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Debunking The 4 Biggest Myths About Artificial Intelligence in Retail

Retailers must separate fact from fiction as they implement AI solutions.

J.P. Pressley is a contributing writer to BizTech magazine and an editor at Manifest.

Some people fear that artificial intelligence (AI) will take over the world. That’s not going to happen — not how it does in the movies, anyway. It’s a myth.

There are many popular myths circulating about AI, according to reports by PwC and Gartner. And as retailers integrate AI solutions into their businesses, it’s important to know which common beliefs about the technology are myths and which ones are factual.

Here are four big AI myths — and the truths about them.

Myth No. 1: Intelligent Machines Learn on Their Own

Though some machine learning (ML) products may give the impression that a machine can learn on its own, even the most intelligent ones don’t get that way autonomously. Intelligent machines aren’t self-sufficient. They need human intervention and prompting to develop over time.

A blog from the Massachusetts Institute of Technology’s Sloan School of Management explains: “Programmers choose a machine learning model to use, supply the data, and let the computer model train itself to find patterns or make predictions. Over time, the human programmer can also tweak the model, including changing its parameters, to help push it toward more accurate results.” Machine learning does use automation, but only to an extent.

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Myth No. 2: AI Is 100% Objective

People are intrinsically biased. And our biases aren’t limited to race: We can prefer spicy foods over sweet dishes or have a strong affinity for science fiction movies over rom-coms. Since AI is based on a variety of human-generated inputs, it shouldn’t be surprising that AI can also be biased.

You’re addressing where human error comes in, because the training data you use could have human biases.”

Michele Goetz Vice President and Principal Analyst at Forrester

ChatGPT is a good example of this kind of bias. Recent research shows that ChatGPT leans liberal, having picked up political biases from its training data. A separate study also revealed that ChatGPT showed gender bias in recommendation letters it wrote for hypothetical male and female job candidates. Though 67 percent of recruiters say that AI has improved the hiring process, another recent study found that AI-enabled recruitment, while not without its upsides, “results in discriminatory hiring practices based on gender, race, color, and personality traits,” according to an article in Humanities and Social Sciences Communications.

These issues reflect the biases of the humans behind the inputs that AI leverages. As Michele Goetz, vice president and principal analyst at Forrester, told BizTech, “You’re addressing where human error comes in, because the training data you use could have human biases.”

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Myth No. 3: AI Can Fully Understand Consumer Preferences

When it comes to understanding consumer preferences, AI is like a meteorologist making a weather forecast. They both use data to make predictions as accurately as possible based on pattern recognition and other factors. This leads to predictions that are often (but not always) accurate. But while historical data points might not change, the variables of the present can, and these unexpected changes can lead to inaccuracies.

It’s also worth noting that consumer behavior isn’t limited to consumer preferences but is instead the result of a wide range of intangible factors. And while AI is especially helpful in assisting with decision-making when the factors involved are beyond human comprehension, “AI notoriously fails in capturing or responding to intangible human factors that go into real-life decision making — the ethical, moral and other human considerations that guide the course of business, life and society at large,” notes the Harvard Business Review.

Myth No. 4: AI Adoption Is Only for Large Retailers

Certainly, the size of a retailer will influence what kind of AI technologies it can implement. But just because a small or midsized business can’t adopt AI technology at the same scale as a larger retailer, that doesn’t mean that it shouldn’t adopt AI at all. There are a wide range of accessible and scalable AI solutions — including cloud-based ML tools — that retailers can tailor to their unique needs and leverage to better achieve their business objectives in a competitive market.

Not sure how to get started with AI? Major technology brands such as CDW, IBM, Google, Microsoft and NVIDIA have a wide range of solutions to meet your needs. Don’t hesitate to reach out and take advantage. No matter how big or small the business, AI adoption doesn’t have to be a solo journey.

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