How is AI influencing the Alcohol Industry?
Artificial Intelligence is influencing the alcohol sector in a big way. But just how is one of our oldest industries being transformed by our newest technologies?
To comprehend the scale to which AI could be impacting the sector in the (very much immediate) years to come, we can investigate its potential role in every stage of the alcohol consumption process. From generating the perfect brewing recipes, to pouring the perfect pint, AI and machine learning technologies are beginning to have a revolutionary effect.
Recipe Generation
In several leading alcohol companies, AI’s involvement is already evident from the very beginning of the creative process. For example, ‘Mackmyre’, a Swedish single malt whiskey distillery, has incorporated machine learning algorithms to help perfect recipes. They feed these AI models data inputs such as existing combinations, sales statistics and customer preferences which, in turn, output millions of original ideas for potential recipes that are likely to be popular. A (human) master blender then tastes the final product and either affirms the recipe as a success or adjusts the combinations where necessary. As such, this is a terrific example of how AI and human expertise can work together to produce a quality creative product.
Brewing the Product
When it comes to production, we can call upon AB InBev – a Brazilian-Belgian brewing company responsible for mainstream names including Budweiser and Stella Artois – to offer examples of how AI can lend a helping hand. They use state-of-the-art AI networks to help predict the quality of their final product. Their systems analyze real-time data collected throughout the brewing process -including the amount of CO2 used and the length of time each stage takes to reach completion – and feeds this to the network. The resulting beer is then graded by professional beer tasters and these scores are also input into the AI model. By repeating this process, the algorithm can learn the optimum conditions required to produce the perfect product and, after further repetitions, the model can finetune these settings to produce an ever-improving brew. Again, we can see how human-AI interaction is crucial, as the process is reliant on human expertise informing systems on how the process can be bettered and perfected.
Product Distribution
AB InBev has also found a use for AI in the development of strong customer relations – customers being the outlets and distributors that sell their products to the public. They feed a separate machine learning algorithm information on how much a given outlet purchases, sells and doesn’t sell over a set period. Learning from this input, the algorithm can then inform on the amount of stock that should be delivered to each outlet as well as the payment terms that would be appropriate given the current season or weather conditions. Thus, stores are generally better stocked, wastage is reduced and both businesses benefit from AI’s involvement.