex for us. It was waiting for machine learning to show up.”

Atkinson said brands that don’t prioritize the collection and organization of solid customer data ignore a crucial “strategic asset” that will be the bedrock of future customer interaction – and that future isn’t far off.

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Drawing from findings in PHD’s future-looking Merge report, Atkinson predicts that consumers will soon expect to interact with artificial intelligence tools just about everywhere. What has begun in the home with Siri, Alexa and voice assistants, he said, will soon extend to cars, retail stores and most public spaces.

“You’re just going to be able to expect to speak out loud and an AI will hear you,” he told attendees.

Consumers are being “trained” now to ask their devices questions, he said. They’re “increasingly buying devices that can use [machine learning tools] and will adopt it further and further. I do think we’re two to three years away from it being more than a curiosity.”

Because current consumer data will feed and teach brands’ AI and machine learning tools, this makes data a strategic asset.

Changing the status quo
One of the problems companies currently face in managing their data is the belief that it should be “owned” by one group within an organization, he said. Prioritizing data “challenges all the constructions of modern businesses” because companies are generally built into silos. “But data doesn’t see silos. Consumers don’t see silos. They don’t care if IT holds that data or CRM holds it and they don’t like to share. They have higher expectations than that.”

Atkinson used several case studies of current and emerging technologies that illustrate the value of well-collected data. Google’s Visual Positioning Service (VPS), for example, layers data from tens of millions of images uploaded to the service over camera feeds on consumers’ phones. So someone walking through a large store can use their phone display to see where a needed product is and get a route to it mapped onto the display in real time.

Unlike current technology that relies on satellite GPS systems to do this, VPS relies only on customer photos, which machine learning software sorts in real time to understand what a store and its wares look like (and whether a given product is currently in stock). That system relies on clean, well-managed client data.

“A lot of time and attention has been spent on ecommerce, and rightfully so,” Atkinson says. “But these are great examples of taking in-store experiences and making them that much richer and more engaging for consumers.”

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