AI systems are prepared to learn – but are we ready to teach them?

Artificial intelligence could transform retail beyond recognition – but only if teaching is part of the rollout strategy.

Today’s retailers touch base with their customers well beyond their physical stores. No longer confined to shopping centres and the high street, retailers need to meet their customers where they are through an integrated marketplace: in their homes, in their workplaces, in their cars, and in their hands.

The explosion in connected devices and customers is creating huge volumes of digital ‘exhaust’ that retailers can analyse for buying trends, consumer desires, and patterns of behaviour. But, to harness this effectively retailers need a new breed of AI system: one that can identify and extract the signals that are meaningful from those that are just noise.

To see AI systems as the one-stop-shop solution for successful analytics would be misguided. Before organisations can extract and exploit insights, they need to ‘teach’ their system using high-quality data. Low-quality data means the AI system produces distorted, inaccurate results that risk harming the business – instead of helping it. Therefore, retailers have everything to gain from putting their datasets through rigorous vetting and cleansing processes before they’re deployed.

Knowing where to roll out the AI system is also critical to the education process: ask it to manage multiple disciplines at once, and you lose your focus. The most successful implementers identify a specific business pain-point: it could be customer- or employee-facing, and train an AI system to address it.

Online groceries retailer Ocado, for example, had to find a way to process customer queries rapidly and effectively even when there is a sudden deluge, at the same time as keeping its customers happy. It introduced advanced AI software that categorizes customer emails and provides customer service representatives with summaries and priority tags.

But first, Ocado did the groundwork. Before implementation it put the system through an extensive ‘training program’ where it learned from millions of past messages to ensure its email vetting processes were accurate. The result? The system successfully processes thousands of customer emails every day.

AI systems are not just being deployed exclusively by online retailers like Ocado, however. Large American supermarkets Target and Walmart, for instance, have both been experimenting with aisle-roaming robots that learn “on the job”. These autonomous units move through stores scanning barcodes to identify misplaced or out-of-stock items.

The AI that drives the robots learns to become more efficient over time which means productivity rates will climb further still.

Retailers that commit to training their AI systems for specific tasks gain a competitive edge. And, critically, because retail tends to use a number of fragmented, disparate systems, the sector is well-suited for optimisation by fully trained AI.

From automating back office processes to inventory and fulfillment systems and the supply chain, AI has the potential to transform retail.

Just like students without teachers, however, AI systems without any initial instruction lack direction and the retail industry gets less back. But put in the time at the beginning, give the systems the right material, and teach them to identify what is truly valuable, and the sector has much to gain.

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