With up to 52 seasons in Fashion it does not come as a surprise that the Fashion Industry is looking for more intelligent ways to predict consumer behaviour. Previously, the industry has relied on the past years' sales to set trends two years in advance. The forecasting model was set up to keep pace with how fast fashion moves. However, it suffers from great margins of error and an inability to adapt to unpredicted trends. 

Today we live in a data rich age. Machines are able to track and analyse data like never before. Not only is there the potential to transform the industry by providing new data points for trend setting and reducing the margin of error, it is poised to change the consumer experience entirely. From using voice bots for home shopping, to AI apps able to find items for sale from a photo. This is all set to improve the customer experience whilst generating new and valuable data for brands. Machine learning can also help spot counterfeit goods, as shown by it's use in customs.

However, following on from Friday's reports by the Centre for Data Ethics and Innovation (CDEI), as machine learning permeates all areas of our lives we need closer attention being paid to how personal data is being used. The line between 'personalisation' and 'exploitation' is thin. Without transparency, it is difficult to know how personal data is being collected and used. Consumers need a proper understanding of how their data is used, from credit brokers to fashion houses, before we can fully embrace the benefits without hesitation.