Considering we started talking about AI almost two decades ago, it's perhaps surprising that it is only just starting to make an impact on enterprises today. Certainly, this is the case with retail -- today's omnichannel shopping environment has placed a premium on efficient and relevant interactions with brands. Retailers recognise that AI, and specifically machine learning, has the ability to handle vast amounts of data and is able to use that data to identify patterns and to make decisions with minimal human intervention. In today's market conditions, this is an extremely appealing proposition; to be able to deliver more relevant shopping experiences whilst increasing operational efficiency at the same time. However, in many cases the anticipation of AI is still greater than its actual impact on day-to-day life for the vast majority of retailers.

The retail market is becoming increasingly competitive. Customers are expecting more personalised offers and are also more aware of their choices. Operational costs are rising and the amounts of data retailers need to factor in when setting prices are accumulating nonstop. As a result, businesses are hunting for new strategies to increase revenue. Currently, the pricing process is in chaos.

Amazon has long used robots to help humansmove merchandise around itswarehouses. Now automation is transforming Amazon's white-collar workforce, too. The people who command six-figure salaries to negotiate multimillion-dollar deals with major brands are being replaced by software that predicts what shoppers want and how much to charge for it. Machines are beating people at the critical inventory decisions that separate the winners and losers in retail. For the staffers deciding how many books, games or plastic pool toys to peddle, the tradeoff can be stark: Order too little and you miss out.