Companies need to stop AI-washing their products

As I think about the parallels between Artificial Intelligence (AI) and technologies that have had an impact on their marketplaces, I often come back to the analogy of hybrid and electric cars. People who buy those cars may have a basic understanding of how the technologies work, but most tend to focus on the benefits that come with an investment in the technology, notably spending less on gas while also helping to save the environment.

For today’s consumers, it’s not necessarily the technology itself that’s most important but rather the impact that the technology has on the lives of their users. That’s why it’s frustrating for me to see companies that tout AI in the marketing of their products and services, as opposed to the experience that AI offers.

As AI continues to make a name for itself, especially in the ecommerce and retail industries, it’s important to look at how consumers view its rise. A 2016 study by Hubspot Research, for example, found that nearly 90 percent of consumers around the globe are either interested in AI tools or are willing to try them. What’s especially interesting is 63 percent of the study’s respondents had already been exposed to AI without even knowing it.

It’s no wonder than companies are quick to pitch their AI capabilities at trade shows and in their  marketing materials and sales pitches. But are they being completely honest about the AI in their products? After all, there are variants of AI — such as machine learning and deep learning — that provide varying results and experiences. And that may lead to blurred lines of what really qualifies as artificial intelligence.

But rather than question how companies are pitching their AI capabilities, I’d rather outline and address some of the core questions and concerns about what to look for in AI products and services popping up across the consumer marketplace.

Beware of AI-washing

As I noted above, not all forms of AI are the same. A machine-learning system such as IBM’s Watson, for example, utilizes the information it has available to answer questions and make decisions, based on probabilities and such. But it doesn’t have the capabilities to remember and apply an understanding of what may have happened in the past.

This is fine if Watson goes against humans in a Jeopardy showdown. However, it takes a deep-learning type of AI to perform the tasks that will likely resonate the most with consumers. This type of AI stores what it has learned in the past, takes note of how variables and results have changed under different scenarios and then makes decisions based on that.

An ecommerce site may utilize a chatbot that knows what the product inventory looks like, how to calculate shipping information and complete the sale — no human cashier needed. But, without a deeper learning, it cannot make recommendations about other products that a specific shopper might like based on previous visits. Without an understanding of what’s happened in the past, the machine cannot provide an optimal customer service experience.

Brands are falling behind the AI curve

When brands don’t respond to the changes in customer habits or technology, they can quickly fall behind their competitors. The same goes with adoption of AI tools, which is beginning to redefine what instant gratification means.

AdWeek sounded the alarm for brand marketers earlier this year by declaring that the instant gratification inflection point is fast approaching. In today’s world, consumers have come to expect things to happen in real time, whether that’s communication, news or shopping. In the post, Adweek noted that “the point of engagement and the point of transaction are converging, meaning brands that can offer immediacy, personalization, authenticity and accessibility will win out.”

Or, to say it another way, brands that don’t adapt and explore ways to give customers what they want, when they want it, will soon find themselves not just behind the AI curve but behind the overall competitive curve.

Companies are missing the point

It’s one thing to implement an AI strategy into business and quite another to talk about it. Think about the hybrid car analogy again. Are consumers being subjected to advertising that explains how those cars work so that buyers can be better informed? No, they’re not.

Instead, consumers are being fed information on how much money they’ll save at the pump or how they’ll emit fewer emissions into the atmosphere. Some are even happy that they can drive alone in an HOV lane because of their car’s technology.

Because these are the things that matter most to consumers, it makes little sense for a company to push the AI marketing line unless it becomes a selling point based on the experience it provides. For companies to say they’re utilizing AI just for the sake of saying it, without quantifying its effects in any way, seems disingenuous.

When companies can say that their AI technology is not only smart enough to respond in microseconds but powerful enough to understand consumers’ habits, history and tendencies based on past experiences in the same amount of time and with personalized results, then they can credit their AI technology for delivering a great experience.

But in the end, the experience is what consumers judge and what leads to repeat business — and referrals.